Improving Mental Healthcare: A Guide to Measurement-Based Quality Improvement

Improving Mental Healthcare A Guide to Measurement-Based Quality Improvement

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Improving Mental Healthcare A Guide to Measurement-Based Quality Improvement By

Richard C. Hermann, M.D., M.S. Director, Center for Quality Assessment and Improvement in Mental Health, Institute for Clinical Research and Health Policy Studies, Tufts-New England Medical Center; Associate Professor of Medicine and Psychiatry, Tufts University School of Medicine; Adjunct Associate Professor of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts

Washington, DC London, England

Note: The authors have worked to ensure that all information in this book is accurate at the time of publication and consistent with general psychiatric and medical standards, and that information concerning drug dosages, schedules, and routes of administration is accurate at the time of publication and consistent with standards set by the U.S. Food and Drug Administration and the general medical community. As medical research and practice continue to advance, however, therapeutic standards may change. Moreover, specific situations may require a specific therapeutic response not included in this book. For these reasons and because human and mechanical errors sometimes occur, we recommend that readers follow the advice of physicians directly involved in their care or the care of a member of their family. Books published by American Psychiatric Publishing, Inc., represent the views and opinions of the individual authors and do not necessarily represent the policies and opinions of APPI or the American Psychiatric Association. Copyright © 2005 American Psychiatric Publishing, Inc. ALL RIGHTS RESERVED Manufactured in the United States of America on acid-free paper 09 08 07 06 05 5 4 3 2 1 First Edition Typeset in Adobe’s Baskerville Book and Caecilia American Psychiatric Publishing, Inc. 1000 Wilson Boulevard Arlington, VA 22209-3901 www.appi.org Library of Congress Cataloging-in-Publication Data Hermann, Richard C., 1963– Improving mental heathcare : a guide to measurement-based quality improvement/ by Richard C. Hermann.— 1st ed. p. ; cm. Includes bibliographical references and index. ISBN 1-58562-088-2 (alk. paper) 1. Mental health services—United States—Quality control. 2. Mental illness—Treatment—United States—Quality Control. 3. Psychiatry—United States—Quality control. 4. Outcome assessment (Medical care)—United States—Methodology. I. Title. [DNLM: 1. Mental Health Services—United States. 2. Data Collection—methods— United States. 3. Needs Assessment—United States. 4. Outcome and Process Assessment (Health Care)—methods—United States. 5. Quality Assurance, Health Care—methods— United States. 6. Quality Indicators, Health Care—United States. WM 30 H552i 2005] RA790.6.H47 2005 362.2’0973—dc22 British Library Cataloguing in Publication Data A CIP record is available from the British Library.

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Contents

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .ix Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xi

Part I Role of Process Measures in Quality Assessment and Improvement

1

Quality Assessment and Improvement in a Changing Healthcare System . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2

Measuring Clinical and Administrative Processes of Care . . . 27

3

Selecting Process Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

4

Comparing and Interpreting Results From Process Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

5

Role of Measurement in Quality Improvement. . . . . . . . . . . . 97

Part II National Inventory of Mental Health Quality Measures

6

Guide to Inventory Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137

7

Prevention Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143

8

Access Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157

9

Assessment Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211

10

Treatment Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255

11

Coordination Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451

12

Continuity Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 489

13

Patient Safety Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 569 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 647 Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 655 Measures Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 661 Index of Measures by Domain of Quality . . . . . . . . . . . . . . . 669 Index of Measures by Diagnosis . . . . . . . . . . . . . . . . . . . . . . 677 Index of Measures by Treatment Modality . . . . . . . . . . . . . . 681 Index of Measures by Population Characteristics . . . . . . . . . 687 Index of Measures by Data Source . . . . . . . . . . . . . . . . . . . . 689

Acknowledgments

T

his book is based on research conducted at the Center for Quality Assessment and Improvement in Mental Health (CQAIMH) and funded by the U.S. Agency for Healthcare Research and Quality, the National Institute of Mental Health, and the Substance Abuse and Mental Health Services Administration. Additional support was provided by the Evaluation Center at Human Services Research Institute, the Institute for Clinical Research and Health Policy Studies at Tufts-New England Medical Center (NEMC), and the Tufts-NEMC Research Fund. CQAIMH research staff contributing to this work included Jeff Chan, Julie Regner, Caitlin Rollins, Scott Provost, Dawei Yang, Edward Chiu, Chet Jakubiak, and Greta Lagodmos. Acknowledgment is also due Drs. Robert Dorwart, Heather Palmer, and Kenneth Wells for their generous mentorship, as well as to my wife, Whitney Hermann, for her enthusiastic support.

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Foreword

I

n current proposals for Medicare reform, pay-for-performance plans for reimbursement have been widely discussed as a means of improving the quality of health care services. Although the details of how health insurance managers of Medicare benefits will actually evaluate performance are yet to be defined, it is likely that they will attempt to measure the adequacy of diagnosis and the degree to which treatments follow professional guideline recommendations for specific procedures, medications, and psychosocial interventions in the most cost-effective treatment settings. To the degree that it can be assessed, failure to monitor treatment errors or to coordinate care between hospitals, partial care, nursing homes, and outpatient settings will likely result in reduced payments that will penalize low levels of performance and reward those at higher levels. Although fee-for-service programs such as Medicare may not have the capacity to monitor prevention, access to care, continuity, and coordination of care (in addition to treatment and safety), such concerns will be present in large health maintenance organization (HMO) plans that have capitated responsibilities for the total health care of a defined beneficiary population. In the latter groups, process measures in all of these additional areas may be used to manage the range of services that are necessary for patients but are beyond the responsibility of a single physician. In the largely fragmented and disorganized U.S. mental health system, attempts to monitor all of the above aspects of healthcare have taken place in many different settings and delivery systems. Dr. Hermann describes the efforts of clinicians, hospitals, insurance plans, managed care organizations, accrediting groups, and government agencies to develop methods to measure and thereby improve the quality of mental health care. Presidential commission and Institute of Medicine reviews have been conducted on healthcare quality over the past two decades and have noted particular challenges in the

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area of mental health quality assessment. However, as mental health services have increasingly been integrated into federal Medicaid and Medicare systems, rather than under separate state mental health systems, the pressure for similar treatment of health and mental health care will continue to rise. The recent move of Medicare to bring mental health hospital treatment under a prospective payment system (PPS) that relies on diagnosis-related groups (DRGs) is another indicator of the pressure to use similar standards for general medical and mental health services. As a result of the above-mentioned trends, one can expect to see an increasing amount of attention to the measurement of quality in mental health services. For those who need to acquaint themselves with the current state of the art in quality assessment, this volume can offer a very useful guide. In addition to laying down the conceptual framework for measuring different aspects of mental health treatment and comprehensive services, it provides an inventory of 275 quality improvement (QI) process measures that have been developed and used in the United States. The author specifically notes that he is not including the more-difficult-to-develop outcome measures that might be applicable across different treatment settings. A similar inventory of outcome measures and a future integration of both process and outcome measures is undoubtedly the holy grail of quality assessment for any healthcare system—one that is unlikely to be obtained in the short term. Although there is a tremendous variation in the degree to which these process measures have been tested and used in real-world treatment settings, Dr. Hermann provides a succinct description of the characteristics of each one. This volume provides an introduction to the landscape of quality measurement in mental health systems, which can enable the readers to evaluate which measures might be most appropriate for a given system in which they operate. As mentioned by the author, there is no bright beacon to point the way for measuring the quality of mental health services in any particular setting. However, for many who currently are operating in the fog created by our complex de facto mental health system, these chapters can illuminate areas where measurement has led to the improvement of patient care that can be documented—to the benefit of all parties involved in the provision and payment of mental health services. Darrel A. Regier, M.D., M.P.H.

Introduction

E

nvision a healthcare system in which patients are routinely screened for psychiatric disorders, and every case is detected. All patients presenting with a psychiatric problem receive a thorough clinical assessment, whether in primary care or the mental health sector, leading to an accurate diagnosis. Initial evaluations routinely address common comorbidities of mental illness, including substance abuse and medical conditions. Access to mental healthcare is equitable, timely, and unimpeded by inadequate availability, delays, or financial barriers. Treatment routinely reflects guideline recommendations that are based on research studies and consensus among experts, yet is tailored to circumstances and preferences of individual patients. Selection of psychotropic medications is appropriate to diagnosis, clinical presentation, and associated patient characteristics. Dosages outside recommended therapeutic ranges are prescribed only rarely and for well-documented reasons. Duration of medication treatment is adequate to achieve its intended goals. Psychosocial interventions are similarly well matched to patient needs and delivered with fidelity to proven models. Patients receive treatment at the most appropriate level of care at each phase of their illness and experience continuity of care as they transition from one level of care to the next. In partnership with patients, families, and case managers, clinicians coordinate the patient’s care, bridging gaps among facilities, therapists, and prescribing clinicians; between mental health and substance-related care; between psychiatric and primary care; and among the healthcare, education, and socialservice systems. Care is delivered safely, with a minimum of errors, injuries, or unnecessary use of coercive interventions such as commitment or restraints. Prevention, access, assessment, treatment, continuity, coordination, and safety: these are clinical processes that compose mental healthcare. Each day hundreds of thousands of clinicians and staff members execute these pro-

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cesses effectively. It is also true, however, that nationwide studies have found that the quality of mental healthcare varies widely—as is true elsewhere in medicine. Substantial gaps have been observed between evidence-based practice guidelines and clinical care as it is actually delivered. Lower-than-optimal rates of detection, assessment, and coordination have been observed. Barriers to access and continuity of care have been identified. Variations in quality of care have been shown to influence critical clinical outcomes: rates of remission and relapse, severity of symptoms and functioning, and patients’ quality of life. Factors contributing to these variations are complex, including organizational, financial, and educational characteristics of the healthcare system as well as differences among patients. Many are the result of the U.S. healthcare system’s desultory evolution. Even more than most of the healthcare system, mental healthcare represents a patchwork of specialty and primary care settings; state, federal, and private sector financing; and diverse organizational systems. “Every system is perfectly designed to achieve the results it achieves,” observed Donald Berwick (1996, p. 619), in advocating integration of routine, measurement-based quality improvement (QI) into the daily work of delivering care. We need to broaden our conception of quality from examining individual practice to assessing the functioning of our delivery systems and in the process, as Berwick puts it, “reframe performance from a matter of effort to a matter of design.” Over the past two decades, groups representing the varied “stakeholders” in the U.S. health system—consumers and families, clinicians, hospitals, plans, payers, managed care organizations, purchasers, accreditors, and government agencies—have fostered a national movement to promote routine assessment and improvement in quality of care. Central to QI is the ability to measure quality in its many dimensions. Measurement can be used to identify a problem with quality of care, determine its magnitude, and motivate change. If participants intervene to improve a flawed clinical process, reassessment can evaluate the effectiveness of the intervention to determine whether it should be implemented more broadly or set aside. In some ways, measurement-based QI is new to clinicians. It requires that we expand our view of care beyond our individual work with a patient and consider the patient’s outcomes as the result of all of his or her interactions with the healthcare delivery system. It asks us to work collectively to address problems in these interactions (e.g., a lack of coordination among clinicians) rather than assuming responsibility for only our own contributions to care. In other ways, clinicians will find QI to be familiar. Like clinical practice, QI employs an empirical approach that draws upon inductive reasoning: one develops a hypothesis, tests it through intervention, and reevaluates to assess impact.

Introduction

❚ xiii

❚ STATUS OF PROCESS MEASUREMENT Measuring quality requires tools that are valid, reliable, and sensitive to change. However, many process measures were designed for use in research studies that resembled archeological digs: expensive, comprehensive, and retrospective excavations into quality of care for a single condition, at a single site, at a single point in time. Although scientifically sound, many of these measures are too burdensome and, in total, too numerous for routine use in measurement-based QI. Organizations providing care, such as practices, clinics, hospitals, and health plans, need a smaller group of meaningful and feasible measures to inform and facilitate QI. Rather than acting as archeologists, we need to work like meteorologists, positioning a limited number of sensors at strategic nodes amid the multidimensional matrix of populations, conditions, modalities, and settings comprising the mental health system to obtain serial, real-time information on critical processes of care. In 1998, a presidential commission on healthcare quality noted that measurement for mental health and substance-related care was particularly underdeveloped (President’s Advisory Commission on Consumer Protection and Quality in the Health Care Industry 1998). Subsequently, groups representing diverse stakeholders in the mental health system have proposed hundreds of measures to assess quality of care. A systematic assessment found these measures to vary greatly in terms of their development, scientific properties, and foundation in research evidence (Hermann et al. 2000, 2002a, 2002b). Accordingly, a number of initiatives are under way to develop consensus among stakeholders around a limited number of measures for common use.

❚ GOALS AND AUDIENCE FOR BOOK This book examines the clinical, policy, and scientific underpinnings of process measurement, methods to develop or identify measures meeting specific needs, and ways healthcare organizations can use process measures to improve the quality of mental healthcare. Each of the stakeholders in the mental health system would benefit from an understanding of quality measurement, particularly as measurement results come to play a larger role in healthcare. Clinicians are likely to see their professional standing, payment levels, and credentialing determined in part by their performance on quality measures. They will be asked to participate in measurement-based QI projects in the organizations where they practice. Clinics, hospitals, and health plans are increasingly adopting QI methods, both in response to external requirements

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and in pursuit of their own needs to achieve high standards of care while improving efficiency. Accreditors, payers, and other oversight groups increasingly require healthcare organizations to participate in comparative quality assessment activities. The resulting data are provided as feedback to participating organizations to motivate improvement and, in the future, is likely to be disseminated to employer-purchasers and consumers with the intent of stimulating competition based on quality. With the emergence of these new roles, clinicians, managers, and payers will need to be familiar with principles of quality measurement and prepared to understand basic qualities of the measures themselves.

❚ OVERVIEW OF CONTENTS In response to the 1998 commission report, the U.S. Agency for Healthcare Research and Quality (AHRQ) launched an initiative to promote qualitymeasure development for vulnerable populations. Among a number of projects, they funded the Center for Quality Assessment and Improvement in Mental Health (https://www.cqaimh.org) to systematically inventory and evaluate quality measures for mental health and substance-related care. The National Inventory of Mental Health Quality Measures summarizes clinical, technical, and scientific properties of more than 300 process measures in a user-friendly format to help potential users find measures meeting their needs (Hermann 2004). Inventory data on 275 of these measures comprise the second half of this book. Section I of the book consists of five chapters. Chapter 1 describes the factors that have led to a nationwide emphasis on improving quality of care, including a growing body of research detailing problems of quality in both physical and mental healthcare. The chapter also provides an introduction to major approaches to quality assessment, including measurement of structures, processes, and outcomes of care. Chapter 2 further describes technical process measures, one of the most widely used methods of quality assessment. Among the topics addressed are the domains of process these measures assess, the purposes for which they are used, and how they are constructed. Chapter 3 provides guidance to clinicians, managers, and others needing to select measures for quality assessment and improvement, presenting a model for balancing the diverse considerations that are encountered. State, national, and international initiatives to identify quality measures for mental healthcare are described. Chapter 4 addresses methods of analyzing and interpreting results from quality assessment activities, including case-mix adjustment and the use of means, norms, standards, and benchmarks. Chapter 5 describes the use of process measures in QI. It reviews research on the effectiveness of

Introduction

❚ xv

measurement-based QI and provides a practical guide to conducting QI in mental healthcare organizations. Section II begins with a chapter that briefly describes methods used to collect and evaluate measures for the inventory. Subsequent chapters, organized by domain of process, provide information on each measure, including their clinical rationale, specifications, data sources, supporting evidence, and readiness for use as well as (where available) data on their reliability, validity, results, case-mix adjustment, standards, and benchmarks.

❚ CAVEATS This book is intended to be a volume amid a shelf of different approaches to quality assessment. Its focus on technical process measures should not be perceived as advocating this approach over other quality assessment methods such as evaluating interpersonal process, fidelity, or treatment outcomes. After 20 years of debate between advocates of measuring processes versus outcomes, it is now widely recognized that both approaches are essential and, in many cases, complementary (Hermann 2002). Process measures are the focus here because, despite their wide use, many proposed measures remain insufficiently developed or evaluated (Eddy 1998; Palmer 1997). Moreover, while several texts authoritatively review the status of outcomes measurement in mental healthcare (American Psychiatric Association Task Force for the Handbook of Psychiatric Measures 2000; IsHak et al. 2002; Lyons et al. 1997), there are no thorough assessments of process measurement. The intent of this book is not to recommend all of the measures presented. In fact, their scientific properties, clinical importance, and foundation in research studies vary widely. Instead, the purpose is to provide context and information on their strengths and limitations to inform clinicians, managers, and policy makers who may use them. In addition, by providing an assessment of the current status of the field, the book and inventory are intended as a foundation for further measure development, testing, and consensus development. Finally, the book’s working title, Points of Light, was left behind for reasons of practicality and prior political use. Yet as it implies, process measures do not function as beacons that broadly illuminate quality of care across healthcare systems. Rather, they provide a constellation of point-process assessments that can, collectively, contribute to an understanding of the quality of mental healthcare. Combined with other approaches and used judiciously, process measures can identify potential quality problems, provide insight into contributing factors, and guide efforts to improve care.

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❚ REFERENCES American Psychiatric Association Task Force for the Handbook of Psychiatric Measures: Handbook of Psychiatric Measures. Washington, DC, American Psychiatric Association, 2000 Berwick DM: A primer on leading the improvement of systems. BMJ 312:619–622, 1996 Eddy D: Performance measurement: problems and solutions. Health Aff 17:7–25, 1998 Hermann RC: Linking outcome measurement with process measurement for quality improvement, in Outcome Measurement in Psychiatry: A Critical Review. Edited by IsHak W, Burt T, Sederer L. Washington, DC, American Psychiatric Publishing, 2002, pp 23–55 Hermann RC: National Inventory of Mental Health Quality Measures. Center for Quality Assessment and Improvement in Mental Health, 2004. Available at: http://www.cqaimh.org/quality.html. Accessed July 12, 2005. Hermann R, Leff HS, Palmer RH, et al: Quality measures for mental health care: results from a national inventory. Med Care Res Rev 57 (suppl 2):135–154, 2000 Hermann RC, Finnerty M, Provost S, et al: Process measures for the assessment and improvement of quality of care for schizophrenia. Schizophr Bull 28:95–104, 2002a Hermann RC, Leff HS, Provost SE, et al: Process measures used in quality assessment and improvement: are they based on research evidence? Presented at the 15th National Institute of Mental Health Services Research Conference, Washington, DC, April 2002b IsHak W, Burt T, Sederer L (eds): Outcome Measurement in Psychiatry: A Critical Review. Washington DC, American Psychiatric Publishing, 2002 Lyons JS, Howard KI, O’Mahoney MI, et al: The Measurement and Management of Clinical Outcomes in Mental Health. New York, John Wiley and Sons, 1997 Palmer R: Process-based measures of quality: the need for detailed clinical data in large health care databases. Ann Intern Med 127:733–738, 1997 President’s Advisory Commission on Consumer Protection and Quality in the Health Care Industry: Quality First: Better Health Care for All Americans. Final Report of the President’s Advisory Commission on Consumer Protection and Quality in the Health Care Industry. Washington, DC, U.S. Government Printing Office, 1998

P A R T

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Role of Process Measures in Quality Assessment and Improvement

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C H A P T E R

1

Quality Assessment and Improvement in a Changing Healthcare System “A cadre of young researchers was trained in scientific management…including the use of chart-making, forms, and accountancy.” They reviewed allocation of resources and personnel, “to see if they were really needed.” Analyzing reams of data, they generated “report cards” that shed light on the quality of services in different areas. It was “nothing short of a revolution in the approach to such matters.” Caro 1975

This narrative was written to describe a 1907 initiative to upgrade mu-

nicipal services in New York City (Caro 1975). And yet, it accurately characterizes the rise of measurement-based quality improvement (QI) in recent years. QI originated early in the twentieth century, first in manufacturing and then spreading to other industries. Working in a research division of AT&T in 1926 (later Bell Laboratories), QI’s founders—statisticians, engineers, and theorists—were charged with developing a systematic process for what they

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named quality assurance: “to develop the theory of inspection [based] on mathematical knowledge…and new principles where existing knowledge is inadequate; to develop methods of stating the quality of various type of apparatus…to make regular reports on the current quality of these materials; to study the quality and performance of service as an aid to further and improved developments” (Wadsworth et al. 1986). Government support for training led to further diffusion of quality assurance during World War II. Ironically, manufacturers in the United States fully embraced these techniques only decades later, after the Japanese automobile industry, with the help of American consultants, demonstrated their usefulness. Early application of quality assurance in healthcare involved site visits of facilities and peer review of cases in which treatment resulted in adverse events. Measurement was used infrequently and mainly to assess structural features of facilities, such as the number of beds or patient-to-staff ratios. In recent years, measurement has played a larger role and measures have shifted from evaluating structures of care to assessing quality and outcomes. The retrospective evaluation characteristic of quality assurance has been supplanted by a forwardlooking model of quality improvement. The focus on individual adverse outcomes has broadened to include analyses of system-wide data describing routine care and outcomes. In some cases, quality measurement has expanded beyond an assessment of the care received to encompass all of a population’s healthcare needs, both met and unmet.

❚ QUALITY OF HEALTHCARE IN THE UNITED STATES One force compelling attention to quality improvement has been the accumulation of research showing that quality of care varies widely and frequently falls short of evidence-based standards. Quality of care as defined by the Institute of Medicine (IOM) is “the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge” (Lohr 1990, p. 21). Consistent with this definition, quality of care research has examined 1) underuse of healthcare services (or the failure to provide treatment expected to improve health outcomes); 2) overuse (or inappropriate provision of treatment under circumstances in which health benefits do not outweigh health risks); and 3) misuse (or treatment provision accompanied by a preventable complication or mistake) (Chassin and Galvin 1998). Research instruments have been developed to assess these three items, principally by comparing processes of care to standards derived from research evidence, practice guidelines, or recommendations of expert panels.

Quality Assessment and Improvement

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What is the magnitude of problems with quality of care in the United States? A 1998 review of research studies found that only 50% of samples studied received preventive care recommended by practice guidelines, whereas 70% received recommended care for acute conditions and 60% for chronic conditions (Schuster et al. 1998). Using a newly developed Community Quality Index based on 439 quality measures for 30 conditions, McGlynn et al. (2003) found that only 55% of a randomly selected sample received recommended care. There is no single explanation as to why the quality of healthcare falls short with such frequency, but a number of contributing factors are described below (Berwick et al. 1990; Chassin and Galvin 1998; Institute of Medicine 2001a; McGlynn 1998). • Growth in the volume and complexity of medical knowledge. Developments in psychopharmacology illustrate the challenge to clinicians presented by ongoing technological development. For many years, a few medication classes predominated among recommended treatments for major psychiatric syndromes: lithium for bipolar disorder, tricyclic and monoamine oxidase inhibitor antidepressants for depression, and traditional antipsychotic drugs for schizophrenia. Recent years have seen a profusion of new options: anticonvulsant mood stabilizers, atypical antipsychotics, and several classes of antidepressants. Releases of new medications are accompanied by innumerable research studies weighing their effects; many of these reports are rigorous and informative, while others are a by-product of aggressive marketing. Despite advances in synthesis and dissemination, the diffusion of clinical knowledge remains slower than desirable. • Increased prevalence of chronic conditions. Increased life expectancy has contributed to an increased prevalence of individuals with chronic illnesses. Adequate treatment of these conditions requires the active participation of patients with varying levels of education, resources, and support. A number of interventions emphasizing collaborative care have been shown to improve quality and outcomes of care for chronic conditions, but these interventions have not been widely adopted. • A healthcare system that is decentralized, fragmented, and difficult to navigate. After two decades of rapid change, the organization and financing of care present challenges to patients and clinicians alike. As one IOM task force concluded, “Care delivery processes are often overly complex, requiring [multiple] steps and handoffs,…waste resources, leave unaccountable gaps in coverage, result in the loss of information, and fail to build on the strengths of all health professionals involved to ensure that care is timely, safe and appropriate” (Institute of Medicine 2001a, p. 28). • Variability in available resources. Studies of area variation in the use of effective medical and mental health interventions provide evidence that the avail-

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ability of clinicians and facilities, adequate health insurance, and state policies regarding insurance and clinical practice all influence quality of care (Fortney et al. 1996; Hermann et al. 1995; Paul-Shaheen et al. 1987; Rosenheck and Astrachan 1990; Sturm et al. 2003). • Lack of professional consensus. Although not as rigorously studied, professional uncertainty about the value of specific treatments may also contribute to variations in clinical practice. Available evidence suggests practices well grounded in research studies and consensus among clinicians may vary less than practices that lack supporting research and consensus (Wennberg et al. 1982). Despite the growing evidence basis for clinical practices in mental healthcare, the diversity of theoretical orientations among clinicians contribute to variation in mental health practices (Hermann 1996; Hermann et al. 1995).

❚ QUALITY OF MENTAL HEALTH AND SUBSTANCE-RELATED CARE Quality of care for mental health and substance use disorders has been subject to study because of the prevalence, morbidity, and treatability of these conditions. An estimated 19%–29% of Americans have a psychiatric disorder in a given year (Kessler et al. 1994; Narrow et al. 2002). A World Health Organization study found these conditions accounted for almost 11% of the global burden of disease. Five of the 10 leading causes of disability (in years of life lived with disability) are psychiatric conditions—depression, bipolar disorder, schizophrenia, obsessive-compulsive disorder, and alcohol abuse (Murray and Lopez 1996). The United States spends an estimated $82 billion annually on psychiatric care, with additional indirect costs in terms of nonpsychiatric medical utilization, criminal justice costs, burden on families and other informal caregivers, and lost work productivity (Broadhead et al. 1990; Croghan et al. 1998; Rice et al. 1992; SAMHSA 1998). Many psychiatric conditions can be effectively treated with somatic and psychosocial interventions, resulting in reduced symptoms and improved functioning (Gabbard 1995). Clinical research on the efficacy of psychiatric treatments have been synthesized into practice guidelines by the Agency for Healthcare Research and Quality, American Psychiatric Association, Veterans Health Administration, and other organizations (Agency for Health Care Policy and Research Depression Guideline Panel 1993a; American Psychiatric Association 2002; Veterans Health Administration Office of Quality and Performance 2002). These guidelines provide a robust basis from which to compare clinical practice with evidence-based recommendations. Studies of quality of care for mental disorders and substance use disorders

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Quality Assessment and Improvement

show results comparable with other areas of medicine and surgery. McGlynn et al.’s 2003 nationwide study of quality of care found only 11% of patients with alcohol dependence and 58% of patients with depression received recommended treatment. Tables 1–1 through 1–5 summarize results from major studies of mental healthcare. They demonstrate substantial gaps between clinical practice and guideline recommendations for several major conditions, among them depression, bipolar disorder, panic disorder, schizophrenia, and anxiety disorders. Similar findings are seen across treatment modalities, clinical settings, systems of care, and geographic regions. Because the studies vary in sampling methods and measure specifications, results are not comparable across disorders or settings. For example, higher rates of appropriate antidepressant dosages were found in Veterans Administration (VA) medical centers than in non-VA primary care practices. However, the VA sample consisted of patients diagnosed with depression by their clinicians, whereas the latter sample included all primary care patients with depression, regardless of whether the condition had been detected by the patient’s clinician (Charbonneau et al. 2003; Wells et al. 1999).

TABLE 1–1.

Quality of care for patients with depression

Quality measures

Conformance (%)

Managed primary care* Treatment during index visit with depression Counseling alone

23.5

Referral for counseling

16.2

Initiated or adjusted medication

31.1

Any of the above

47.8

Appropriate dosage if on antidepressant

34.7

Veterans Health Administration**

Acute

Continuation

Maintenance

80

91

91

Antidepressants for adequate duration

61

43

44

Three or more visits during acute phase

62

–

–

Antidepressant above minimally adequate dosage

*1,204 outpatients with depression in 46 primary care clinics in five states, 1996–1997 (Partners in Care Study; Wells et al. 1999). **12,678 patients diagnosed with depression in 14 Northeast Veterans Health Administration Medical Centers, 1997–1999 (Charbonneau et al. 2003).

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TABLE 1–2. Quality of care for health maintenance organization patients diagnosed with bipolar disorder Quality measures Prescription for a mood stabilizer during 1-year period Interruption of mood stabilizer during initial 3 months

Conformance (%) 83 46

Mood stabilizer dosage probably adequate

36–39

One or more blood levels in 210 days of mood-stabilizer treatment

39–53

One or more blood tests for medication-specific adverse effects in 210 days of mood-stabilizer treatment

13–60

Note. 1,246 adults diagnosed with bipolar disorder in a Seattle-area staff model health maintenance organization, 1995–1996 (Unutzer et al. 2000).

TABLE 1–3. Quality of medication treatment for primary care patients diagnosed with panic disorder Quality measures

Conformance (%)

Prescribed evidence-based medication during 3-month period

52

Adequate daily dosage for 6 weeks or longer

34

Adherent to medication for 25 days or longer

28

Note. 58 patients diagnosed with panic disorder under usual care in three Seattle primary care clinics, 2000 (Roy-Byrne et al. 2001).

Few studies have examined the quality of care for substance use disorders. Greater clinician adherence to manualized psychotherapies for these disorders has been associated with better outcomes, but these treatments are not in wide use. Several small studies have explored differences in clinician and facility-specific rates of client attendance, inpatient discharge against medical advice, and program completion (Najavits et al. 2000). However, these measures are not clearly indicative of quality of care. For other psychiatric interventions, evidence suggesting over- or underuse is inferential, drawn from studies showing high rates of practice variation across settings and geographic areas. This type of study does not identify individual cases of inappropriate care but can identify clinical procedures or treatments which are likely to be over- or underused. For example, studies have shown utilization rates of physical restraint to vary widely across inpatient facilities with similar patient populations. Differences in staff decision making, including thresholds for restraint use, have been

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Quality Assessment and Improvement

TABLE 1–4. Quality of care for patients diagnosed with schizophrenia Quality measures

Conformance (%)

Medication Antipsychotic prescribed on hospital discharge

89.2

Dosage within recommended range

62.4

Antipsychotic prescribed for outpatient maintenance care

92.3

Dosage within recommended range

29.1

Outpatients with extrapyramidal symptoms prescribed antiparkinson medications

46.1

Psychosocial treatment Outpatient psychotherapy or counseling

45.0

Outpatient family education and support

9.6

Outpatient vocational rehabilitation

22.5

Note. 719 patients diagnosed with schizophrenia in two states, 1998 (Schizophrenia Patient Outcomes Research Team [PORT] Study; Lehman 1999).

TABLE 1–5. illness

Quality of care for patients with serious mental

Conformance (%)

Quality measures One or more visits for a mental health problem in prior 12 months Received evidence-based medication and four or more physician visits, or received eight or more psychotherapy visits (mood and anxiety disorders only)

Anxiety disorder

Mood disorder

Non-affective psychosis

39.4

45.8

55.9

18.9

21.8

4.1

Note. 5,877 survey respondents, ages 15–54, with a psychiatric condition from a nationally representative community-based sample, 1990–1992 (National Comorbidity Survey; Wang et al. 2002).

shown to contribute to this variation (Busch and Shore 2000). Another study found per capita utilization rates of electroconvulsive therapy (ECT) in 317 U.S. cities to vary more than nearly any procedure in medicine (Hermann et al. 1995). ECT use rates ranged from 0.4 to 81.2 patients treated per 10,000 population. In contrast, the prevalence of major depression—the primary

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clinical indication for ECT—varies only twofold across geographic regions. Greater ECT use was related to higher concentrations of psychiatrists, primary care physicians, and psychiatric hospital beds per capita as well as less stringent state legal regulation. A subsequent study using administrative data from a large commercial insurer found that 14% of patients treated with ECT had diagnoses outside evidence-based treatment indications (Hermann et al. 1999). ECT was more likely to be used for non-evidencebased diagnoses by psychiatrists trained in earlier decades, suggesting a role for targeted education. Other studies report a lack of consensus among clinicians regarding ECT’s utility (Janicak et al. 1985; Kalayam and Steinhart 1981), an illustration of the “professional uncertainty” that is believed to be a component of high-variation procedures. Patients’ racial or ethnic status as well as age, financial status, and other sociodemographic characteristics have been shown to be associated with disparities in quality of care. Many studies of medical and surgical treatments and a small number of studies in mental healthcare have found that members of racial or ethnic minority groups received lower quality of care than white, non-Hispanic populations (Alegria et al. 2002; Chow et al. 2003; Institute of Medicine 2002; Schneider et al. 2002; U.S. Public Health Service 2001). Deficits in quality have also been observed in clinical processes other than treatment. Problems with access to mental health and substance-related care are well known and have been summarized in several national surveys and reports (Andrews and Henderson 2000; Etheridge et al. 1995; U.S. Department of Health and Human Services 1999). Prevention, particularly early detection and treatment, provides significant opportunities for improving care. Approximately 30%–50% of patients with a depressive disorder seen in primary care are not diagnosed or treated (Joseph and Hermann 1998). Substance-use disorders are frequently undetected by both primary care and mental health clinicians (National Institute on Alcohol Abuse and Alcoholism 1993). Psychiatric treatment is often not accompanied by adequate clinical assessment. For instance, Wells et al. (1993) examined medical records of 1,198 elderly patients hospitalized for treatment of depression in 297 acutecare general medical hospitals and found that records lacked documented assessment of suicidal ideation (46%), cognitive status (26%), psychosis (50%), and psychiatric history (19%). Numerous studies illuminate problems with continuity of care for individuals with psychiatric disorders, including multiple transfers of patients among providers, missed handoffs during transitions across levels and sites of care, lapses in communication, and gaps between planning and follow-through (Adair et al. 2003; Johnson et al. 1997). Other studies have depicted variability in coordination of patient care among mental health clinicians and their counterparts in substance-related care, primary care, and social services (Felker et al. 1996; Lima and Brooks 1985; Rach-

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Beisel et al. 1999). Safety is an understudied topic in mental healthcare, but areas warranting attention include medication errors as well as staff and patient injuries (Institute of Medicine 1999). Reasons for the gaps in quality detected by these studies are multiple and complex, including patient factors beyond providers’ control. However, the deficits are widely believed to be at least partially remediable. Controlled studies of system-wide interventions have achieved significant improvement in many clinical processes, with concurrent improvement in clinical outcomes (Gilbody et al. 2003; Herz et al. 2000; Katon et al. 1999; Roy-Byrne et al. 2001; Wells et al. 1999).

❚ NATIONAL AGENDA FOR QUALITY ASSESSMENT AND IMPROVEMENT Mobilized in part by research findings such as those just described, groups representing diverse stakeholders in the healthcare system are converging to launch a national agenda for QI. One of the most visible expressions of this movement to date is an influential series of reports by the IOM, a component of the National Academy of Sciences. These studies have synthesized existing data on quality and safety; linked these findings to underlying clinical, organizational, and financial characteristics of the healthcare system; and called for sweeping, extensive change (Chassin and Galvin 1998; Institute of Medicine 1997, 1999, 2001a, 2001b, 2003). A principal mechanism of the IOM’s vision for reforming and improving healthcare is “the establishment of monitoring and tracking processes for use in evaluating progress…[toward] safety, effectiveness, patient-centeredness, timeliness, efficiency and equity” (Institute of Medicine 2001a, p. 7). A 1998 report of the President’s Commission on Consumer Protection and Quality in the Health Care Industry also emphasized a central role for measurement in motivating and facilitating nationwide QI efforts. The commission called for standardized reporting made possible through “development of core sets of quality measures applicable to each sector of the industry” (President’s Advisory Commission on Consumer Protection and Quality in the Health Care Industry 1998). This agenda has been echoed among policy makers involved in mental healthcare. Between 1999 and 2001, the U.S. Surgeon General issued three reports addressing the need for concerted efforts to improve mental healthcare; one specifically focused on care for children, another on disparities in care by culture, race, and ethnicity (Office of the Surgeon General 2001; U.S. Department of Health and Human Services 1999; U.S. Public Health Service 2001). A National Institute of Mental Health–sponsored workgroup, in a

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1998 report to Congress, called for “constructing monitoring tools and systems to assess adherence to guidelines, [which are] important for developing a capacity to monitor the quality of routine care. Such monitoring helps identify areas where practice needs to be improved, appropriate questions for efficacy and effectiveness research, and gaps between evidence-based treatment and prevailing practice” (National Advisory Mental Health Council Clinical Treatment and Services Research Workgroup 1998, p. 28). The 2002 report of the President’s New Freedom Commission on Mental Health highlighted the underuse of evidence-based practices for treatment of severe mental illnesses (Table 1–6) and called for development of methods to encourage their adoption (President’s New Freedom Commission on Mental Health 2003). Payers and purchasers have brought economic forces to bear on healthcare delivery in ways that have encouraged attention to quality. As healthcare costs doubled in the 1970s and again in the 1980s, private and public sector payers, along with employer purchasers, pressed for “accountability” in healthcare delivery. This signified a desire for information assessing the health benefits of their investment in healthcare. In response, payers, accreditors, and government agencies began to measure access, quality, and outcomes of care. Resulting data have been used for reporting and contracting as well as for encouraging improvement through comparative assessment and feedback to providers and consumers. Increasing healthcare costs also gave rise to a host of cost containment strategies that in turn raised concerns among consumers and clinicians about quality and increased their interest in indicators of quality of care. One costcontainment strategy, utilization management, uses criteria to determine the type and intensity of care eligible for payment. In addition, health plans built or contracted with networks of providers to manage the delivery of care more directly. A third approach, the transition in payment methods from fee-forservice reimbursement to fixed rates (e.g., for a hospital stay, episode of care, or covered enrollee), flipped financial incentives to providers from favoring overuse of services to favoring underuse. Two additional developments, consolidation of healthcare providers and computerization, contributed to the rise of quality assessment. As long as healthcare remained largely a cottage industry of independent practices, facilities, and insurers, there was little infrastructure available to assess quality across providers or coordinate improvement initiatives. The expansion of public insurance programs, hospital mergers, development of provider networks, and growth of integrated systems and health plans contributed to the development of common standards for data collection and assessment methods. The growth in use of computer-based information systems to facilitate clinical, operational, and financial activities provided opportunities

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TABLE 1–6. Selected evidence-based and emerging practices in mental healthcare Evidence-based practices* •

Specific medications for specific conditions

•

Cognitive and interpersonal therapies for depression

•

Preventive interventions for children at risk for serious emotional disturbances

•

Treatment foster care

•

Multisystemic therapy

•

Parent–child interaction therapy

•

Medication algorithms

•

Family psychoeducation

•

Assertive community treatment

•

Collaborative treatment in primary care

•

Training in illness self-management

•

Supported employment

•

Integrated treatment for co-occurring substance use disorders

Emerging best practices** •

Consumer-operated services

•

Jail diversion and community reentry programs

•

School mental health services

•

Trauma-specific interventions

•

Wraparound services

•

Multifamily group therapies

•

Systems of care for children with serious emotional disturbances and their families

* Treatments and services whose effectiveness is well documented. ** Promising treatments and services that are less thoroughly evidence based. Source. Adapted with permission from New Freedom Commission on Mental Health: Achieving the Promise: Transforming Mental Health Care in America. Final Report. DHHS Pub. No. SMA-033832. Rockville, MD, New Freedom Commission on Mental Health, 2003; and Drake RE, Goldman HH, Leff HS, et al: “Implementing Evidence-Based Practices in Routine Mental Health Service Settings.” Psychiatric Services 52:179–182, 2001.

to collect comparable data across large numbers of providers as well as to implement guidelines, utilization criteria, and other decision-support systems. Consolidation and computerization in healthcare are ongoing processes; vast heterogeneity remains among healthcare organizations and information systems. Thus, although these trends have fueled quality assessment and improvement activities, their present status is a rate-limiting step to further progress.

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❚ METHODS OF QUALITY ASSESSMENT Methods of quality assessment can be organized into three perspectives— structures, processes, and outcomes of care—based on a framework developed by Avedis Donabedian in the 1970s (Donabedian 1980) and subsequently elaborated and applied to mental healthcare (Table 1–7). Structures represent the human, physical, and organizational components of the healthcare system. Processes represent interactions between patients and the healthcare system. Outcomes are the results of these interactions on patients. Quality measurement from each perspective can provide valuable insights. The sections that follow summarize methods of assessing structures, processes, and outcomes in mental healthcare as well as discuss the strengths and weaknesses of each method. It should be noted that subsequent frameworks have elaborated on Donabedian’s tripartite model, identifying additional foci for quality assessment and improvement activity. An influential IOM framework highlights the central role of the patient and family’s experience of care, and calls for patient-centered approaches to improvement. Against a matrix that also highlights timeliness, effectiveness, and efficiency of care, the IOM framework emphasizes cross-cutting domains of safety and equity. Furthermore, this framework distinguishes among acute, chronic and end-of-life care, underscoring that quality is a concern at each stage of treatment (Institute of Medicine 2001a, 2001b)

TABLE 1–7.

Framework for assessing quality of care

Structure

Process

Outcome

Clinician characteristics

Interpersonal processes

Symptoms

• Communication Facility/Plan characteristics

• Decision making

Functioning

• Interpersonal style Financing characteristics

Technical processes

Quality of life

• Prevention • Detection

Adverse events

• Access • Assessment

Satisfaction

• Treatment/Fidelity • Coordination • Continuity • Safety

Cost-effectiveness

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Structural Measures Structural components of the healthcare system include clinicians, facilities, health plans, and the means of financing care. Characteristics of each component have been used as indicators of quality. Health plans use board certification in credentialing physicians, indicating an advanced level of education and training. Accreditors assess nurse-to-patient ratios in their periodic evaluations of hospitals, an indicator recently linked to better clinical outcomes of medical and surgical (not psychiatric) care (Needleman et al. 2002). The per capita rate of specialists in short supply, such as child psychiatrists, is used as an indicator of community-based access to care. As attention to cultural competency of care has grown in recent years, particularly in the public sector, structural indicators have been developed to assess the availability of translators and clinicians from diverse backgrounds. Indicators relevant to the financing of care include the proportion of patients or a population with health insurance, which has been associated with both access and quality. Among the advantages of structural measures is that information needed to construct them is often available from databases used for licensure, credentialing, administration, or reimbursement of care. Structural measures may have good face validity, which is to say they seem like sensible indicators of quality. A higher rate of child psychiatrists per capita in a geographic area may contribute to better access and quality of mental healthcare for children and adolescents. However, as the IOM definition of quality indicates, a structural measure truly represents quality of care only to the extent that it is associated with superior health outcomes. There are often few data available to prove or disprove the presumed association, and there are often intervening considerations. For instance, higher rates of child psychiatrists per capita indicate better access to mental health services for children only if other factors, such as insurance coverage, do not remain barriers. The measure presumes that child psychiatrists provide better care than other clinicians and that this care leads to improved outcomes in real-world settings. In the absence of empirical data supporting these assumptions, one may prefer to measure downstream processes or outcomes directly, such as the proportion of children with a mental health problem who see a child psychiatrist, or the proportion with a specific disorder who receive evidence-based care. Structural measures have largely given way to use of process and outcome measures in recent years.

Process Measures Processes of care encompass interactions between consumers and the healthcare system. These interactions begin with whether an illness is prevented or detected, whether an afflicted individual accesses care, and then whether they

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are adequately assessed and receive appropriate, safe treatment. After treatment is initiated, subsequent processes include continuity of care and the adequacy of coordination across clinicians, settings, and levels of care. Evaluation of the process of care is typically divided into two areas: its clinical content—frequently described as technical process—and the quality of the interaction between patients and healthcare personnel, known as interpersonal process. Interpersonal processes of care are typically evaluated from the patient’s perspective through surveys and interviews. Commonly evaluated components include the clarity and adequacy of clinician–patient communication, involvement of patients in clinical decision making, and interpersonal style in terms of respectfulness, supportiveness, and sensitivity to cultural differences (Stewart et al. 1999). Two commonly used instruments to assess interpersonal processes in mental healthcare are the Experience of Care and Health Outcomes (ECHO) Survey (Cubansky et al. 2002) and the Mental Health Statistics Improvement Program (MHSIP) Consumer Survey (Teague et al. 1997), which have been adopted, respectively, by commercial health plans and many state mental health authorities. The following illustrative question from the ECHO examines the quality of clinician communication: In the last 12 months, how often did the people you went to for counseling or treatment explain things in a way you could understand?

Technical processes of care are assessed by comparing clinical practices, as performed, with norms and standards of care. Process measures can range from relatively simple rate-based indicators to complex multi-item instruments. Single-item processes measures are described in greater detail in Chapter 2. The following example evaluates a component of clinical assessment during an initial examination: The proportion of patients diagnosed with major depression for whom suicidality was assessed and documented in the medical record.

Process measures that compare multiple components of a programmatic intervention with its empirically proven model are known as fidelity measures. A number of interventions—including assertive community treatment, supported employment, and integrated treatment for co-occurring psychiatric and substance use disorders—have been found to vary in effectiveness in a direct relationship with the fidelity of their implementation (Becker et al. 2001; McHugo et al. 1999). State mental health authorities are beginning to pilottest fidelity measures for these conditions as a basis for improving the implementation of evidence-based practices (Drake et al. 2001).

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One strength of process measures is that they can be selected to focus on important, frequent aspects of care. Because they focus on care delivery rather than downstream outcomes, they can be used to provide timely feedback to providers. They identify specific deficits in care that can then be addressed through improvement activities. Although the burden of process measurement varies, some measures require only preexisting, computerized sources of data, allowing for widespread, relatively low-cost implementation. Some process measures can readily be used to compare quality across providers, because they do not require case-mix adjustment to adjust results for differences in patient populations beyond a provider’s control. However, like measures of structure, the validity of process measures is often unproven. In some cases validity may be supported by research evidence that associates the underlying clinical process with positive clinical outcomes in controlled trials. Measure validity can also be directly tested by comparing outcomes of patients whose care conforms to the measure with those of patients whose care does not, such as in an evaluation of a measure of appropriate medication treatment for schizophrenia (Owen et al. 2000).

Outcome Measures Measurement of clinical outcomes potentially provides the most meaningful information about quality of mental health or substance-related care. Ultimately, the most important questions in assessing quality of care are whether symptoms remit, functioning and quality of life improve, adverse events are avoided, and consumers are satisfied. There are well-developed and rigorously tested instruments addressing each of these areas (American Psychiatric Association Task Force for the Handbook of Psychiatric Measures 2000; IsHak et al. 2002). Outcome measurement’s challenge lies less in its significance or measurability than in the feasibility of implementation and the utility of the results. Among the most common approaches to assessing clinical outcomes is to evaluate the severity of illness over time, typically before and after an acute event (e.g., a depressive episode) or unit of service use (e.g., an inpatient hospitalization). Dimensions of severity include the intensity of symptoms, functional impairment, or quality of life. These can be measured using scales specific to individual disorders or with instruments designed for heterogeneous populations. Instruments can be administered by clinicians or directly by patients. Choices among instruments are often accompanied by trade-offs between accuracy and burden of administration. For example, among instruments assessing symptoms, the Hamilton Rating Scale for Depression (Ham-D) consists of 24 items through which clinicians assess the severity of a single disorder, major depression (Hamilton 1967). In contrast, the Symptom

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Checklist–90—Revised (SCL-90-R) is a 90-item patient-administered questionnaire that addresses multiple categories of psychiatric symptoms including depression, anxiety, and psychosis (Derogatis 1994). Functional assessment examines patients’ ability to participate in designated roles (e.g., familial, occupational, and interpersonal). At one end of the spectrum is the Global Assessment of Functioning scale (GAF; American Psychiatric Association 2000). Advantages include its wide use as Axis V of the DSM-IV-TR multiaxial diagnostic system and its brevity. Clinicians rate symptoms as well as social and occupational functioning, on a single-item scale from 1 to 100. Although the GAF has good reliability in formal testing, there is a paucity of data on its reliability when used routinely. Its single-item scale also conflates symptoms and functioning, whereas their severity may differ. At the other extreme is the World Health Organization Disability Assessment Schedule (WHODAS II), which discriminates among six functional domains with sensitivity and reliability but at the higher burden of 36 clinician-assessed items (World Health Organization 2000). Many severity assessment instruments, such as the Ham-D and SCL-90-R, were developed for clinical research and later adapted to quality assessment. Others were designed specifically for routine evaluation of quality of care. For example, a series of disorder-specific outcome modules developed by Smith et al. (1997) at the University of Arkansas assess changes in clinical status over time for depression, alcohol dependence, panic disorder, and schizophrenia. The modules also collect information about patient characteristics for case-mix adjustment and are linked to a Web-based system for producing reports. Another approach is illustrated by the Behavior and Symptom Identification Scale (BASI S-32), developed by Eisen et al. (1986) at McLean Hospital for diagnostically mixed patient samples. This 32-item instrument produces composite scores in five domains: depression and anxiety, psychosis, impulsive and addictive behavior, relation to self/others, and daily living/ role functioning. Rates of adverse events provide additional data on clinical outcomes. They can be useful to quality assessment activities, particularly if they have a number of desirable characteristics. The event should be relatively common, important, identifiable from existing data sets, temporally proximal to healthcare provision, and result directly from inadequate or inappropriate care. Few adverse events meet all of these characteristics. Medication side effects are important, often immediate, and can result from poor treatment, but descriptive data are not routinely available. Suicide rates are critically important and available from mortality data (albeit with underreporting). Suicide is relatively rare, however, in the 6- to 12-month time periods typical in quality assessment. Over longer periods, patients may access care from many providers over many episodes of illness, limiting conclusions that can be drawn

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about the quality of care delivered by any one provider during any single episode of care. Other outcomes may be of particular interest to specific stakeholder groups. State mental health authorities, which fund services for individuals with severe mental illness, have sought to implement outcome measures that assess effectiveness in terms of increased employment, reduced criminal justice involvement, and (among adolescents) increased school attendance. Providers of substance abuse services have measured abstinence rates among individuals receiving treatment. A number of private sector employers, seeking methods to evaluate the healthcare purchased for employees, have adopted measures of employee well-being (such as the SF-36; Ware and Sherbourne 2001) and measures of work impairment associated with illness (as in the Workplace Limitations Questionnaire; Lerner et al. 2001). Demonstration of the value of QI interventions in terms of these outcomes may carry particular weight in the marketplace, where these stakeholders are influential decision makers. Additional strengths of outcome measures are closely tied to their limitations. Measuring outcomes is efficient in that it assesses the aggregate impact of all care (e.g., medication, therapy, patient education) rather than individual processes. Outcomes measurement can be less directive than process measurement. A clinic’s finding that remission rates from major depression among their patients are comparatively low opens up many avenues for possible improvements in care. It leaves the specific approach to improving care up to the clinic’s staff. In contrast, a process measure that identifies a specific deficit in care received by depressed patients (e.g., delayed access or subtherapeutic antidepressant dosages), tends to suggest a specific solution (i.e., reducing waiting times or educating providers about dosage levels). Clinicians may prefer the greater autonomy afforded by outcome measures. However, with so many factors influencing the course of mental illness, the determinants of poor outcomes may be difficult to identify without accompanying indicators of process. In addition, case-mix adjustment is essential for using outcomes to compare provider performance. However, available data on case-mix characteristics is often insufficient and statistical models for adjustment frequently lack explanatory power. Outcome instruments can be burdensome to administer, whether by clinicians or patients, although technology has markedly lowered costs of data entry and analysis. A final barrier to widespread use of outcome measures is lack of agreement on which instruments should be adopted. A number of stakeholder groups, including the American Psychiatric Association, the American College of Physicians, and the American Academy of Family Physicians, have begun discussing adoption of a standardized instrument to assess depression. One candidate is the nine-item depression module of the Patient Health Questionnaire, which

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can be used for screening, severity assessment, and examination of treatmentrelated outcomes (Kroenke et al. 2001).

❚ CONCLUSION Recent attention to quality of care has been driven by a combination of empirical data on quality deficits, organizational and economic changes in healthcare, and growing consensus among policy makers and other key stakeholders that improvement is needed. There is much work still to be done to identify and refine quality measures as well as to determine what type of measures are best used for which purposes. Complementarity among different approaches to measurement is increasingly recognized (Hermann 2002; Palmer 1997). Many state mental health systems assess both interpersonal and technical processes, recognizing that clinician–patient interaction is crucial to achieving technical quality and the best-possible outcomes. Evaluating processes and outcomes of care can provide the combined benefits of each method. Findings of substandard outcomes can help engage clinicians in improvement efforts, while findings of associated deficits in clinical processes can provide direction for improvement efforts. Although measures of structure have fallen out of favor, recent research has identified a number of structural features of care that have been demonstrated to influence patient outcomes (Meyer and Massagli 2001). Further research and experience with each of these approaches to measurement will allow for their more efficient and useful deployment.

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American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision. Washington DC, American Psychiatric Association, 2000 American Psychiatric Association: American Psychiatric Association Practice Guidelines for the Treatment of Psychiatric Disorders: Compendium 2002. Washington, DC, American Psychiatric Association, 2002 American Psychiatric Association Task Force for the Handbook of Psychiatric Measures: Handbook of Psychiatric Measures. Washington, DC, American Psychiatric Association, 2000 Andrews G, Henderson S (eds): Unmet Need in Psychiatry. New York, Cambridge University Press, 2000 Becker D, Smith J, Tanzman B, et al: Fidelity of supported employment programs and employment outcomes. Psychiatr Serv 52:834–836, 2001 Berwick D, Godfrey A, Roessner J: Curing Health Care. San Francisco, CA, JosseyBass, 1990 Broadhead W, Blazer D, George L, et al: Depression, disability days, and days lost from work in a prospective epidemiologic survey. JAMA 264:2524–2528, 1990 Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Caro R: The Power Broker: Robert Moses and the Fall of New York. New York, Random House, 1975 Charbonneau A, Rosen AK, Ash AS, et al: Measuring the quality of depression care in a large integrated health system. Med Care 41:669–680, 2003 Chassin M, Galvin R: The urgent need to improve health care quality: Institute of Medicine national roundtable on health care quality. JAMA 280:1000–1005, 1998 Chow JC, Jaffee K, Snowden L: Racial/ethnic disparities in the use of mental health services in poverty areas. Am J Public Health 93:792–797, 2003 Croghan T, Obenchain R, Crown W: What does treatment of depression really cost? Health Aff 17:198–208, 1998 Cubansky J, Shaul JA, Eisen SV, et al: Experience of Care and Health Outcomes (ECHO) Survey: A Survey to Elicit Consumer Ratings of Their Behavioral Health Treatment and Counseling. Washington, DC, National Committee for Quality Assurance, 2002 Derogatis LR: Symptom Checklist-90-Revised (SCL-90-R): Administration, Scoring, and Procedures Manual, 3rd Edition. Minneapolis, MN, National Computer Systems, 1994 Donabedian A: Explorations in Quality Assessment and Monitoring: The Definition of Quality and Approaches to Its Assessment. Ann Arbor, MI, Health Administration Press, 1980 Drake RE, Goldman HH, Leff HS, et al: Implementing evidence-based practices in routine mental health service settings. Psychiatr Serv 52:179–182, 2001 Eisen S, Grob M, Klein A: BASIS: the development of a self-report measure for psychiatric inpatient evaluation. Psychiatr Hosp 17:165–171, 1986 Etheridge RM, Craddock SG, Dunteman GH, et al: Treatment services in two national studies of community-based drug abuse treatment programs. J Subst Abuse 7:9–26, 1995 Felker B, Yazel J, Short D: Mortality and medical comorbidity among psychiatric patients: a review. Psychiatr Serv 47:1356–1363, 1996

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Fortney J, Booth B, Smith G: Variation among VA hospitals in length of stay for treatment of depression. Psychiatr Serv 47:608–613, 1996 Gabbard G (ed): Treatments of Psychiatric Disorders. Washington, DC, American Psychiatric Press, 1995 Gilbody S, Whitty P, Grimshaw J, et al: Educational and organizational interventions to improve the management of depression in primary care: a systematic review. JAMA 289:3145–3151, 2003 Hamilton M: Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol 6:278–296, 1967 Hermann R: Variation in psychiatric practices: implications for health care policy and financing. Harv Rev Psychiatry 4:98–101, 1996 Hermann RC: Linking outcome measurement with process measurement for quality improvement, in Outcome Measurement in Psychiatry: A Critical Review. Edited by IsHak W, Burt T, Sederer L. Washington, DC, American Psychiatric Publishing, 2002, pp 23–55 Hermann R, Dorwart R, Hoover C, et al: Variation in ECT use in the United States. Am J Psychiatry 152:869–875, 1995 Hermann RC, Ettner SL, Dorwart RA, et al: Diagnoses of patients treated with ECT: a comparison of evidence-based standards with reported use. Psychiatr Serv 50:1059–1065, 1999 Herz MI, Lamberti JS, Mintz J, et al: A program for relapse prevention in schizophrenia: a controlled study. Arch Gen Psychiatry 57:277–283, 2000 Institute of Medicine: Managing Managed Care: Quality Improvement in Behavioral Health. Washington DC, National Academy Press, 1997 Institute of Medicine: To Err Is Human: Building a Safer Health System. Washington, DC, National Academy Press, 1999 Institute of Medicine: Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC, National Academy Press, 2001a Institute of Medicine: Envisioning the National Health Care Quality Report. Washington, DC, National Academy Press, 2001b Institute of Medicine: Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC, National Academy Press, 2002 Institute of Medicine: Priority Areas for National Action: Transforming Health Care Quality. Washington, DC, National Academy Press, 2003 IsHak W, Burt T, Sederer L (eds): Outcome Measurement in Psychiatry: A Critical Review. Washington DC, American Psychiatric Publishing, 2002 Janicak P, Mask J, Trimakas K, et al: ECT: An assessment of mental health professionals’ knowledge and attitudes. J Clin Psychiatry 46:262–266, 1985 Johnson S, Prosser D, Bindman J, et al: Continuity of care for the severely mentally ill: concepts and measures. Soc Psychiatry Psychiatr Epidemiol 32:137–142, 1997 Joseph RC, Hermann RC: Screening for psychiatric disorders in primary care settings. Harv Rev Psychiatry 6:165–170, 1998 Kalayam B, Steinhart M: A survey of attitudes on the use of electroconvulsive therapy. Hosp Community Psychiatry 32:185–188, 1981 Katon W, Von Korff M, Lin E, et al: Stepped collaborative care for primary care patients with persistent symptoms of depression: a randomized trial. Arch Gen Psychiatry 56:1109–1115, 1999

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Kessler R, McGonagle K, Zhao S, et al: Lifetime and 12-month prevalence of DSMIII-R psychiatric disorders in the United States: results from the National Comorbidity Survey. Arch Gen Psychiatry 551:8–19, 1994 Kroenke K, Spitzer RL, Williams JB: The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 16:606–613, 2001 Lehman A: Quality of care in mental health: the case of schizophrenia. Health Aff 18:52–65, 1999 Lerner D, Amick B, Rogers WH, et al.: The work limitations questionnaire. Med Care 39:72–85, 2001. Lima B, Brooks M: Coordination of services for outpatients under concurrent medical and psychiatric care. Gen Hosp Psychiatry 7:330–333, 1985 Lohr KN (ed): Medicare: A Strategy for Quality Assurance. Washington, DC, National Academy Press, 1990 McGlynn EA: The State of Quality: How Good is Care? Written Testimony Prepared for the President’s Advisory Commission on Consumer Protection and Quality in the Health Care Industry. Santa Monica, CA, RAND, 1998 McGlynn EA, Asch SM, Adams J, et al: The quality of health care delivered to adults in the United States. N Engl J Med 348:2635–2645, 2003 McHugo G, Drake R, Teague G, et al: Fidelity to assertive community treatment and client outcomes in the New Hampshire dual disorders study. Psychiatr Serv 50:818–824, 1999 Meyer GS, Massagli MP: The forgotten component of the quality triad: can we still learn something from structure? Jt Comm J Qual Improv 27:484–493, 2001 Murray C, Lopez A(eds): Summary: The Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability From Diseases, Injuries, and Risk Factors in 1990 and Projected to 2020. Cambridge, MA, Harvard University Press, 1996 Najavits LM, Crits-Christoph P, Dierberger A: Clinicians’ impact on the quality of substance use disorder treatment. Subst Use Misuse 35:2161–2190, 2000 Narrow W, Rae D, Robins L, et al: Revised prevalence estimates of mental disorders in the United States. Arch Gen Psychiatry 59:115–123, 2002 National Advisory Mental Health Council Clinical Treatment and Services Research Workgroup: Bridging Science and Service (Recommendation 17). Bethesda, MD, National Institutes of Health, National Institute of Mental Health, 1998 National Institute on Alcohol Abuse and Alcoholism: Alcohol and Health: Eighth Special Report to the U.S. Congress From the Secretary of Health and Human Services. Rockville, MD, U.S. Department of Health and Human Services, National Institutes of Health, 1993 Needleman J, Buerhaus P, Mattke S, et al: Nurse staffing and quality of care in hospitals in the United States. N Engl J Med 346:1715–1722, 2002 New Freedom Commission on Mental Health: Achieving the Promise: Transforming Mental Health Care in America. Final Report. DHHS Pub. No. SMA-03-3832. Rockville, MD, New Freedom Commission on Mental Health, 2003 Office of the Surgeon General: Report of the Surgeon General’s Conference on Children’s Mental Health: A National Action Agenda. Washington, DC, U.S. Public Health Service, Office of the Surgeon General, 2001 Owen R, Thrush C, Kirchner J, et al: Performance measurement for schizophrenia: adherence to guidelines for antipsychotic dose. Int J Qual Health Care 12:475– 482, 2000

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Palmer R: Process-based measures of quality: the need for detailed clinical data in large health care databases. Ann Intern Med 127:733–738, 1997 Paul-Shaheen P, Clark J, Williams D: Small area analysis: a review and analysis of the North American literature. J Health Polit Policy Law 12:741–808, 1987 President’s Advisory Commission on Consumer Protection and Quality in the Health Care Industry: Quality First: Better Health Care for All Americans. Final Report of the President’s Advisory Commission on Consumer Protection and Quality in the Health Care Industry, 2003. Available at: http://www.hcqualitycommission.gov/final/chap04.html. Accessed June 13, 2005. RachBeisel J, Scott J, Dixon L: Co-occurring severe mental illness and substance use disorders: a review of recent research. Psychiatr Serv 50:1427–1434, 1999 Rice D, Kelman S, Miller L: The economic burden of mental illness. Hosp Community Psychiatry 43:1227–1232, 1992 Rosenheck R, Astrachan B: Regional variations in patterns of inpatient psychiatric care. Am J Psychiatry 151:1180–1183, 1990 Roy-Byrne PP, Katon W, Cowley DS, et al: A randomized effectiveness trial of collaborative care for patients with panic disorder in primary care. Arch Gen Psychiatry 58:869–876, 2001 Schneider E, Zaslavsky A, Epstein A: Racial disparities in the quality of care for enrollees in Medicare managed care. JAMA 287:1288–1294, 2002 Schuster M, McGlynn E, Brook R: How good is the quality of health care in the United States? Milbank Q 76:517–563, 1998 Smith GR, Rost KM, Fischer EP, et al: Assessing the effectiveness of mental healthcare in routine clinical practice: Characteristics, development, and uses of patient outcomes modules. Eval Health Prof 20:65–80, 1997 Stewart AL, Napoles-Springer A, Perez-Stable EJ: Interpersonal processes of care in diverse populations. Milbank Q 77:305–339, 1999 Sturm R, Ringel JS, Andreyeva T: Geographic disparities in children’s mental health care. Pediatrics 112:e308, 2003 Substance Abuse and Mental Health Services Adminstration (SAMHSA): National Expenditures for Mental Health, Alcohol and Other Drug Abuse Treatment, 1996. Rockville, MD, U.S. Department of Health and Human Services, 1998 Teague G, Ganju V, Hornik J: The MHSIP mental health report card: a consumeroriented approach to monitoring the quality of mental health plans. Eval Rev 21:330–341, 1997 Unutzer J, Simon G, Pabiniak C, et al: The use of administrative data to assess quality of care for bipolar disorder in a large staff model HMO. Gen Hosp Psychiatry 22:1–10, 2000 U.S. Department of Health and Human Services: Mental Health: A Report of the Surgeon General. Rockville, MD, U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, National Institutes of Health, National Institute of Mental Health, 1999 U.S. Public Health Service: Mental Health: Culture, Race, and Ethnicity. A Supplement to Mental Health: A Report of the Surgeon General. Rockville, MD, U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, National Institutes of Health, National Institute of Mental Health, 2001

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Veterans Health Administration Office of Quality and Performance: FY2002 VHA Performance Measurement System: Technical Manual. Washington, DC, Veterans Health Administration, 2002 Wadsworth HM, Stephens KS, Godfrey AB: Modern Methods for Quality Control and Improvement. New York, John Wiley and Sons, 1986 Wang P, Demler O, Kessler R: Adequacy of treatment for serious mental illness in the United States. Am J Publ Health 92:92–98, 2002 Ware JE Jr, Sherbourne CD: The MOS 36-item short-form health survey (SF-36). I. conceptual framework and item selection. Med Care 30:473–483, 1992 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993 Wells K, Schoenbaum M, Unutzer J, et al: Quality of care for primary care patients with depression in managed care. Arch Fam Med 8:529–536, 1999 Wennberg J, Barner B, Subkoff M: Professional uncertainty and supplier-induced demand. Soc Sci Med 16:811–824, 1982 World Health Organization: The World Health Organization Psychiatric Disability Schedule (WHODAS II). Geneva, World Health Organization, 2000

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C H A P T E R

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mong the many approaches to measuring quality in healthcare, singleitem measures of technical process are among the most widely used. Table 2–1 lists a selection of process measures developed for mental health and substance-related care. Technical process refers to the content of care—in contrast to interpersonal aspects of the delivery of care. These measures may assess clinical processes, such as the rate of inappropriate use of a therapeutic intervention, or administrative processes, such as the proportion of patients requesting outpatient services who are seen within a specified length of time. In either case, however, the measure compares care with an implicit or explicit standard to inform judgments about quality. Not included under this definition are measures that reflect utilization without quality-related significance, such as the length of hospital stays or the proportion of enrollees receiving mental health services. Hundreds of process measures have been developed to assess mental healthcare (Hermann et al. 2000, 2002b). Clinician organizations, government agencies, consumers, payers, and other stakeholders in the mental health system have implemented or proposed process measures for use in quality assessment and improvement. Measures have been developed for both

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TABLE 2–1. Process measures for quality assessment in mental health and substance-related care Measure developers or users

Measurement set

Clinician organizations American Medical Association

Clinical Performance Measures for Major Depressive Disorder

American Academy of Child and Adolescent Psychiatry (AACAP)

AACAP Performance Indicators

American Psychiatric Association Task Force on Quality Indicators

Quality Indicators Quality Indicators for Children

National Association of Social Workers (NASW)

NASW Clinical Indicators

Health systems and healthcare managers American College of Mental Health Administration

Indicators for Behavioral Health

Child and Adolescent Residential Psychiatric Programs (CHARPP)

CHARPP Improvement Measurement Program

National Association of State Mental Health Program Directors Research Institute

Behavioral Health Performance Measurement System

Accreditors Commission on Accreditation of Rehabilitation Facilities

Performance Measures for Rehabilitation Programs

Joint Commission on Accreditation of Healthcare Organizations

National Library of Healthcare Indicators

National Committee for Quality Assurance

Health Plan Employer Data and Information Set (HEDIS)

Managed behavioral healthcare organizations American Managed Behavioral Healthcare Association

Performance Measures for Managed Behavioral Healthcare

Comprehensive Behavioral Care

Quality Indicators

Massachusetts Behavioral Health Partnership (MBHP)

MBHP Behavioral Health Program Performance Measures

M-CARE

Quality Improvement Performance Measures

Merit Behavioral Health Care of Iowa

Iowa Mental Health Performance Indicators

ValueOptions/Value Behavioral Health

Corporate Quality Indicators

Government agencies Veterans Health Administration (VHA)

Mental Health Program Performance Monitoring System

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TABLE 2–1. Process measures for quality assessment in mental health and substance-related care (continued) Measure developers or users

Measurement set

VHA/Department of Defense (DOD)

VHA/DOD Performance Measures for Major Depressive Disorder

Iowa Department of Human Services

Iowa Performance Plan Indicators

Massachusetts Division of Medical Assistance

Performance Measures for Medicaid Recipients

Outcomes Roundtable for Children and Families (ORCF)

ORCF Measures for Behavioral Health Disorders

Tennessee Department of Mental Health and Mental Retardation

TennCare Partners Program Performance Measures

Texas Commission on Alcohol and Drug Abuse (TCADA)

TCADA Performance Measures

Consumers Mental Health Statistics Improvement Program (MHSIP)

Process measures derived from MHSIP Consumer Survey items

Employer purchasers Digital Inc.

Health Maintenance Organization Performance Measures

Foundation for Accountability (FACCT)

FACCT Quality Measures

Other Lehman and Steinwachs, Schizophrenia Bulletin, 1998

Schizophrenia Patient Outcomes Research Team (PORT) Measures

RAND Corporation

RAND Pediatric Quality Indicators

Washington Circle Group

Washington Circle Group Performance Measures

Wells et al., American Journal of Psychiatry, 1993

Measures of Inpatient Care for Elderly Patients With Depression

psychosocial and somatic interventions as well as for numerous disorders, settings, and subpopulations. This chapter addresses the following questions: • • • • •

Who uses process measures and for what purposes? What domains of clinical process can measures evaluate? What data sources are available for measurement? How are process measures constructed? What is the comparative basis for determination of quality?

A typical rate-based process measure is depicted in Figure 2–1. The concept underlying the measure is that assertive community treatment (ACT)

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Numerator

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Number of patients from the denominator who are enrolled in an intensive case management program such as PACT. x 100 = %

Denominator

Number of individuals ages 18–65 who have at least two inpatient stays or four emergency department crisis visits with a diagnosis of schizophrenia in the prior 12-month period.

FIGURE 2–1. Program for Assertive Community Treatment (PACT) utilization for individuals with schizophrenia. Source. Adapted from American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1999. Used with permission.

has been shown to be effective in reducing inpatient admissions and emergency department visits among individuals with schizophrenia. ACT is also associated with high levels of patient satisfaction and increases in the proportion of patients living independently. Because these programs are resource intensive, they are typically targeted to patients who can most benefit from the intervention, namely those with chronic, unstable illness characterized by frequent exacerbations of sufficient severity to require hospitalization. The measure’s denominator attempts to define the eligible population using data on the patient’s diagnosis, age, and prior intensive service utilization. The numerator includes those who have received the designated service.

❚ MEASURE USES AND USERS Uses of process measures can be grouped into three categories to inform 1) provider selection, 2) internal quality improvement (QI), 3) external QI, and 4) research QI. Provider selection refers to choices consumers and purchasers make among clinicians, facilities, or health plans. Internal QI consists of activities conducted by healthcare providers to assess and improve the care they deliver. Characteristically, members of the provider organizations select the foci of these activities. In contrast, external QI is initiated by organizations that finance, manage, purchase, or provide oversight of care rather than by providers themselves. One of the most common approaches to external QI em-

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ploys provider profiling, or comparing performance among providers on selected quality measures. The primary purpose of this activity is to encourage providers to improve in areas in which they perform poorly. Providing feedback to providers—in terms of ranks from highest to lowest or comparisons of individual results with overall means or percentiles—has been shown to stimulate improvement, although usually to a moderate degree. External organizations across the country are experimenting with a variety of inducements to further motivate improvement, including public dissemination of results, provider education, administrative mandates, contract stipulations, sanctions, and financial incentives. Research QI is another distinct type. These are experimental interventions, usually under controlled conditions, that test interventions aimed at improving quality of care. The methods, measures, and findings from research studies are invaluable sources for subsequent realworld QI initiatives. However, quality measures used in research may not be directly applicable to real-world activities. A greater range of data sources, as well as resources for collection and analysis, is typically available to researchers. Measures developed for research may need to be modified for use in internal and external QI. Roles of specific stakeholders in quality assessment and improvement are described in the following sections.

Consumers Consumers can benefit from information resulting from process measurement in several ways. Under some types of health insurance, consumers have a choice of clinicians, hospitals, or health plans. Traditionally, consumers’ selection of a clinician or hospital has been informed by word of mouth or the preferences of a referring physician. In choosing a health plan, consumers are provided information on reimbursable services, out-of-pocket costs, and flexibility in selecting providers. Only recently, however, has information on quality of care begun to be available to inform these decisions. For individuals with severe mental illness, family members are often also part of the decisionmaking process. Quality of care data are also used by groups representing consumers and families in advocating for better mental healthcare. For example, quality deficits revealed by the Schizophrenia Patient Outcomes Research Team (PORT) Study (Table 1–4) were widely publicized by the National Alliance for the Mentally Ill.

Employer Purchasers Employer purchasers of healthcare are beginning to use quality of care data in purchasing health benefits for their employees. An employer’s selection of health plans can be particularly important in businesses that do not provide

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employees with choices among plans. In the absence of information on quality, corporate benefit managers have traditionally based their decisions on benefit design and cost, providing plans with little incentive to improve care and great incentive to cut costs. With the emergence of information on quality, employers can purchase care on the basis of value and provide incentives for plans to balance quality considerations and cost containment.

Clinicians and Managers Clinicians and managers of practices, clinics, hospitals, and systems of care increasingly conduct internal measurement-based QI. These activities can be motivated by quality concerns initiated by clinicians or staff within these organizations or in response to requirements of accreditors, payers, and other oversight groups. Clinician organizations such as the American Psychiatric Association and the National Association of Social Workers have proposed measures for use in QI (American Psychiatric Association Task Force on Quality Indicators 2002; National Association of Social Workers Commission on Health and Mental Health 1990). Clinicians from various disciplines are usually represented in multi-stakeholder measure development initiatives.

Accreditors Accreditors of health plans and hospitals have played a leading role in QI by implementing standardized quality measures and mandating measurementbased QI in organizations seeking accreditation. The National Committee for Quality Assurance (NCQA) developed the widely used Health Plan Employer Data and Information Set (HEDIS) measures for use in health plan accreditation, including several specific to mental healthcare. The NCQA publishes comparative results on these measures for more than 300 plans. From the late 1990s through 2002, the Joint Commission on Accreditation of Healthcare Organizations’ (JCAHO; 2001, 2003) ORYX initiative required behavioral health facilities to implement quality-measurement systems from an approved list and use the results in QI activities. Dozens of measurement systems were certified for ORYX, assessing a wide variety of clinical processes and outcomes. The benefit of this approach was that hospitals were able to chose approaches to quality assessment that they found most useful. The drawback was that with each hospital measuring quality differently, results could not be compared across hospitals. More recently, JCAHO has stepped back from some ORYX requirements and initiated a process to develop Core Performance Measures for Hospital-Based Inpatient Psychiatric Services. The intent is to adopt standardized measures that allow for comparisons among hospitals.

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Private and Public Payers Private and public payers of mental healthcare seek accountability from providers by evaluating the quality of the care they finance. Under fee-for-service reimbursement, these payers have data available from reimbursement claims on patient characteristics, clinical conditions, and service utilization from which they can construct limited measures of quality. Medicare and Medicaid agencies have been particularly active in developing and implementing quality measures (R. C. Hermann, C. B. Bethell, D. Read, et al., “Measuring the Quality of Child and Adolescent Mental Health Services in State Medicaid Programs,” June 13, 2005). Commercial payers and plans have additionally used quality-measurement data in selecting clinicians and facilities for participation in their provider networks. A number of public and private payers have begun linking reimbursement levels to performance on quality measures to provide incentives for improvement (Rosenthal et al. 2004). Thus far, this has occurred primarily in primary care, but the practice is likely to be extended to mental healthcare as well.

Managed Behavioral Healthcare Organizations Managed behavioral healthcare organizations (MBHOs) contract with employers, payers, and health plans to manage the administration and costs of mental health and, in some cases, substance-related care. Many MBHOs use process measures to assess quality of care, profile provider performance, and provide feedback to encourage improvement. Like primary payers, MBHOs uses performance on quality measures in contracting with clinicians and hospitals on participation in their network.

Government Agencies Government agencies play a variety of roles in the mental health system in addition to payer. As one of the largest employers in the United States, the federal government is a major purchaser. It is also a direct provider of care via the Veterans Health Administration, which has conducted significant work on practice guidelines and quality measures for mental healthcare. The Substance Abuse and Mental Health Services Administration, a division of the U.S. Department of Health and Human Services, funds a number of measure development initiatives. State mental health authorities serve as payers, providers, and/or regulators. State agencies license hospitals and clinics and can require participation in measurement activities as a condition of licensure.

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Mental Health Services Researchers and Program Evaluators Mental health services researchers and program evaluators were early developers of quality measures, which have been used in studies identifying variations in clinical practices, gaps between evidence-based and actual care, and the influence of financial and organizational change on quality. Researchers continue to serve in clinical and methodological roles in multi-stakeholder measure development initiatives.

❚ DOMAINS OF CLINICAL PROCESS When considering quality of care, we often first think about the quality of interventions—their underuse, overuse, and misuse. However, treatment is only one domain of clinical process. Donabedian’s (1980) framework defines process broadly as encompassing “activities that go on within and between practitioners and patients” (p. 79). Based on this definition, technical processes of care have been categorized into seven domains—prevention, access, assessment, treatment, continuity, coordination, and safety (Hermann and Palmer 2002). Measures have been developed to assess mental health and substancerelated care in each of these areas (Hermann et al. 2000, 2002b). The paragraphs that follow describe each domain and provide illustrative measures.

Prevention Preventive approaches to mental illness include interventions aimed at preventing new cases (primary prevention), achieving early detection and treatment (secondary prevention), and providing effective treatment of existing cases (tertiary prevention). There are few measures of primary prevention in mental healthcare and not many interventions, although promising research is under way for individuals with prodromal symptoms of schizophrenia and for at-risk children of parents with depressive disorders. Interventions for secondary prevention are better established. A number of process measures have been developed to assess rates of screening and treatment of mental and substance use disorders within at-risk populations. The Veterans Health Administration requires its primary care clinics to screen all outpatients for depression on an annual basis and uses the following measure to evaluate clinic performance: The proportion of individuals receiving at least one primary care visit in a 12-month period whose medical record contains results from a standardized depression-screening instrument.

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Access Measures of access to mental healthcare have been used to evaluate the availability of services, the ease or difficulty of obtaining them, and commonly encountered barriers such as waiting lists, cultural issues, and lack of geographic proximity. Some of this information can be obtained from administrative data, but patient surveys can provide more detailed information. Many measurement systems include a version of the following measure, which evaluates the extent of delays in obtaining outpatient services: For individuals requesting services at community mental health centers, the mean duration (in days) between a request for services and the first face-toface visit.

Assessment Standard components of an initial assessment of a patient presenting with a psychiatric problem include current psychiatric status and functioning; past history of illness and treatment; a history of medical illness, substance use, and psychosocial functioning; and an examination of mental status. Research studies have documented frequent omissions in each of these areas in medical record documentation of initial evaluations of inpatients and outpatients. Missing elements of a comprehensive assessment can have direct implications for treatment. For example, the combination of an antidepressant and antipsychotic drug is clinically indicated for treatment of depression with psychotic features. However, research studies have found that depressed patients are frequently not assessed for psychosis, and psychosis is often not detected. The following measure has been used to evaluate this component of assessment: The proportion of inpatients hospitalized with major depression that has a documented assessment for psychosis on admission.

Treatment Measures of treatment have been developed for both somatic and psychosocial interventions across a range of mental and substance-related disorders. While some measures examine primarily whether an evidence-based treatment was selected, others examine the appropriateness of the intensity or duration of an intervention. Example, evidence basis: The proportion of individuals experiencing a mild to moderate major depressive episode who receive psychotherapy or an antidepressant medication.

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Example, intensity: The proportion of individuals receiving an antidepressant medication for major depression who receive a dosage within the guidelinerecommended range. Example, duration: The proportion of individuals initiating an antidepressant medication for a major depressive episode who continue the medication for a 12-week acute treatment phase.

Coordination Measures of coordination evaluate the adequacy of clinicians’ monitoring of patient status, exchange of information, and activities to ensure the provision of needed services and maintenance of continuity of care. Organizational structures common in mental healthcare, such as division of treatment between a therapist and psychopharmacologist, increases the need for communication among clinicians. Transfer of up-to-date written documentation is similarly essential, though sometimes overlooked, between inpatient and outpatient providers as well as between mental health and primary care clinicians. Case managers can provide much-needed coordination of care for individuals with severe mental illness among multiple providers and outreach when exacerbation of an individual’s illness disrupts usual care. The proportion of inpatients hospitalized for psychiatric treatment for which the medical record documents contact between the patient’s inpatient and outpatient mental health clinicians.

Continuity Continuity of care for mental health services has been defined as “a process involving the orderly, uninterrupted movement of patients among the diverse elements of the service delivery system” (Bachrach 1981, p. 1449). Areas of concern regarding continuity of care include turnover among clinicians, the regularity of care, and patients’ transitions across levels of care (e.g., initiating ambulatory care following hospital discharge) or between healthcare sectors (e.g., completion of a referral from primary care to a mental health specialist; Johnson et al. 1997). The proportion of inpatients hospitalized for major depression that have an ambulatory mental health visit within 7 days of discharge.

Safety Promoting patient safety in healthcare has taken on increased prominence in recent years, as research has shown unexpectedly high rates of medical errors

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and preventable adverse events (Institute of Medicine 1999). In mental healthcare, prominent safety concerns include medication errors, falls, suicides, patient and staff injuries, and appropriate use of seclusion and restraint. In healthcare systems, adverse events are examined through intensive review of individual adverse events and “near misses” as well as through monitoring aggregate numbers of events by type. Both approaches can lead to identification of opportunities to improve care; the measure below illustrates the latter approach. The proportion of inpatients hospitalized for a psychiatric disorder who are injured in the course of a restraint event.

❚ DATA SOURCES FOR MEASUREMENT The content of quality measures is limited by the availability and cost of the data needed to construct them. Data sources used for quality assessment are described in the following sections. Some are preexisting, collected in the course of delivering, financing, and documenting care, whereas others must be collected de novo for assessment purposes. In the current healthcare climate of increasing costs and constrained resources, organizations are cautious about adopting quality measures requiring primary data collection.

Administrative Data Administrative data are collected in computer databases in the course of enrolling for health insurance, providing care, and obtaining reimbursement. Insurance enrollment data includes sociodemographic information such as a patient’s age, gender, race, marital and family status, and residence. Utilization data record the number and duration of hospital stays, outpatient visits, and procedures—typically accompanied by patient diagnosis. Pharmacy data describe drugs prescribed, dates prescriptions were filled, medication strength, number of pills dispensed, and sometimes dosage. Standardized codes are used: ICD-9 or DSM-IV-TR for diagnosis, Current Procedural Terminology (CPT-IV) and Healthcare Common Procedure Codes (HCPC) for procedures, and the National Drug Codes (NDC) for drugs. Linking these databases can provide a composite of patient characteristics and care received. A drawback to administrative data is that they lack detailed clinical information, particularly on severity of illness, presenting symptoms, and considerations contributing to clinical decision making. Administrative data are generally considered to be the least costly source of information for process measurement; however, resources are needed for data cleaning, linking, and analysis.

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Medical Records Medical records typically contain more clinically detailed data than administrative databases. For example, a hospital discharge note provides not only an inpatient’s diagnosis and length of stay but also describes the clinical presentation, the care the patient received while hospitalized, and his or her clinical status on discharge. Medical record data are labor-intensive and thus relatively costly to collect. Some types of data may not be systematically recorded, may be missing, or may be recorded illegibly.

Laboratory Data Laboratory data provide information relevant to measures assessing the performance of appropriate tests and the quality of clinical decision making based on test results. Performance of tests may be obtainable from billing records. Test results can be obtained from medical records. Increasingly, laboratory data are available electronically. However, linking these files across data systems to utilization and enrollment files can be difficult.

Patient-Reported Data Patient-reported data can provide important information on both clinical care and patient status. Through surveys or interviews, patients can provide information on technical processes as well as insights into the influence of patient preferences on clinical decisions. Standardized patient self-administered assessment of illness severity also provides information useful for case-mix adjustment. Patient surveys and assessment instruments are relatively costly alternatives for quality measurement, requiring patient and staff time for data collection, computer entry, and analysis.

Clinician-Reported Data Clinician-reported data include structured clinician-administered assessments of patient status and functioning as well as reports of clinical care and decision making. Structured assessment by experienced clinicians represents a gold standard for several areas of psychiatric evaluation. However, as with other primary sources, clinician-reported data are relatively costly to collect. The accuracy of clinician-reported data can vary based on the comprehensiveness of clinicians’ evaluations and their use of structured approaches to assessment, such as standardized diagnostic criteria.

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Risk Management Records Risk management records can provide useful information for assessment of rates of seclusion, restraint, medication errors, falls, and other adverse events. The availability of this information in the medical record or in other locations varies on the basis of state regulations, documentation practices, liability concerns, and other considerations. Historically, this information has not been entered into computerized databases, but increasingly state agencies and other organizations are requiring systematic reporting of adverse events. State mental health authorities, for example, often collect data on seclusion and restraint.

Scheduling and Intake Data Scheduling and intake data can provide insights into access to care beyond information available from administrative databases. For example, administrative data will report that a patient attended an outpatient visit, but not whether a request for service resulted in a prolonged waiting time or if an appointment was scheduled but the patient did not show up. Although many outpatient clinics have records of scheduling data, they are often not computerized and require resources for data entry and linking to other data sources.

Utilization Management Data Utilization management data can also provide further insights into access of care, including initial requests for care, denials, and appeals. This information is often computerized and thus potentially available for quality assessment purposes. However, these data are often not available for quality assessment purposes and may not be linked to data sources.

❚ CONSTRUCTION OF PROCESS MEASURES Most process measures are rates, although they may also consist of counts, ratios, means, or medians. Results from rate-based measures are expressed as proportions or percentages, as illustrated in an illustrative measure in Figure 2–2. This measure assesses the proportion of patients initiating a new course of antidepressant treatment for major depression who complete a 12-week acute phase of treatment. Research studies have shown that an average of 12 weeks of continuous treatment with an antidepressant is needed for remission. A rate-based measure can be thought of as three successively smaller concentric circles (Figure 2–3). The outermost circle comprises the general pop-

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Numerator

Number of patients from the denominator who complete a 12-week course of the medication. x 100 = %

Denominator

FIGURE 2–2.

Number of patients initiating an antidepressant medication for major depression.

Acute-phase medication treatment of depression.

Source. Adapted from National Committee for Quality Assurance: Health Plan Employer Data and Information Set (HEDIS 2003). Washington, DC, National Committee for Quality Assurance, 2002. Used with permission.

General population Denominator population Numerator population

FIGURE 2–3.

Sampling for rate-based measures.

ulation. The denominator specifications define the boundary of the next smallest circle, describing the subpopulation eligible for evaluation by the measure. The innermost circle comprises the subset of the denominator population that meets criteria for measure conformance established by the numerator. For a measure to be implemented, detailed specifications are needed that describe inclusion and exclusion criteria for the denominator and numerator. Measure specifications define the sources of data, the eligible population, and the process under evaluation. Carefully designed, precise specifications help to ensure that the measure can be implemented accurately and reliably across facilities and systems of care.

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Selecting Among Data Sources Quality measures are often constructed from more than one data source. In the case of the antidepressant measure in Figure 2–2, outpatient visits and diagnosis come from administrative data derived from utilization claims. Information on the initiation and duration of antidepressants can be obtained for pharmacy claims if the patient is enrolled in a health plan that pays for medications. If pharmacy claims are unavailable, alternative sources of the information include medical records and patient report, each with implications for data accuracy and acquisition costs. For measures designed to be implemented across providers, it is essential that they rely on consistent specifications and data sources so that results reflect true differences in the care provided rather than measurement error.

Denominator Specifications The measure denominator defines the event or state determining a patient’s eligibility for the measure. The measure illustrated in Figure 2–2 indicates both a state (i.e., having a diagnosis of major depression) and an event (i.e., initiating an antidepressant medication). Measure specifications would describe these factors in further detail, including, for example, standard data codes for major depression from DSM-IV-TR or ICD-9 as well as codes for all eligible antidepressants from the NDC. Specifications may further include inclusion or exclusion criteria with regard to patient age, gender, and other characteristics. One may wish to apply the antidepressant measure to adults separately from children, because of a difference in factors influencing adherence. Criteria may also specify clinical setting, although this measure was designed to include patients initiated on an antidepressant at any level of care. The denominator also specifies the cohort of interest, for example, members of a health plan or patients of an individual clinician.

Numerator Specifications The numerator defines the subset of individuals from the denominator who are receiving the designated process of care—in the case of the illustrative measure, “completion of a 12-week course of medication.” Administrative data provide information about the date and quantity of filled prescriptions. Because gaps between prescription refills are common, this specification needs to address how long a gap (in number of days) is allowed before a patient is excluded from the numerator. An alternative numerator for this measure assesses the number of patients who received an antidepressant at an adequate dosage and duration. A benefit

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of this approach is that it provides a broader view of the quality of medication treatment. A drawback is that poor performance on the measure does not reveal which of the two processes needs further attention.

Information Proxies The “art” of constructing quality measures is in balancing the data available with the knowledge desired. Developing specifications for a measure often requires the use of approximations, or proxies, for elements of the process under evaluation. Measure developers and users of the resulting information should critically assess whether these proxies are adequate. One example is “filled prescriptions” as an indicator of the duration of antidepressant use, because it does not reveal whether a patient actually took the medication. Another challenge in developing this measure is operationalizing the concept of “initiating medication.” Measuring a 12-week acute phase of treatment is only relevant among individuals starting a new course of medication. However, depression can be a recurrent or chronic condition and many patients stop and restart medication at varying intervals. Administrative data may not distinguish between an acute phase of illness or a chronic course, or between intermittent continuation of a medication and initiation of a new course of treatment. A common approach to identifying a new treatment episode is to include a “wash-out period” in the denominator specifications, limiting the eligible population to individuals who have not received an antidepressant for a defined period, such as 3 months. Some process measures in their entirety can be best understood as a proxy for a broader concept. For example, hospital readmission rates are intended as a proxy for the quality of inpatient care, discharge planning, and/ or coordination between inpatient and outpatient providers of care. The measure is widely used due to the availability of hospital admission and discharge data in administrative data systems, but its significance is controversial. In general, research studies have failed to show significant relationships between readmission rates and other measures of quality in mental healthcare (Ashton et al. 1997; Lyons et al. 1997).

Determination of Quality As documentation accompanying the National Quality Measures Clearinghouse (NQMC) points out, process measures distinguish between good and poor quality of care in one of two ways (NQMC 2003). Patient-level measures compare the experience of each eligible patient with an intrinsic standard. For example, the antidepressant measure in Figure 2–2 categorizes each case as meeting or failing to meet a standard of continuous medication treat-

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ment for 12 weeks. In contrast, aggregate-level measures can be used to make inferences about quality, but only for a cohort of patients; they do not categorize individual cases as reflecting good or poor quality. For example, rates of physical restraint use are commonly used in the assessment of inpatient psychiatric care. Psychiatric hospitals with much higher restraint rates than similar institutions may raise concern, or at least prompt further inquiry. However, the institution’s restraint rate reveals nothing about the appropriateness of an individual use of restraints.

Deriving Measures From Guidelines Among measures that evaluate care through comparison with a standard of quality, a measure is only as valid as the standard upon which it is based. For this reason many have recommended that process measures be derived from clinical practice guidelines. Practice guidelines incorporate research evidence and clinical consensus into “systematically developed statements…about appropriate healthcare for specific clinical circumstances”(Field and Lohr 1992, p. 84). By focusing on the most important, evidence-based, clinical processes for psychiatric disorders of high prevalence (morbidity and treatability), guidelines provide an excellent foundation for quality measure development. QI initiatives are often aimed at closing gaps observed between actual and guideline-based practice. Palmer and Banks (1995) described a model for developing quality measures from practice guidelines (Table 2–2). Although initiatives to develop quality measures for mental healthcare may fall short of this ideal at one stage or another, most follow the general developmental process they describe.

❚ CONCLUSION This chapter describes a number of methodological issues in the construction of process measures. Other issues require further development; for instance, most clinical processes are not assessed consistently at different levels of the healthcare system. An ideal process measure would be scalable, or applicable to multiple system levels. Results on the performance of individual clinicians could be aggregated up to assess performance of the group practice or clinic in which they work. These results could be aggregated up to assess performance of care provided under a plan or geographic area. Users could also drill down into results to examine, for example, whether poor performance is attributable to a subset of providers with distinct characteristics. A related problem is that assessment of performance at the clinician level can be limited by an inadequate sample of patients within an individual clinicians’ practice

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TABLE 2–2. Model process for deriving quality measures from clinical practice guidelines 1. Identify measure purpose. 2. Form a multidisciplinary panel with representation of relevant stakeholders, clinical specialties, and methodological areas. 3. Identify relevant clinical practice guideline developed based on available scientific evidence and an explicit, rigorous methodology. 4. Identify patient population covered by the guideline recommendation. 5. Translate recommendation into review criterion. 6. Identify applicable clinicians or sites of care. 7. Define case sample and time window. 8. Identify data source(s). 9. Specify numerator and denominator. 10. Draft data collection procedures. 11. Assess need for case-mix adjustment. 12. Devise analytic procedures. 13. Pilot-test and revise draft specifications and procedures. 14. Assess measure properties such as reliability and validity. 15. Implement measure for quality assessment. Source. Adapted from Palmer R, Banks N: Using Clinical Practice Guidelines to Evaluate Quality of Care, Volume 2: Methods. Washington, DC, U.S. Department of Health and Human Services, Agency for Health Care Policy and Research, 1995, pp. 42–71. Used with permission.

that meet inclusion criteria for a measure (Hofer et al. 1999; Katon et al. 2000). Another problem with process measures relates to their narrow focus on specific processes of care. In selecting providers or plans, consumers and purchasers may find it difficult to absorb and integrate results from many different measures. The development of summary scores for recognizable dimensions of care may address their needs for meaningful, relevant results. McGlynn et al. (2003) developed such a quality index for technical process measures of general healthcare, with domain scores for acute, chronic, and preventive care. In mental health and substance-related care, such an index could yield summary scores for prevention, access, assessment, treatment, continuity, coordination, and safety. Aggregate scores derived from a body of measures may also be a partial solution to small samples when measuring performance of individual clinicians, because domain scores would be derived from measures addressing a range of processes and populations, broadening the base of patients that can be included in the sample.

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❚ REFERENCES American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision. Washington DC, American Psychiatric Association, 2000 American Psychiatric Association Task Force on Quality Indicators: Quality Indicators: Defining and Measuring Quality in Psychiatric Care for Adults and Children. Washington, DC, American Psychiatric Association, 2002 Ashton CM, Del Junco DJ, Souchek J, et al: The association between the quality of inpatient care and early readmission. Med Care 35:1044–1059, 1997 Bachrach L: Continuity of care for chronic mental patients: a conceptual analysis. Am J Psychiatry 138:1449–1456, 1981 Donabedian A: Explorations in Quality Assessment and Monitoring: The Definition of Quality and Approaches to Its Assessment. Ann Arbor, MI, Health Administration Press, 1980 Field MJ, Lohr KN (eds): Guidelines for Clinical Practice: From Development to Use. Washington, DC, National Academy Press, 1992 Hermann RC, Palmer RH: Common ground: a framework for selecting core quality measures. Psychiatr Serv 53:281–287, 2002 Hermann RC, Leff HS, Palmer RH, et al: Quality measures for mental health care: results from a national inventory. Med Care Res Rev 57 (suppl 2):135–154, 2000 Hermann RC, Finnerty M, Provost S, et al: Process measures for the assessment and improvement of quality of care for schizophrenia. Schizophr Bull 28:95–104, 2002b Hofer TP, Hayward RA, Greenfield S, et al: The unreliability of individual physician report cards for assessing the costs and quality of care of a chronic disease. JAMA 281:2098–2105, 1999 Institute of Medicine: To Err Is Human: Building a Safer Health System. Washington, DC, National Academy Press, 1999 Johnson S, Prosser D, Bindman J, et al: Continuity of care for the severely mentally ill: concepts and measures. Soc Psychiatry Psychiatr Epidemiol 32:137–142, 1997 Joint Commission on Accreditation of Healthcare Organizations: ORYX: The Next Evolution in Accreditation. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Joint Commission on Accreditation of Healthcare Organizations: Facts About ORYX for Hospitals. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2003 Katon W, Rutter C, Lin E, et al: Are there detectable differences in quality of care or outcome of depression across primary care providers? Med Care 38:552–561, 2000 Lehman AF, Steinwachs DM: Patterns of usual care for schizophrenia: initial results from the schizophrenia patient outcomes research team (PORT) client survey. Schizophr Bull 24(1):11–20, 1998 Lyons J, O’Mahoney M, Miller S, et al: Predicting readmission to the psychiatric hospital in a managed care environment: implications for quality indicators. Am J Psychiatry 154:337–340, 1997 McGlynn EA, Asch SM, Adams J, et al: The quality of health care delivered to adults in the United States. N Engl J Med 348:2635–2645, 2003

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National Association of Social Workers Commission on Health and Mental Health: NASW Clinical Indicators for Social Work and Psychosocial Services in the Acute Psychiatric Hospital. Washington DC, National Association of Social Workers, 1990 National Quality Measures Clearinghouse (NQMC): NQMC Template of Measure Attributes. Rockville, MD, National Quality Measures Clearinghouse, 2003 Palmer R, Banks N: Using Clinical Practice Guidelines to Evaluate Quality of Care. Volume 2: Methods. Rockville, MD, U.S. Department of Health and Human Services, Agency for Health Care Policy and Research, 1995, pp 31–71 Rosenthal MB, Fernandopulle R, Song HR, et al: Paying for quality: providers’ incentives for quality improvement. Health Aff (Millwood) 23(2):127–141, 2004 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993

C H A P T E R

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rocess measurement in mental health has proceeded through a phase of “letting a thousand flowers bloom,” which has resulted in hundreds of measures. They vary widely in their attributes and address a multitude of processes across the mental health system. Out of this unruly garden, organizations typically need to pick a small number of measures to populate a report card or assess a specific aim for improvement. The following vignettes highlight the role of measure selection in comparing providers, motivating quality improvement (QI) externally, and facilitating QI internally. When reviewing these real-world applications of quality measures, consider the following questions from the perspective of those choosing which measures to use. • • •

What is the role of quality measures in the activity described? What are the consequences of selecting one set of measures versus another? What considerations should be incorporated into measure selection? Selecting Providers

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Hired by a state Medicaid agency to manage mental healthcare for state residents with severe mental illness, a managed behavioral healthcare organization (MBHO) contracted with 30 hospitals to provide inpatient care. When requesting applications from hospitals that wished to participate in the network, the MBHO required the hospitals to submit results on several quality measures, using administrative data from the prior year. Hospital quality of care, the Request for Applications stated, will “comprise 20% of the selection process.”

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IMPROVING MENTAL HEALTHCARE Under newly instituted requirements by the Joint Commission on Accreditation of Healthcare Organizations (JCAHO), hospitals seeking accreditation must use quality-measure results in the recredentialing of staff clinicians. A hospital asked each of its departments, including psychiatry, to select three measures and submit clinician-specific results for each clinician proposed for recredentialing. A large corporation provided its employees with a choice of three plans for health insurance coverage. In addition to the usual information on each plan’s benefits, co-payments, and employee financial contribution, this year’s employee handbook included ratings, using a scale of zero to five stars, that assessed the plan’s performance in several areas of care. The ratings included data on mental healthcare drawn from the Health Plan Employer Data and Information Set (HEDIS) evaluation of health plans.

Motivating Quality Improvement Externally

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Faced with news reports of injuries and overuse of physical restraints, a state mental health authority (SMHA) launched an initiative to encourage reduction in restraint use by child and adolescent inpatient psychiatric services. One component of the program was to provide feedback to each inpatient service on its restraint use relative to other inpatient services in the state. Extra staff training, education, and if needed, resources for staffing were provided to facilities in the top 25th percentile in restraint use per inpatient. A large commercial health insurer implemented a plan to provide financial incentives for superior performance on quality measures. The insurer placed clinician group practices into one of three payment tiers based on their cumulative performance on a report card of measures. Clinician groups were reimbursed for the clinical services assessed by the measures at a 5% differential between each tier, with best-performing clinician groups receiving the highest reimbursement rate and poorest-performing clinician groups receiving the lowest rate. Participation in the quality assessment program was described as voluntary; however, clinicians electing not to participate received the lower reimbursement rate for their services.

Facilitating Quality Improvement Internally

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A busy public clinic was the primary mental healthcare provider for an urban community with high rates of mental illness and substance abuse. After funding cutbacks constrained the clinic’s ability to replace several departing clinicians, the clinic’s waiting list of individuals requesting services ballooned. As a result, the clinic’s leadership designated access as the primary improvement priority for the coming year. They convened a workgroup to conduct a QI initiative and assigned the group a primary measure to guide their work: the average waiting time between a consumer’s initial request for outpatient services and his or her first visit. The

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goal, said the clinic director, would be to reduce delays by redesigning processes for patient intake and clinician assignment to make better use of existing staff.

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After participating in a comparative quality measurement initiative, a health plan convened a task force to review their results relative to other plans and decide which, if any, results warranted remediation efforts. Members of the task force noted that only 40% of the plan’s enrollees who began an antidepressant drug for depression completed a 12-week course. A clinician on the task force, noting that these patients had been sufficiently depressed that they started an antidepressant, expressed concern about the low rate of adherence. A participating financial manager noted that antidepressants were among the most costly expenditures for the plan and questioned the waste involved in premature terminations. Another member noted that several plans treating similar populations had substantially better results.

As these applications illustrate, quality measurement is moving from the periphery toward the mainstream of healthcare activities. Increasingly, stakeholders are positioning quality measures to influence where patients will be treated, who will be permitted to treat them, how much will be paid for their care, and which conditions, populations, and processes will receive attention. As efforts ensue to tighten linkages between measure results and tangible consequences, the choice of what processes are measured becomes more important. A health plan’s selection of an aim for internal measurement-based improvement implies a commitment of sustained attention and resources for weeks to months. The opportunity costs of these decisions are substantial. Choosing to improve care for depression consumes resources—for measurement, analysis, reporting, meetings, education, materials for intervention—that could have been applied to other conditions. Alternatively, these resources could have been applied directly to expanding provision of existing services rather than attempting to improve them. A major payer or accreditor’s selection of a specific measure for comparative use can have even greater impact, because their decision may influence the QI priorities (and thus resource allocation) of hundreds of health plans. Consequences of measure selection will increase as quality assessment becomes more integral to more aspects of healthcare and incentives are implemented to strengthen their impact. Accordingly, measure selection processes need to be thoughtful and grounded in analysis of the needs of patients, priorities of the mental health system, and providers’ ability to implement change. The section that follows describes a framework for selecting quality measures. Although the examples provided emphasize the selection of measures for external QI activities, such as report cards, these considerations also

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apply to selection of measures for internal QI, a topic that is addressed in detail in Chapter 5.

❚ FRAMEWORK FOR MEASURE SELECTION Many stakeholder organizations have developed criteria describing desirable attributes of quality measures, emphasizing the need for measures to be meaningful, feasible, affordable, and amenable to improvement (Institute of Medicine 2001). Although useful, these criteria tend to focus on ideal properties of measures. In practice, available measures of mental health and substance-related care vary in terms of these properties. Moreover, some of these desirable attributes conflict with others (Hermann and Palmer 2002; Hermann et al. 2000). Developers of report cards typically seek to include measures that broadly represent the breadth and diversity of the mental health system, for example, in terms of domains of process, disorders, populations, modalities, and settings. This intends to ensure some aspects of care are not unduly emphasized over others. However, seeking breadth in the content of measures may be in conflict with the goal of selecting measures with the best measurement properties. Adding further complexity to measure selection, report card initiatives often bring together diverse stakeholders to identify consensus-based measures that meet common needs. Achieving consensus can be more difficult than expected, because although stakeholders share the broad goal of improving quality, they have diverse and at times competing priorities. In recognition of these complexities, the Center for Quality Assessment and Improvement in Mental Health (CQAIMH) developed a framework for measure selection (Figure 3–1) that makes explicit potential conflicts among desirable measure attributes, characteristics of existing measures, and competing priorities of stakeholders (Hermann and Palmer 2002). The sections below follow the contents of the framework. First, we describe desirable attributes of quality measures (the upper portion of Figure 3–1) along with the challenges to attaining these qualities. We provide data from the National Inventory of Mental Health Quality Measures on the prevalence of these attributes among quality measures for mental healthcare (Hermann 2004). Second, we describe dimensions of the mental healthcare system (the lower portion of Figure 3–1) and provide data from the National Inventory on the extent to which existing quality measures address these priority areas. Third, we describe inherent conflicts between choosing measures with desirable attributes and choosing measures that are broadly representative of the mental healthcare system. Although these conflicts pose challenges to multi-stakeholder initiatives in assessing quality of care, they also suggest trade-offs that can lead to consensus on quality measures for common use.

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Maximize measure attributes

Selecting Process Measures

Meaningfulness • • • • •

Feasibility

Clinically important Addresses stakeholder needs Evidence based Valid Problem area

• • • • •

Data available Affordable Accurate Confidential Reliable

Actionability • • • •

Comprehensible Comparable Interpretable Controllable

Domains of process (Prevention, detection, access, assessment, treatment, continuity, coordination, safety)

Clinical conditions (Primary and secondary mental disorders, comorbid substance use disorders, and medical disorders)

Vulnerable populations (Children, elderly, racial/ethnic minorities, rural populations)

Modalities (Medication, other somatic interventions, therapy, other psychosocial interventions)

Clinical settings (Inpatient, intermediate, and outpatient; primary and specialty care; nursing homes; prisons)

Level of healthcare system (Population, payer or managed behavioral health organization, delivery system, facility, provider, patient)

Measurement purpose (Internal QI, external QI, consumer selection, purchasing, research)

Represent mental health system broadly

FIGURE 3–1. sures.

CQAIMH framework for selecting quality mea-

Source. Adapted from Hermann RC, Palmer RH: “Common Ground: A Framework for Selecting Core Quality Measures for Mental Health and Substance Abuse Care.” Psychiatric Services 53:281–287, 2002. Used with permission.

Meaningfulness Clinically Important When weighing the importance of a process proposed for measurement, a central consideration is potential for the process to influence a clinically important outcome, such as improvement in symptoms, functioning, or quality of life. Other factors also influence the process’s potential impact: Among dis-

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order-specific measures, how prevalent is the disorder? What level of morbidity or disability does it cause? If the process is a clinical intervention, how effective is it? If the process facilitates treatment, as in a measure of access to care, is there evidence supporting the effectiveness of that care? Addresses Stakeholder Needs A measure proposed to assess quality of care should address a process of high importance to at least one stakeholder group. Few processes will be of equal importance to consumers, clinicians, consumers, payers, and other stakeholders. When evaluating an existing measure, it can be useful to note not only the stakeholder perspective of the organization developing the measure but also that of participating individuals. Among the more than 300 measures in the National Inventory, more than half were developed with participation from clinicians, managers, and researchers, while a third or more had input from accreditors, payers, and consumers. Fewer measures were developed with input from managed care organizations or employers. Evidence Based A process measure is said to be evidence based when research studies link the underlying process to a positive change in patient outcome. Research evidence from clinical trials exists along a spectrum. Randomized controlled trials constitute the strongest evidence, studies with retrospective and other nonrandomized designs provide middling support, and uncontrolled studies and case reports are weakest. Among mental health measures, slightly more than 25% are evidence based, with one-quarter of the subset based on randomized controlled trials and three-quarters based on less rigorous studies (Hermann et al. 2002b). Valid A measure’s validity is the degree to which its results reflect the true quality of the process measured. Research data can inform appraisal of both the evidence basis and the validity of a process measure; however, the former evaluates the underlying process, whereas the latter examines the properties of the measure. A measure that is evidence based may not be valid, for example, when the measure specifications provide an inadequate proxy for the clinical process. Two types of validity have been considered in evaluating measures of technical processes. Face validity reflects whether the measure appears to assess what it claims. Initiatives employing panels of experts often rely on face validity in selecting measures. Predictive validity examines whether patients whose care conforms to a measure’s specifications experience better out-

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comes than patients whose care is outside the measure’s parameters. Fewer than 10% of measures in the National Inventory have been assessed for predictive validity. Problem Area Measures selected for quality assessment should evaluate known or suspected problems in quality of care. Resources for quality assessment and improvement are too scarce to be expended on serial measurement of stable, high-performing processes. As described in Chapter 1, a substantial amount of data have accumulated in mental healthcare that identifies clinical practices exhibiting high variation and/or deviating from evidence-based guidelines. Further insights into potential problems are readily available from consumers and other participants in the delivery or receipt of care.

Feasibility Data Available Measurement is dependent on available data sources. These sources need to be accessible to the organization reporting on the measure. Hospitals, for example, are often not able to report accurately on readmission rates among discharged patients because some patients may be readmitted to other hospitals. On the other hand, payers may have utilization data for patients that include all of their inpatient admissions, allowing them to calculate readmission rates accurately. Some measures require data from multiple sources: sociodemographic information recorded during enrollment in an insurance plan, the frequency of outpatient visits from utilization claims, and medication dosing from pharmacy claims. For such a measure to be feasible, all three sources need to have a common patient-level identifier to permit the information to be linked. Affordable The cost of implementing measures varies by the burden imposed by collecting the necessary data. Preexisting administrative data are typically the least costly to collect, although these databases still need to be accessed, cleaned, linked, and manipulated by skilled programmers. Data from medical records are more costly to collect, as are structured evaluations administered by clinicians and patient self-administered assessments. Other sources of data, such as laboratory results, occurrence reports, and utilization review information may or may not be computerized and can present difficulties in linking information. Nearly all of the measures in the National Inventory require administrative data. A majority require further information, from medical records

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(48%), occurrence reports (19%), patient-administered instruments (13%), pharmacy data (12%), patient contact/appointment logs (7%), and other sources (12%) such as laboratory data, clinician-administered instruments, program enrollment data, utilization management databases, and proprietary data systems. Accurate The accuracy of administrative data from reimbursement claims is limited (Iezzoni 1997). An analysis of Medicaid claims from six states found that 25% of individuals with a claim for schizophrenia in 1994 had at least one claim the following year for a nosologically incompatible condition, such as bipolar disorder, psychotic disorder not otherwise specified, or schizoaffective disorder (Hermann 2003a). Model developers have developed a variety of strategies to deal with inconsistencies among claims-based diagnoses, for example, using algorithms to assign patients to the diagnosis that appears most frequently. Other studies have examined the accuracy of claims-based diagnoses compared with a variety of gold standards. Lurie et al. (1992) compared diagnoses from administrative claims for schizophrenia with medical record– based assessments by psychiatrists, finding them to have good specificity but lesser sensitivity. Geiger-Brown et al. (personal communication, June 2, 2005) compared diagnoses from Medicaid claims with those from patients’ reports and structured clinical interviews, finding agreement rates to be good for schizophrenia, fair for bipolar disorder, and fair to poor for other mental disorders. Other sources of data have their limitations as well. Patient surveys are susceptible to response and recall bias. A recent study found that subjects asked about prior healthcare utilization were less likely to report hospitalizations for mental healthcare than for nonpsychiatric conditions (Marshall et al. 2003). Research on the accuracy of medical records is mixed, with some studies suggesting they are adequate to assess appropriateness of clinical decision making (Kosecoff et al. 1987) and others reporting under-documentation of salient features of psychiatric disorders and treatment response (Cradock et al. 2001). Confidential Assessment of quality of care needs to be conducted in accordance with procedures that protect the confidentiality of patient health information. Reporting quality measure results usually occurs in an aggregate format that does not identify individual patients. However, patient identity can be transiently exposed when the information is abstracted from medical records or when personal identification numbers are used to link individuals across disparate databases. Federal rules protecting the confidentiality of patient-level informa-

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tion, including those stemming from the Health Insurance Portability and Accountability Act, spell out conditions for accessing data for quality assessment activities (Gostin 2001). Some state laws are more restrictive regarding use of data related to mental health and substance-related care. Reliable Reliability refers to the consistency and reproducibility of measure results over time, across different sites, and among individuals applying the measure. Ideally, measure selection is based on data from formal reliability testing. In practice, data on reliability are available for fewer than 10% of measures in the National Inventory. Reliability can be enhanced through the use of abstraction forms and guidelines for data collection and detailed programming specifications for analysis. The precision of specifications for a measure contributes to its reliability by increasing the likelihood that the data will be collected, assembled, and interpreted the same way by each user. Some measures may be conceptually sound but lack specifications sufficient for reliable use. One such measure that has been proposed is “the proportion of inpatients who receive a psychosocial assessment upon admission.” Missing are specifications defining what constitutes an adequate psychosocial assessment. Is any information on development, family, relationships, education, work, or living situation sufficient for credit on the measure? How many of these topics must be addressed and at what level of detail? Approximately 60% of measures in the National Inventory have been fully specified and operationalized for use, while the remainder require further development prior to implementation.

Actionability Comprehensible Measure results need to be comprehensible to their intended audience. Stakeholders vary in their experience with quantitative data. To interpret measure results, one has to understand the clinical intent of a measure as well as the degree to which the measure’s specifications fulfill that intent. In addition, one needs to know what level of quality the measure seeks to establish. Some measures evaluate practice against a high standard of care. An example is “the percentage of individuals treated for a first episode of depression that responded to an antidepressant who remain on the medication for at least 1 year.” Others represent a much more minimal standard, such as “the proportion of emergency-department or hospital patients discharged with a diagnosis of borderline personality disorder who have at least one mental health visit in the subsequent 90 days.” Without clarification, this measure may be

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misperceived as representing an acceptable standard of care. Although inadequate for clinical purposes, the measure usefully identifies a cohort of patients who lack minimally adequate follow-up care. Comparable Comparisons of provider performance on quality measures can be influenced by differences in the composition or “case mix” of providers’ patient populations. To permit fair comparisons, quality measure results may need to be adjusted for patient characteristics that influence measure results but are beyond the provider’s control (Hermann 2003a). Approaches to case-mix adjustment are described in Chapter 4. Methods for case-mix adjustment have been proposed for 18% of measures in the National Inventory, 7% based on stratification and 11% on multivariate models. Interpretable Another factor affecting a measure’s usefulness is the interpretability of its results. Sixty percent conformance to an evidence-based guideline recommendation may represent good or poor quality of care depending on the extent to which better results are achievable. A variety of numerical thresholds can be useful in interpreting results, including administratively established standards, averages derived from previous results, norms, and benchmarks that represent excellent performance. These are further described in Chapter 4. Standards have been proposed for nearly 25% of National Inventory measures, whereas prior results are available for approximately 40%. Norms and benchmarks have been established for few measures. Controllable One of the most important considerations in selecting a measure for QI is whether the process is under the user’s control. Without control over the underlying process, the user is unlikely to improve performance on the measure. For instance, the nursing staff of a psychiatric hospital was asked to identify a problem area that they would measure and work collectively to improve. They identified a problem that was both serious and measurable: a number of medication-labeling errors by the hospital pharmacy had resulted in mistaken administrations of medication to patients. They proposed a measurement-based QI project that aimed to decrease the number of labeling errors. Although their objective was a good one, the nurses were unlikely to achieve it. They could provide feedback to the pharmacy director, but the nurses themselves lacked the authority to change the pharmacy’s labeling process. On reflection, the nurses modified their measure from the rate of labeling er-

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rors to the proportion of labeling errors they detected before the patient received the medication, a process that was under their control and would achieve their objective of improving the safety of care.

❚ DIMENSIONS OF MENTAL HEALTH SYSTEM Process measures in mental healthcare are not equally available or equally rigorous for each dimension of the mental healthcare system. The distribution of measures in the National Inventory ranges from more than 100 measures that assess treatment to fewer than a dozen that assess preventive practice. Measures are similarly skewed to a relatively narrow range of conditions, settings, modalities, and vulnerable populations, limiting current applications and highlighting areas in which further development is needed.

Clinical Conditions Of the 308 measures in the National Inventory, approximately half are specific to individual psychiatric disorders while the other half are applicable across diagnostic categories. Measures of treatment interventions tend to be diagnosis-specific, while measures of access, continuity, and safety are for the most part applicable across disorders. Disorder-specific measures principally address three diagnostic categories: depressive disorders (31%), schizophrenia and other psychotic disorders (28%), and substance-related disorders (24%). Disorders that have substantial prevalence but lack significant numbers of measures include anxiety, cognitive, personality, and eating disorders as well as disorders first diagnosed in childhood. Although less prevalent, other conditions nonetheless warrant further consideration based on their functional impact—bipolar and obsessive-compulsive disorder, for instance, both rank among the 10 leading causes of disability worldwide. Few existing measures examine care for common comorbidities of psychiatric conditions, including mental, medical, and substance-related comorbidities.

Vulnerable Populations Policy makers are placing increased attention on assessing and improving care for vulnerable groups. Although 14% of existing measures evaluate care for children, only 7% address care for the elderly and fewer than 1% evaluate disparities in care based on race or ethnicity. One of the few measures explicitly developed to examine disparities in mental healthcare examines the proportion of individuals who attend a second appointment after an initial psychiatric evaluation, stratified by racial/ethnic groups. It is based on re-

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search findings that members of minority groups were significantly less likely to have a follow-up visit. Although the finding does not shed light on reasons for the disparity—such as differences in financial resources, patient preferences, provider behavior, or quality of care—it provides a compelling starting point for further investigation. Disparities have been observed in receipt of evidence-based mental health treatments (Office of the Surgeon General 2001), and further measure development is needed in this area. Since the completion of the National Inventory, published research has suggested future directions for quality assessment and improvement for vulnerable populations. Zima et al. (2005) has developed and applied measures of the quality of child mental health services, documenting varying rates of guideline conformance for assessment, service linkages, parental involvement, psychosocial treatment and safety. The Improving Mood-Promoting Access to Collaborative Treatment (IMPACT) study developed measures to assess the quality of primary care for late-life depression among elderly patients, and demonstrated the ability of a multi-modal intervention to improve quality and outcomes of care (Unutzer et al. 2002). Illustrative of renewed energy in the development of structural measures of quality, Chinman et al. (2003) developed an instrument to assess provider competencies in treating individuals with severe mental illness. The instrument assesses provider attitudes, knowledge and skills necessary for the delivery of high-quality care. Each of these advances has potential applications beyond research in realworld QI activities

Modalities Of approximately 130 measures in the National Inventory that assess specific clinical interventions, approximately 70% examine biological interventions and 30% psychosocial interventions. In addition, perhaps due to the abundance of published clinical drug trials, biological measures tend to assess components of care with greater specificity—addressing such topics as treatment adequacy, intensity, and duration—whereas measures of psychosocial interventions tend to assess only whether or not a clinically indicated treatment was received.

Clinical Settings As clinical care shifts from a focus on inpatient care—where quality assurance efforts originated—to ambulatory, intermediate, and community levels of care, quality measures are needed for a wider range of settings and levels of care. Existing measures were applicable to outpatient (56%), inpatient (49%), residential (14%), and community (9%) settings. Fewer measures were appli-

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cable to emergency or long-term care settings, to the general medical sector, or to nontraditional clinical settings with high rates of mental illness such as homeless shelters, prisons, and nursing homes.

Level of Healthcare System Quality of care can be assessed for an individual patient, at the level of the practice or facility where care is delivered, for enrollees of a health plan, or for an entire population. Some measures are specific to a single level; for instance, a measure examining the impact of utilization management denials on access evaluates a process specific to a health plan or managed behavioral healthcare organization (MBHO). Other measures can be applied to multiple levels, first to the caseloads of individual providers and then aggregated up to the level of the group, facility, or plan.

❚ TRADE-OFFS IN MEASURE SELECTION Inherent tensions among measure attributes complicate the task of selecting measures that are meaningful and feasible and affordable and actionable. For instance, measures of evidence-based processes (i.e., more meaningful) often require clinical information beyond what administrative data can provide. Evidence-based measures tend to rely on data from medical records, surveys, or structured assessments that are costly to collect (less affordable) (Hermann et al. 2000). Highly detailed specifications have successfully operationalized some clinical process measures (more feasible), but the required level of detail makes them less comprehensible to users (less actionable). In assessing timeliness of ambulatory visits after hospital discharge, managers have argued that the measure should include visits that are scheduled but not attended because they reflect the provider’s availability and intent to provide timely care (more accurate). Typically, however, such measures do not. Only attended visits are available through computerized databases; scheduled visits typically need to be collected manually (less affordable). Further difficulty is encountered when one wishes to select measures having these desirable attributes and also representing the mental health system broadly. Within any one dimension of care (e.g., treatment) there will be a limited number of measures having a desired attribute (e.g., evidence basis). When one adds a second dimension of care (e.g., inpatient treatment) there will be fewer, and with a third (e.g., inpatient treatment of schizophrenia) fewer still. There are also inherent contradictions between measure selection based on maximizing desirable measurement properties (represented by the vertical

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arrow in Figure 3–1) and selection that aims to broadly represent diverse features of the mental health system (represented by the horizontal arrow in the figure). Measures of some system dimensions are more likely than other measures to have certain attributes. Measures of treatment are more likely to be evidence based than measures of access, assessment, or continuity. Measures of drug treatments are more likely to be evidence based than measures of psychosocial interventions—not because of the evidence base of the modalities themselves but because of the limitations of available information on treatment. Existing data sources document specific diagnoses, drugs, and dosages—information that can be matched to findings from clinical trials. In contrast, administrative and medical records data do not typically describe psychosocial interventions in enough detail to determine whether their use, intensity, or duration are based on research evidence. The challenge of balancing measure quality with system representativeness is even greater when stakeholder groups come together to select measures for common use. Diverse stakeholders (e.g., clinicians of different specialty groups, payers, and consumers) differ in some of their priorities for quality assessment and improvement. For example, representatives from medical specialty societies often emphasize the need for evidence-based measures. However, representatives from hospital associations and health plans have expressed caution about the greater data-collection burden imposed by evidence-based measures. Representatives of nonmedical mental health specialist organizations have expressed reluctance to support measures emphasizing disorder-focused “medical models” of care. Some consumer advocates have expressed preferences for measures encouraging patient-centered processes of care (such as recovery models, peer support, and housing assistance) rather than measures of evidence-based practices such as psychotropic medications or assertive community treatment (Hermann and Palmer 2002).

❚ INITIATIVES TO DEVELOP CORE MEASURE SETS Until recently, stakeholder organizations each developed their own set of quality measures. This approach ratcheted up the burden on providers, who were required to report different measure results to each payer, MBHO, accreditor, and government agency that oversees them. Even when they adopted similar measures, each organization often employed different specifications, resulting in data that did not permit comparisons of care across geographic regions, plans, or health systems. As a result, a number of stakeholder organizations have sought to develop consensus on one or more set of “core measures” that can be used widely and uniformly across the mental

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healthcare system for quality assessment, improvement, accountability, and related purposes. Core measures have been defined as “a standardized performance measure that meets…evaluation criteria, has precisely defined specifications, can be uniformly embedded in extant systems, has standardized data collection protocols to permit uniform implementation by healthcare organizations and permit comparisons of healthcare organization performance over time…” A core measure set is correspondingly defined as “a unique grouping of performance measures carefully selected to provide, when viewed together, a robust picture of the care provided in a given area” (JCAHO 2005, p. D-3)

Consensus Within Stakeholder Groups A number of initiatives have led to adoption of core measures for use within specific settings and sectors of the mental healthcare system. Under the leadership of the National Committee for Quality Assurance, commercial health plans have adopted common quality measures, known as HEDIS, that include six measures of mental health and substance-related care. HEDIS measures have also been adopted by a number of state Medicaid programs. Under the American Managed Behavioral Healthcare Association, MBHOs developed the Performance Measures for Managed Behavioral Healthcare Programs (PERMS). This set has not been implemented for routine use, but some of its measures have been incorporated into other report cards. Federal Partnerships With State Mental Health Authorities State mental health authorities (SMHAs), which provide treatment to individuals with severe mental illness, receive federal funds that are accompanied by reporting requirements intended to promote accountability. In recent years, federal oversight has shifted from emphasizing regulatory compliance to promoting QI using common quality measures. Progress on several initiatives has come through partnerships among a number of groups: the Substance Abuse and Mental Health Services Administration (SAMHSA), the SMHAs, the National Association of State Mental Health Program Directors (NASM HPD), workgroups of the Mental Health Statistics Improvement Program (MHSIP), and participation of consumers of mental health services and their families. A number of states have adopted common measures of access, technical and interpersonal quality, and outcomes. These measures are constructed principally from existing state administrative data systems and the MHSIP Consumer Survey of experiences with mental healthcare. Prior to implementation, these candidate measures were pilot tested in multistate feasibility studies that examined data availability and consistency across states, adequacy of specifications, and utility of the resulting information. To

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date, this measurement initiative has emphasized process measures over outcome measures. Although many states have, in addition, assessed outcomes such as changes in symptoms and functioning, they have used different instruments, thereby limiting comparability of results. Promising concepts for outcomes assessment—such as proportions of mental health service recipients employed, homeless, or involved in criminal justice system—have been explored but have been limited by difficulties linking state databases across sectors (e.g., databases recording healthcare utilization and data recording convictions for criminal activity), inconsistencies in measurement specifications across states, and limitations in case-mix adjustment (Lutterman et al. 2003). State-federal partnerships have also made notable progress assessing the quality of inpatient care in public psychiatric hospitals. More than 240 public psychiatric hospitals have implemented the NASMHPD Research Institute’s Behavioral Healthcare Performance Measurement System. Participating hospitals select from a panel of measures—including rates of readmission, patient injuries, restraints, seclusion, and elopements—collect and submit the necessary data, and receive regular reports comparing their performance with that of other participating hospitals.

Consensus Across Stakeholder Groups Identifying core measures for use across stakeholder groups, settings, and sectors has proven to be more challenging than adopting measures within a single group. Several initiatives are described in the section that follows. These efforts are based on fairly similar criteria regarding measure attributes and each covers a variety of system dimensions. Where they differ is in the rigor and transparency of the selection process as well as the extent to which a resulting measure set has been identified, specified, and implemented. CQAIMH Core Measures for Mental Health and Substance-Related Care A core measure initiative led by CQAIMH employed a structured method of consensus development to arrive at a balanced a set of 28 measures that are 1) meaningful to stakeholders, 2) feasible to implement, and 3) collectively representative of diverse dimensions of the mental health system. The methodology explicitly acknowledged tensions among these three goals as well as differences in stakeholder priorities. It facilitated trade-offs to arrive at a core set of measures (Hermann and Palmer 2002; Hermann et al. 2002a; Hermann et al. 2004). The consensus development process, funded by the Agency for Healthcare Research and Quality and SAMHSA, was

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based on structured assessment of measures by a 12-member, multi-stakeholder panel with representation of the following perspectives: consumers, families, clinicians, managers, payers, employer-purchasers, federal agencies, state and local mental health and substance abuse authorities, MBHOs, accreditors, and researchers (Table 3–1). Panel members were diverse in their geographic region, race/ethnicity, and gender. They ranged from individual consumers of mental health services to practicing clinicians to leaders of national organizations, including the National Alliance for the Mentally Ill, American Psychiatric Association, JCAHO, and state and federal mental health agencies. Of the 308 process measures in the National Inventory of Mental Health Quality Measures, 116 met screening criteria as unique, operationalized, and based on available sources of data. Panelists rated each measure on attributes of meaningfulness and feasibility drawn from the CQAIMH framework (Figure 3–1). Meaningfulness • • •

The clinical process is important to the panelists’ primary stakeholder group. A gap is present between actual and ideal practice. Improved performance is likely to be associated with better patient outcomes.

Feasibility • • •

The measure is clearly and precisely specified. The data-collection burden is acceptable. Case-mix adjustment is either adequate or not needed to compare performance fairly.

To inform their judgments, panelists were provided information on each measure including specifications, clinical rationale, stakeholders involved in measure development, data source requirements, extent of operationalization, measure status, basis in research evidence and (to the extent available) reliability and validity, standards, measurement of cost, and case-mix adjustment. Measures that received divergent ratings were discussed by the panel and then individually re-rated. This two-stage, modified Delphi approach allowed for a balance between independent judgment and an exchange of perspectives among stakeholders. Rather than forcing agreement among individuals with markedly different points of view, permitting the strongest advocates to

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TABLE 3–1. Panelist characteristics in the consensus development process for the CQAIMH core measure set Panelists Shareholder perspective

1

2

3

Accrediting organization

4

5

6

7

8

9

10 11 12

X X

Public sector payer/purchaser Federal State

X X

X

X

Private sector payer/purchaser

X

X

X

Clinicians Nurse Psychiatrist

X X

X

X

Psychologist

X

X

X

Social worker

X

Case manager

X

X

Managed care organization

X

Delivery system manager

X

Researcher

X X X

Families

X

X

Geographic region Northeast

X

X

X

X

South

X X

North central

X

X

West

X X

X X

Race/Ethnicity/Gender Black

X

Hispanic

X

Female

X X X

X

X

X

X

X

Specialized experience Children Elderly Serious mental illness

X X

X X

Substance abuse

X X X X

Primary care Advocacy

X

X X

X

X

X

X

X

X X

X X

X

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dominate, or arriving at a stalemate from lack of agreement, the method resulted in quantitative data on stakeholder assessments and their degree of consensus that was used to construct a representative set of measures. Based on panel ratings, measures were mapped to healthcare system dimensions from the CQAIMH framework (Figure 3–1), using an algorithm that identified measures with the highest ratings and greatest consensus in each dimension. In this way, balance was achieved between the initiative’s two primary goals: selecting measures having strong attributes and representing diverse dimensions of the healthcare system. The resulting 28 measures (Table 3–2) are notable for their breadth. They include measures from each of the 7 process domains (i.e., treatment, access, assessment, continuity, coordination, prevention, and safety). Approximately half assess care across clinical conditions, while the remainder examine care specific to individual diagnoses. Among measures assessing treatment, half examine psychosocial interventions and half pharmacotherapy. Four are applicable across settings, while most are specific to individual levels of care: inpatient, outpatient, residential, emergency services, nursing homes, and primary care. Measures address important comorbidities of mental illness— including medical and substance use disorders—as well as problems with quality specific to vulnerable populations, including children, elderly individuals, and racial/ethnic minorities. Overall, on a 9-point scale with 1 representing the highest score, the 28 measures had an average rating of 2.96 for meaningfulness and 4.47 for feasibility. There was greater consensus among stakeholders on the meaningfulness of the measures than on their feasibility, with stakeholders having responsibility for data collection indicating greater concern about more laborintensive measures. The selected measures reflect trade-offs on the issue of data-collection burden. Evidence-based measures, which tend to require more burdensome sources of data, compose approximately half of the 28 measures. Forty percent rely on readily available administrative data, while the remainder require additional data from medical records, occurrence reports, program enrollment files, or other sources (Hermann et al. 2004). Forum on Performance Measures in Behavioral Health SAMHSA has supported a series of initiatives building consensus among stakeholders for core measures spanning sectors and settings of care. The Forum on Performance Measures in Behavioral Health originated from a series of meetings of representatives from dozens of stakeholder organizations at the Carter Center in Atlanta, Georgia. This activity builds on work led by the American College of Mental Health Administration, which developed consensus on conceptual areas for measurement. The Forum serves as a vehicle

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TABLE 3–2. CQAIMH core measure set for mental health and substance-related care Measure

Evidence rating* Data source

Treatment One or more visits with adult caregiver for individuals 13 years and under treated for a psychiatric or substance use disorder in 3-month period

C

Administrative data Medical record

Clinician contact with family member of consenting individuals with schizophrenia at initial evaluation

B

Administrative data Medical record

Cumulative daily antipsychotic dosage between 300 and 1,000 chlorpromazine equivalents among individuals with schizophrenia at hospital discharge

A

Administrative data Medical record

Prescription of atypical antipsychotic drug among individuals receiving one or more clinical services for schizophrenia in a 6-month period

A

Administrative data Pharmacy data

Continuation of treatment for 90 days or longer among individuals initiating treatment for a substance use disorder

B

Administrative data

Three or more medication visits or eight or more psychotherapy visits in 12-week period among individuals newly diagnosed with major depression

B

Administrative data

Continuation of antidepressant medication for 12 weeks or longer after initiation for major depression

A

Administrative data Pharmacy data

Daily antipsychotic dosage between 0.5 and 9.0 chlorpromazine equivalents per kilogram of body weight at discharge for individual under 18 years of age hospitalized for psychotic disorder

B

Administrative data Medical record

Daily antipsychotic dosage of 200 chlorpromazine equivalents or more for nursing home resident with dementia without psychotic symptoms in 3-month period

B

Minimum data set

One or more serum drug levels taken for individuals with bipolar disorder treated with mood stabilizers in 12-month period

B

Administrative data Pharmacy data

Use of an anticholinergic antidepressant drug for individuals 65 years and older prescribed antidepressants

B

Administrative data Pharmacy data

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TABLE 3–2. CQAIMH core measure set for mental health and substance-related care (continued) Measure

Evidence rating* Data source B

Administrative data

Number of involuntary physical restraint events per patient day in 3-month period

C

Administrative data Medical record

Number of inpatient injuries per patient day in 3-month period, stratified by assault, self-injury, falls, or during restraint or seclusion

C

Administrative data Occurrence reports

Number of nursing home residents with dementia restrained physically in 3-month period

B

Minimum data set

Assessment of suicidal ideation among patients diagnosed with major depression

C

Administrative data Medical record

Number of unplanned departures per patient discharge in 3-month period, stratified by against medical advice and elopement

B

Administrative data Medical record

Beneficiaries with one or more mental health or substance-related services in 12-month period

C

Administrative data

Denials for mental health or substance-related services per number of requests in 12-month period

C

Administrative data

Assessment of drug and alcohol use at initial evaluation for psychiatric disorder

C

Administrative data Medical record

Assessment of general medical status at initial evaluation for psychiatric disorder

C

Administrative data Medical record

C

Administrative data

One or more psychotherapy visits for individuals within 6 months of hospitalization or emergency department visit for borderline personality disorder Safety

Access

Assessment

Continuity Outpatient visit within 7 days of hospital discharge for psychiatric or substance use disorder

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TABLE 3–2. CQAIMH core measure set for mental health and substance-related care (continued) Measure

Evidence rating* Data source

Four or more psychiatric and four or more substance abuse visits following hospital discharge for dual diagnoses (psychiatric and substance abuse) in 12-month period

B

Administrative data

One or more visits for individuals in 12-month period after initial visit, stratified by race/ethnicity

C

Administrative data

One or more visits per month for 6 months after hospitalization for psychiatric or substance use disorder

B

Administrative data

Contact with primary care clinician for consenting inpatients hospitalized for psychiatric disorder

C

Administrative data Medical record

Enrollment in intensive case management for patients with four or more emergency department visits or two or more hospitalizations for schizophrenia in 12-month period

A

Administrative data Enrollment data

C

Administrative data Medical record

Coordination

Prevention Depression screening for primary care patients during 12-month period

*Evidence rating scale: Level A reflects support by strong research evidence (e.g., randomized controlled studies). Level B indicates support by fair research evidence (e.g., quasi-experimental and observational studies). Level C denotes an absence of research evidence. Source. Adapted from Hermann RC, Palmer RH, Leff HS, et al: Achieving Consensus Across Diverse Stakeholders on Quality Measures for Mental Healthcare. Medical Care 42(12):1246– 1253, 2004. Used with permission.

for consensus development through its workgroups on adult, child, and substance-related measures. In addition, its Methods Working Group developed a model process for measure development as well as a tool for the development of risk adjustment (Hermann 2003b). Core Performance Indicators for State Block Grants As part of a federal movement toward quantitative assessment and accountability, SAMHSA is developing quality measures to be reported by states receiving federal funds to provide mental health services for adults with serious

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mental illness and children with serious emotional disturbances. The measures are based on the Uniform Reporting System, a set of common data standards for state reports on mental health services. Results are reported in the context of establishing performance goals and plans for achieving them. States will begin reporting the first four measures in 2005, with additional measures under development (Table 3–3).

TABLE 3–3. Substance Abuse and Mental Health Services Administration core performance indicators for state mental health systems Indicators

Description

Reporting expected Access to services

Number of persons served by age, gender, and race/ ethnicity; goal to increase access to services

Utilization of psychiatric inpatient beds

Rate of readmission to state psychiatric hospitals within 30 days and 180 days; goal to reduce inpatient utilization and readmission

Evidence-based practices

Number of evidence-based practices provided by state Number of persons receiving evidence-based practice services

Client perception of care

Precentage of clients reporting positively about outcomes

Reporting encouraged Employment or return to school

Profile of adult clients by employment status; goal to increase employment School attendance; goal to increase attendance

Criminal justice involvement

Profile of client involvement in criminal and juvenile justice systems; goal to reduce involvement

Service capacity

Number of persons with severe mental illness or severe emotional disturbance served by age, gender, and race/ethnicity

Under development Social supports

Method to be determined; goal to increase social support

Family stabilization and living conditions

Profile of clients’ change in living situation, including homeless status; goal to improve living conditions

People with co-occurring substance use disorders

To be determined

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Core Measures for Hospital-Based, Inpatient Psychiatric Services Hospitals are moving beyond disparate approaches toward adopting common quality measures for inpatient mental health services. The JCAHO previously required hospitals to implement one of many measurement systems for mental health services that it certified under its ORYX program. More recently, they have shifted to adopting core measures for a number of medical specialties and disseminating results through the Internet in a format that facilitates comparisons among hospitals. In conjunction with NASMHPD and the National Association of Psychiatric Health Systems (NAPHS), JCAHO has launched an initiative to identify and implement a set of core performance measures for hospital-based, inpatient psychiatric services (HBIPS). Among components of the emerging framework are processes of care, outcomes, transitions of care, and safety. Washington Circle Group Core Measures for Alcohol and Other Drug Services A multidisciplinary group of providers, researchers, and managed care and public policy leaders, the Washington Circle Group developed a core set of performance measures for alcohol and other drug services with support from SAMHSA (Table 3–4). Intended for use by public and private-sector health plans, the Washington Circle Group measures have been specified and pilot tested and are being incorporated into a number of national measurement programs, including HEDIS. The measures were constructed from existing data sources such as administrative databases and enrollee surveys. Based on an understanding of substance disorders as chronic relapsing conditions, measures were developed using a framework of services consisting of four domains: prevention/education, recognition, treatment, and maintenance. Outcomes Roundtable for Children and Families Another initiative funded by SAMHSA, the Outcomes Roundtable for Children and Families (ORCF), is working to develop consensus-based quality measures to assess care provided to children and adolescents with emotional, mental health, and substance-related needs and their families (Doucette 2003). Working initially from a list of 180 measures, the group identified 29 candidate measures categorized into four groups: 1) process of care and access; 2) consumer or family perception of quality and appropriateness of care; 3) consumer or family report of improvement as a result of treatment; and 4) developmental measures, defined as “measures that may not reflect current service models but were developed to drive policy change” (p. 3). Data

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TABLE 3–4. Washington Circle Group core measures for alcohol and other drug services Domain

Measure

Data source

Prevention/Education

Educating patients about substance disorders

Enrollee survey

Recognition

Identification rates

Administrative data

Treatment

Initiation of substance disorder Administrative data services

Maintenance

Linkage of detoxification and substance disorder services

Administrative data

Treatment engagement

Administrative data

Interventions for family and significant others

Patient survey

Maintenance of treatment effects

Patient survey

sources were limited to administrative data systems and surveys. The ORCF sought feedback on candidate measures from organizations involved in child mental health services, juvenile justice, child welfare, and family advocacy as well as Medicaid agencies, which play an important role in the financing of care for this population. The survey collected detailed information from ratings and rankings of these measures, focusing on their importance, feasibility, and data availability. Results will be used to further refine the measure set and specifications. Mental Health Statistics Improvement Program Mental Health Quality Report The SAMHSA-sponsored Mental Health Statistics Improvement Program (MHSIP), which developed a consumer survey widely used by SMHAs, is working toward a proposed set of “universal measures” that could be applied to any sector or service system. The proposed MHSIP Mental Health Quality Report, represents a partnership between MHSIP and a number of national stakeholder organizations. The workgroup envisions a set of measures that would include some specific to settings and populations and others that are crosscutting. These measures would be oriented toward consumer perspectives of care and the promotion of recovery from severe mental illness. After compiling an initial list of 52 measures, some more fully developed than others, the group has surveyed stakeholders regarding their relative importance (high, medium, low).

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National Healthcare Quality Report Under a mandate from Congress, the Agency for Healthcare Research and Quality prepares an annual report to evaluate the quality of the nation’s healthcare, to document whether quality is improving over time, and to provide comparative data against which states, health plans, and providers can compare their performance. Organization of the report and measure selection is based on an Institute of Medicine framework that emphasizes dimensions of care (i.e., safety, effectiveness, patient-centeredness, timeliness, equity) and patient needs (i.e., staying healthy, getting better, living with illness or disability, coping with the end of life). Measures are limited to those for which national- and state-level data are already available. The 2004 report included results from three HEDIS depression measures as well as per capita suicide rates from the National Vital Statistics System (Agency for Healthcare Research and Quality 2004). Organisation for Economic Co-operation and Development Healthcare Quality Indicators Project The movement toward common quality measures for mental healthcare goes beyond the borders of the United States. The Organisation for Economic Cooperation and Development (OECD), a nongovernmental organization established after World War II to administer U.S. aid to Europe under the Marshall Plan, has brought together representatives from 20 countries to identify core measures for generating internationally comparable data on quality and outcomes of care. After developing an initial set of measures, mental health was designated as one of six priority areas for further development. A subcommittee was convened to review and recommend measures from existing indicators of technical quality and clinical outcomes based on preexisting administrative data. The initial list consisted of 134 measures from 24 sources. Committee members used a rating process adapted from the CQAIMH initiative to identify 12 meaningful and feasible measures. Eleven assess processes of treatment, continuity, and coordination, while a single outcome measure examines the reduction in life expectancy for people diagnosed with a major mental illness (Hermann et al. 2003).

❚ CONCLUSION Recent initiatives on mental healthcare quality by the National Quality Forum, a national standards-setting organization, and the Institute of Medicine are adding momentum toward identification of core measures. The challenges inherent in selecting quality measures for common use can be visualized by viewing the model in Figure 3–1 as a multidimensional matrix. Each

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cell represents the intersection of specific measure attributes, mental health system dimensions, and stakeholder preferences. The complexity of this matrix, combined with limitations of available measures, has slowed progress toward widespread adoption of standardized quality measures. Yet this goal remains highly desirable, not only to reduce provider burden and improve the comparability of data but also to identify candidate measures for more intensive testing and refinement. Several principles may contribute to further progress. First, some applications may require more rigorously grounded measures than others. Selecting a measure for public disclosure of results, for example, requires a higher threshold of rigor than use for internal improvement or voluntary participation in benchmarking. Still higher standards would be needed for linking measure results to reimbursement rates or sanctions. Second, trade-offs between measure attributes and system characteristics are inevitable and should be made explicit in the selection process. Diverse stakeholders are unlikely to come to agreement on every measure in a core set. The aim should instead be to select a panel of measures that meet diverse needs. Formal methods of consensus development can help surmount the gridlock that can result from competing priorities (Hermann et al. 2004; Rubenstein et al. 1995). Third, preexisting administrative data alone has not yielded a sufficiently meaningful set of measures for quality assessment and improvement. Supplementation of existing data with variables derived from patient surveys and chart review will likely be needed. Nearly all organizations delivering healthcare conduct some medical record review and are understandably reluctant to add to this burden. Existing requirements to review medical records should be reassessed and reallocated, where possible, to consensus-based activities that have high value. Advances in technology, such as implementation of electronic medical records, may help but will not provide a panacea. Consensus will still be needed to identify variables needed for measurement and to develop uniform specifications. Quality measures for mental health and substance-related care are at an early stage of development. Only through iterations of implementation and further development will specifications become more refined, standards emerge, and data become available for testing validity, reliability, and casemix adjustment. Over time, these steps will provide much needed tools for comparing quality across providers and motivating improvements in care.

❚ REFERENCES Agency for Healthcare Research and Quality: National Healthcare Quality Report. Rockville, MD, Agency for Healthcare and Research Quality, 2004

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Chinman M, Young AS, Rowe M, et al: An instrument to assess competencies of providers treating severe mental illness. Ment Health Serv Res 5:97–108, 2003 Cradock J, Young AS, Sullivan G: The accuracy of medical record documentation in schizophrenia. J Behav Health Serv Res 28:456–465, 2001 Doucette A: Summary of Findings: Outcome Roundtable for Children and Families Performance Measurement Survey. Substance Abuse and Mental Health Services Administration, Outcomes Roundtable for Children and Families, 2003 Gostin LO: National health information privacy: regulations under the Health Insurance Portability and Accountability Act. JAMA 285:3015–3021, 2001 Hermann RC: Risk adjustment for mental health care, in Risk Adjustment for Measuring Healthcare Outcomes. Edited by Iezzoni LI. Chicago, IL, Health Administration Press, 2003a, pp 349–361 Hermann RC: Template for Risk Adjustment Information Transfer (TRAIT). Report of the Working Group on Methods and Implementation, Forum on Performance Measures in Behavioral Healthcare. Rockville, MD, U.S. Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, 2003b Hermann RC: National Inventory of Mental Health Quality Measures. Center for Quality Assessment and Improvement in Mental Health, 2004. Available at: http://www.cqaimh.org/quality.html. Accessed July 12, 2005. Hermann RC, Palmer RH: Common ground: a framework for selecting core quality measures. Psychiatr Serv 53(3):281–287, 2002 Hermann RC, Leff HS, Palmer RH, et al: Quality measures for mental health care: results from a national inventory. Med Care Res Rev 57 (suppl 2):135–154, 2000 Hermann RC, Leff HS, Lagodmos G: Selecting process measures for quality improvement in mental healthcare. 2002a. Available at: http://www.cqaimh.org/research.html. Accessed June 23, 2005. Hermann RC, Leff HS, Provost SE, et al: Process measures used in quality assessment and improvement: are they based on research evidence? Presented at the 15th National Institute of Mental Health Services Research Conference, Washington DC, April 2002b Hermann RC, Mattke S, Organisation for Economic Co-operation and Development Mental Health Care Panel: OECD Technical Paper No. 17 Selecting Indicators for the Quality of Mental Health Care at the Health Systems Level in OECD Countries. 2003. Available at: www.oecd.org. Accessed June 23, 2005. Hermann RC, Palmer RH, Leff HS, et al: Achieving consensus across diverse stakeholders on quality measures for mental healthcare. Med Care 42(12):1246–1253, 2004 Iezzoni L: Assessing quality using administrative data. Ann Intern Med 127:666–674, 1997 Institute of Medicine: Envisioning the National Health Care Quality Report. Washington, DC, National Academy Press, 2001 Joint Commission on Accreditation of Healthcare Organizations (JCAHO): Specification Manual for National Hospital Quality Measures. Oakbrook Terrace, IL, Joint Commission on Accreditation of Healthcare Organizations, 2005 Kosecoff J, Fink A, Brook R, et al: The appropriateness of using a medical procedure: is information in the medical record valid? Med Care 25:196–201, 1987 Lurie N, Popkin M, Dysken M, et al: Accuracy of diagnoses of schizophrenia in Medicaid claims. Hosp Community Psychiatry 43:69–71, 1992

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Lutterman T, Ganju V, Schacht L, et al: Sixteen-State Study on Mental Health Performance Measures. Rockville, MD, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, 2003 Marshall SF, Deapen D, Allen M, et al: Validating California teachers study self-reports of recent hospitalization: comparison with California hospital discharge data. J Epidemiol 158:1012–1020, 2003 Office of the Surgeon General: Mental Health: Culture, Race, and Ethnicity. A Supplement to Mental Health: A Report of the Surgeon General. Rockville, MD, U.S. Public Health and Human Services, 2001 Rubenstein L, Fink A, Yano E, et al: Increasing the impact of quality improvement on health: an expert panel method for setting institutional priorities. Jt Comm J Qual Improv 21:420–432, 1995 Unutzer J, Katon W, Callahan CM: Collaborative care management of late-life depression in the primary care setting: a randomized controlled trial. JAMA 288:2836–2845, 2002 Zima BT, Hurlburt MS, Knapp P, et al: Quality of publicly funded putpatient specialty mental health care for common childhood psychiatric disorders in California. J Am Acad Child Adolesc Psychiatry 44(2):130–144, 2005

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C H A P T E R

4

Comparing and Interpreting Results From Process Measurement

R

esults from process measures can be challenging to interpret when used to assess provider performance (i.e., the performance of clinicians, clinics, hospitals, or plans). Process measures assess interactions between providers and patients; thus, measure results reflect provider performance but may also be influenced by patient actions. This fact presents two challenges to interpreting results. First, when comparing performance across providers, one must distinguish between differences in results that stem from provider performance and differences determined by the clinical or sociodemographic composition of the populations the providers treat. Analysis of measurement results may need to adjust for these differences in “case mix” to compare care fairly across providers. Second, optimal performance on a rate-based quality measure may theoretically be 100%, but this level of performance may not be feasible due to patient factors beyond a provider’s control. Under these circumstances, additional information can help determine whether measure results demonstrate opportunities for improvement or reflect the best performance that is feasible.

❚ CASE-MIX ISSUES IN COMPARISON OF RESULTS Although process measures are used to evaluate quality of care delivered by a provider, they may also be influenced by patient characteristics beyond the

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provider’s control. A widely used measure of continuity of care, for instance, is the proportion of patients hospitalized for a psychiatric disorder who attend an outpatient visit within 7 days of discharge. Several components of the quality of inpatient care could influence results on this measure, including • Was the patient an active participant in discharge planning? If the patient was unable to participate, was a family member, friend, or case manager involved? • Was a timely appointment for follow-up care scheduled before discharge? • Were the patient’s location and transportation resources considered in selecting a site for outpatient care? • Was ambulatory care the most appropriate disposition after the hospital stay or did the patient require a different level of care? On the other hand, even if the inpatient team took all appropriate steps, a substantial number of patients will not attend the follow-up visit. Studies indicate that individuals with severe mental illness have no-show rates for outpatient visits between 30% and 50%. The probability of missing a scheduled appointment varies with a number of patient characteristics, including • • • • •

Psychiatric conditions impairing energy, motivation, or cognition Comorbid substance use Unstable housing Absence of social support Meager financial resources

Furthermore, the prevalence of these characteristics can vary among different providers’ patient populations. Thus, performance on the continuityof-care measure may be influenced by not only the quality of inpatient care, but also a hospital’s case mix. If hospitals are to be compared based on their performance on the measure, then statistical adjustment may be needed to remove the influence of patient characteristics on the results. Not all process measures require such adjustment. Performance on some measures is influenced only by the provider’s actions, not the patient’s. The following measure is one such example: Among patients newly assessed and diagnosed with major depression, is the clinician’s assessment of suicidality documented in medical record?

Other measures are potentially influenced by patient actions, but their specifications can be modified to minimize the influence of variability among patients. Performance on a measure examining “the proportion of hospital-

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ized patients for which an inpatient clinician contacted the patient’s outpatient clinician” would be lower among patients who did not have an outpatient clinician or were unwilling to consent to the contact. Hospitals treating patients with fewer resources or more severe conditions may be unfairly represented by this measure as providing lower quality care. Measure specifications can sometimes address this type of issue, as in the measure below: Among patients hospitalized for a psychiatric disorder, the proportion for whom the medical record documents contact between the inpatient and outpatient clinician or that the patient did not have an outpatient clinician or that the patient refused consent for contact.

Although completely eliminating the influence of patient characteristics is not always possible, many measures specify a denominator population with criteria for specific age groups, diagnoses, and settings as a means of producing a more homogenous sample that varies less across provider caseloads. This approach has its limits. Measures focusing on very narrowly defined populations may evaluate processes of care less relevant to a broader understanding of quality. They can also result in small sample sizes that lack statistical power to detect differences in quality among providers.

Case-Mix/Risk Adjustment If not addressed in measure specifications, case-mix differences can be addressed in the analysis of measure results. Case-mix adjustment has been defined as a statistical method of accounting for patient-related factors in comparisons of quality, costs, or outcomes of care (Iezzoni 2003). Basic elements of a statistical model for case-mix adjustment include an “outcome” (in this case, performance on a quality measure), patient characteristics hypothesized to influence measure performance, and a statistical equation that quantifies the relationship between significant characteristics and measure performance. Case-mix adjustment is also known as “risk adjustment,” with patient characteristics described as “risk factors,” because modeling seeks to quantify the risk of a given outcome in a specified population. The simplest form of case-mix adjustment is stratification. Measure results are presented within categories (or strata) restricted to one or more patient characteristics, thus permitting comparisons among more homogenous groups. Models using multivariate statistical methods allow for simultaneous adjustment among several case-mix characteristics and can account for interactions between them. Risk factors important to consider in adjustment of quality-measure results in mental health and substance-related care are summarized in Table 4–1. Both available and important, primary diagnosis is among the most commonly used risk factors in adjustment models. Diagnosis provides a partial

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TABLE 4–1. Patient factors used for case-mix adjustment in mental healthcare Diagnosis Primary psychiatric or substance use disorder Comorbid conditions Secondary psychiatric disorders Secondary substance-use disorders Personality disorders Mental retardation Medical conditions Severity Symptoms Functional impairment General health status Chronicity/recurrence Source.

Sociodemographic Age Gender Marital status Education Socioeconomic status Geographic region Employment status Housing status Other Prior utilization Legal status Disability status Social support

Hermann 2003a.

characterization of a patient’s type and severity of symptoms and functional impairment, factors that can influence the patient's participation in clinical care. Comorbid conditions can also contribute to measurement outcomes. For example, approximately 30%–50% of inpatients with schizophrenia also have substance use disorders; patients with both conditions have lower compliance with treatment and worse outcomes than individuals with schizophrenia alone (Dixon 1999). A number of strategies have been developed to quantify comorbid conditions in risk adjustment models. Medical comorbidity, for example, can most simply be represented as a binary variable (i.e., present/absent), or by the number of active medical conditions or a count of the number of physiologic systems (e.g., cardiovascular, pulmonary, renal, etc.) with active disease. An innovative approach to measuring medical comorbidity uses pharmacy claims to calculate a severity index based on the number and type of medications a patient receives (Schneeweiss and Maclure 2000). Diagnostic information is commonly recorded in utilization data collected for reimbursement or administrative purposes. However, for reasons discussed in Chapter 3, the accuracy of this information may be limited. One of the most important factors to consider for risk adjustment—a patient’s severity of illness—can be the most burdensome to collect. Severity of symptoms and functioning often varies among patients, even those with the same diagnosis. When provided with results showing poor performance on a comparative quality assessment initiative, clinicians frequently respond that their performance is worse because “my patients are sicker.” This response highlights the need for adequate adjustment of measure results if they are to motivate clinicians to improve performance.

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There are many well-developed and tested ratings scales that assess severity of symptoms and functional impairment; some are specific to individual disorders, whereas others assess mental health status more broadly (American Psychiatric Association Task Force for the Handbook of Psychiatric Measures 2000). However, systematic use of clinical rating scales is uncommon in routine mental healthcare. Although some health systems have innovated in this area, there is little consensus about which instruments should be used. Implementation specifically for quality assessment has generally been considered too burdensome. Medical records can provide information relevant to severity of illness, but these data are documented inconsistently and pose similar data-collection burdens. Administrative data contain very limited information on severity of illness. The fifth digit of standard codes for documenting diagnosis provides information on severity in some cases. For example, the fifth digit of the ICD10 code for major depression indicates whether the episode is mild, moderate, or severe. However, providers frequently do not document this portion of the code. An analysis of 1994–1995 Medicaid data from six states found the fifthdigit specifier for major depression was missing for 70% of outpatient claims and 35% of inpatient claims (Hermann 2003a). As discussed in Chapter 1, the Global Assessment of Functioning (GAF) score is widely available in clinical records as Axis V of the DSM-IV-TR diagnostic system. However, GAF scores have uncertain accuracy in routine use. Other data elements, available from administrative datasets, have been used as proxies for patient severity, such as involuntary commitment on admission, referral from another hospital or emergency department (rather than from home or a clinician’s office) prior to admission, and planned versus unplanned discharge (e.g., against medical advice or elopement). Prior utilization of mental health services has also been used as an indicator of recurrence or chronicity, as have disability determinations made by veterans or social service agencies. Performance on quality measures has been shown to vary by patients’ sociodemographic characteristics, making these factors candidates for risk adjustment models. A recent study examined variations among Medicare beneficiaries on the Health Plan Employer Data and Information Set (HEDIS) continuity-of-care measure, “the proportion of inpatients attending a followup visit within 30 days of discharge.” Fifty-three percent of Medicare patients hospitalized for a psychiatric condition met criteria for the measure, but significantly lower rates were observed among individuals who were black, dually insured by Medicaid (a proxy indicator of low income), or had low educational attainment (Schneider et al. 2002). Other studies have found age and gender to be associated with differential results on quality measures (Hermann et al. 1998). However, not all sociodemographic characteristics should necessarily be included in a risk adjustment model; the purpose of the

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model should be considered. Indicators of social support, such as marital status or residential status (e.g., homeless or living in a group home), might be important to adjust for when comparing hospitals on the basis of the HEDIS continuity measure. On the other hand, racial or ethnic status would be a poor candidate for inclusion in the adjustment model if an intent of quality measurement were to identify and motivate improvement in these disparities in care. Similarly, whether to adjust for provider characteristics has been a controversial subject in risk adjustment. On one hand, facility type may proxy for unmeasured differences among patients—particularly if measures of patient severity were insufficient. In this case, adjusting for facility type could provide more fair comparisons. Alternatively, if provider performance does vary systematically on the basis of facility type, one would not want to “adjust away” this difference. For example, evidence suggests that practice patterns differ between psychiatric units in general hospitals and psychiatric specialty hospitals (Ettner and Hermann 1998). In assessing quality of psychiatric hospital care, should the performance of these two types of hospitals be compared, or should results be adjusted by hospital type to create a level playing field? The answer rests in part on whether one believes the differences in practice patterns reflect differences in patient populations or in the quality of care provided. Research studies support both perspectives. Studies of risk adjustment models proposed for the Medicare Prospective Payment System found evidence suggesting that hospital type did proxy for patient differences not revealed by administrative data (Horgan and Jencks 1987). However, research based on clinically detailed data from medical records found that quality of inpatient care varied between specialty psychiatric units and general medical units (Norquist et al. 1995). Until recent years, risk adjustment models for mental healthcare focused mainly on lengths of hospital stay and cost. Recent years have seen advances in the application of multivariate modeling to clinical processes and outcomes (Hermann 2003a). Table 4–2 summarizes applications of case-mix adjustment to quality assessment in mental healthcare. As these examples illustrate, a unique configuration of risk factors may be needed to adjust results from individual measures. In some cases, different risk factors have been applied to adjusting results for the same measure, reflecting the absence of a standardized methodology and differences in data availability across initiatives. The application of case-mix adjustment to quality measure results does not guarantee that comparisons of provider performance can be made fairly, only that they may be “more fair” than without adjustment. Case-mix adjustment is usually a partial solution to a complex problem. Some models have been evaluated to determine the percentage of variance explained by the characteristics included in the model. A Center for Quality Assessment and

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TABLE 4–2. Applications of case-mix adjustment to mental health quality measures Quality measures

Risk factors

Stratification Child and Adolescent Residential Psychiatric Programs (CHARPP) measures Therapeutic holds

Age

Seclusion rates

Age

Mental Health Statistics Improvement Program (MHSIP) measures Waiting time between request for services and first visit

Age, illness severity, dual diagnoses, emergency situation

National Committee for Quality Assurance Health Plan Data and Information Set (HEDIS) measures Penetration rates for mental health services

Patient: Age, gender Unit: Level of care

ValueOptions Corporate Quality Indicators Treatment engagement for attention- Insurance type deficit/hyperactivity disorder Multivariate analysis Department of Veterans Affairs Mental Health Program Performance Monitoring System Community tenure after discharge

Age, gender, diagnoses, dual diagnoses, service-connected illness

Ambulatory follow-up after discharge

Age, gender, diagnoses, dual diagnoses, service-connected illness

National Association of State Mental Health Program Directors (NASMHPD) Research Institute Performance Measurement System Hospital readmission rates

Patient: Age, gender, race, marital status, diagnoses, residential status, legal status, referral source Unit: Specialty, chronicity

Restraint and seclusion rates

Patient: Age, marital status, diagnoses, residential status, legal status, referral source Unit: Specialty, chronicity, bed capacity, security level, locked status

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TABLE 4–2. Applications of case-mix adjustment to mental health quality measures (continued) Quality measures

Risk factors

Veterans Administration/Department of Defense Performance Measures for Depressive Disorder Continuation of medication or therapy for depression

Age, gender, depression history, psychosis, substance abuse, medication usage, primary care visits

Ambulatory follow-up after discharge

Age, gender, depression history, psychosis, substance abuse, medication usage, primary care visits

Improvement in Mental Health (CQAIMH) review of published reports of risk adjustment models applied to mental health and substance-related care found that those using administrative data sets explained an average of 6.7% of variance in outcomes (including quality, costs, utilization, or clinical status), whereas models that additionally included data from medical records, severity ratings, or other higher-cost sources explained a more robust 22.8% (Hermann 2003a; R.C. Hermann and C.K. Rollins, unpublished data, July 2005). This finding further supports the need for a combination of data sources for effective quality assessment.

Template for Risk Adjustment Information Transfer With funding from the Substance Abuse and Mental Health Services Administration, the Template for Risk Adjustment Information Transfer (TRAIT) was developed by the CQAIMH to bridge a gap between measure development and the analysis of measure results. Measure development panels typically include participants with expert knowledge about the clinical process under evaluation, including patient factors that may influence measure results. However, they often lack individuals with sufficient statistical expertise to develop risk adjustment models, thus the topic goes unaddressed. After a long period during which a measure is specified, disseminated, and implemented, statisticians are asked to analyze and interpret the results. However, these individuals often lack detailed clinical knowledge about the clinical process or potential risk factors for the adjustment model. TRAIT helps measure developers to identify and document potential risk factors specific to a quality measure. Drawing on their clinical experience and knowledge of the research literature, measure developers are guided to consider sociodemographic, clin-

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ical, and other patient characteristics that may influence measure results. By disseminating TRAIT results along with measure specifications, developers can provide crucial information to analysts for interpreting results. The instrument and user’s guide can be downloaded at http://www.cqaimh.org/research.html (Hermann 2003b).

❚ COMPARATIVE DATA FOR INTERPRETING MEASURE RESULTS Comparative data are useful for interpreting results of quality measures of both patient-level and aggregate-level process measures. Patient-level measures evaluate the experience of each eligible patient against an intrinsic standard. An example is provided by the measure, the proportion of patients with schizophrenia and treated with an antipsychotic medication who receive an adequate daily dosage. The intrinsic standard is the evidence-based therapeutic range for antipsychotic drugs in schizophrenia. On the basis of this standard, each patient is classified as receiving good or poor quality care. Theoretically, the optimal level of performance a provider can achieve is 100% (i.e., all of their patients receive care within the standard). However, even if a provider does everything right, optimal performance is not achievable for some process measures and not desirable for others. With regard to the schizophrenia measure, a small proportion of patients with schizophrenia may benefit from a higher-than-recommended dosage of antipsychotic medication. Others might refuse to take even the lowest recommended dosage despite the provider’s best efforts and use of strategies to educate, motivate, and treat side effects. For providers seeking to interpret their results on this measure, it would help to know what levels of performance are desirable and achievable. Aggregate-level process measures are even more reliant on external sources of data for interpreting results. These are measures for which inferences regarding quality can be made only for the sample as a whole rather than for each case individually. Lacking an intrinsic standard, these measures are used to identify outliers in the performance of providers treating comparable patient populations. An example is the measure of hospitals’ rates of physical restraints per discharged patient. This measure does not determine the appropriateness of any one incidence of physical restraint. It is used to identify hospitals with higher-than-average restraint rates for further inquiry and intervention to reduce their use. Several types of data can be useful in interpreting data from process measurement, including standards, means, norms, and benchmarks. Some of these terms have been applied inconsistently and with overlapping usage, but recent

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literature has been converging toward more distinct definitions (Hermann and Provost 2003). They are described and illustrated in the following sections.

Standards Standards for process measures are numerical thresholds for performance established by individuals or groups. Standards are often developed administratively—that is, without extensive analysis. As such they provide a low-burden option for establishing expected levels of performance. Standards can be absolute (e.g., 90% performance on a measure) or relative (e.g., “10% improvement in performance over last year’s result”). Establishing tiers of standards can differentiate thresholds of performance, such as excellent, acceptable, and inadequate levels of care. An example can be found in the Veterans Health Administration requirement that its primary care clinics screen their patients for depression. They evaluate each clinic’s performance, characterizing clinics that screen 87% of their patients as “fully successful” and clinics that screen 94% as “exceptional” (Veterans Health Administration Office of Quality and Performance 2002). As part of the accountability movement, some public and private payers have established explicit performance standards for quality measure results, in a few cases writing them into provider contracts with associated incentives or penalties. The Massachusetts agency administering Medicaid established such standards in its contract with a managed behavioral healthcare organization (MBHO) to manage mental health services for 400,000 state Medicaid recipients (Table 4–3). The contract tied financial bonuses and penalties to achieving the specified levels of improvement (Sabin and Daniels 1999). The MBHO, in turn, established standards for performance for the hospitals and clinics credentialed to be part of its network and used monthly performance reviews with providers to encourage conformance. The MBHO also used performance results in its process of renewing contracts with hospitals. More recently, Medicare and commercial payers have launched pay-for-performance initiatives that provide increased levels of reimbursement to providers meeting performance standards for specified conditions, processes, and outcomes (Rosenthal et al. 2004) A limitation to administratively established standards is that they may or may not be informed by statistical analysis, prior experience, or stakeholder input. Ideally, the foundation for a standard should be explicit and convincing. If providers perceive a standard as arbitrary or unattainable, they may be less motivated to work toward achieving it. Relative standards can be useful to encourage incremental steps toward a goal but may have other drawbacks. They can impose lower expectations for improvement on poor performers than good performers. The standard of 10% improvement over the prior

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TABLE 4–3. Performance standards for quality measures applied to Medicaid managed behavioral healthcare Standards Measure

Medicaid agency

MBHO

Percentage of hospitalized patients with aftercare visit within 7 days of discharge

<70% increase, penalty ≥75% increase, bonus

>90%

Percentage of hospitalized patients with medication visit within 14 days of discharge

<22% increase, penalty ≥25% increase, bonus

>90%

Percentage of consenting patients with three or more mental health visits whose clinician contacted their primary care physician during 9-month period

<5% increase, penalty ≥20% increase, bonus

>80%

Outpatient

Inpatient Percentage of discharged inpatients readmitted within 30 days

–

<20%

Percentage of hospitalized patients with aftercare plan documented on discharge

–

>95%

Percentage of hospitalized children/ adolescents with documentation of family participation in treatment and discharge planning

–

>95%

year’s performance requires that the provider achieve 30% conformance to an evidence-based guideline to improve by 3%, while the provider who has already achieved 70% conformance is expected to improve twice as much. Paradoxically, as the provider gets closer to the highest level of performance achievable, the numerical expectation for improvement becomes greater. These issues are not unsolvable, but require attention in the development of performance standards.

Mean Results The most commonly available data for interpreting results are average rates achieved by other providers. Comparative quality assessment initiatives typically require providers to submit their results to a coordinating entity such as a state agency or accrediting organization that analyzes the results and pro-

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vides each provider with a report comparing its performance with group means or percentiles. If patient data are collected for case-mix adjustment, the report may provide adjusted rates for individual providers (direct adjustment) or a ratio comparing individual performance to expected performance given the provider’s case mix (indirect adjustment). Because differences in performance may be systematic or random, it is desirable to apply statistical testing to analyses of results. Ideally, a provider has access to a range of results from similar providers treating comparable patient populations. However, many providers will have access only to far less optimal data if any at all. Consider the following case illustration. Clinicians at a community mental health center identify adherence to antidepressant medication as an area of potential concern. They collect data to assess conformance in their patient population to the H EDIS measure of continuous antidepressant use over the first 12 weeks of treatment. They achieve a 30% conformance rate, prompting debate over how to interpret the result. Some of the clinicians, worried about the low score, propose a major improvement effort. Other clinicians argue that a perfect score is unrealistic, citing their patients’ lack of financial resources, transient residence, high rates of substance abuse, and frequent missed appointments. The clinicians review other findings on the measure on the Internet to get a sense of what level of performance might be achievable. Commercial health plans, they find, have achieved scores between 56% and 63% on a national report card (National Committee for Quality Assurance 1999), while a research study of performance by two other health plans demonstrated results (23%–44%) that are closer to their own (Kerr et al. 2000). They discuss possible differences between their patients, who generally lack health insurance or are publicly insured, and those enrolled in a commercial health plan. Risk adjustment is not an option given their resources and lack of access to plan data. However, they identify a research study that applied the same measure in the Medicaid population, a similar cohort (Melfi et al. 1998). The result in this sample, 19% conformance, supports the perspective of the clinicians who suggested their performance might be as good as can be expected. Compared with this population, the center’s performance appears better than average.

The center’s learning process is discussed further in the section on benchmarks later in the chapter. At this stage, however, the clinicians at the center faced a situation common to other small providers attempting to conduct measurement-based quality improvement (QI) without access to large comparative databases. When the only data available to inform interpretation of local results are results from published reports, several considerations can inform the comparison. • What sample sizes underlie the locally obtained and published results?

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• Is the published result from a single site or does it reflect average performance across many sites? • Is the published result obtained from a convenience sample, a random sample, or the population of enrollees or service recipients? • Is the published sample comparable with the local patient cohort in terms of sociodemographic and clinical characteristics? • Are there differences in measure specifications (e.g., major depression versus all depressive disorders) that might lead to different results?

Norms Norms for process measures reflect average results for representative samples or populations. Uses and limitations of norms are similar to those described for averages. However, norms can be more useful for comparisons of results from similarly large, heterogeneous cohorts. Published norms are sometimes stratified by age, diagnosis, or other patient characteristics, allowing for better interpretation of results for these subgroups. Norms are available for some mental health measures that have been applied to populations defined by geography, sectors, or healthcare financing. The National Association of State Mental Health Program Directors Research Institute collects data on several measures of inpatient care from most state psychiatric hospitals and makes aggregate results available. The National Committee for Quality Assurance provides mean rates on HEDIS measures for commercial health plans, while several states make available HEDIS results from Medicaid. Figure 4–1 illustrates results from 34 Texas health plans on the HEDIS measure of continuous antidepressant use. Performance among plans ranged from 20% to 61%, with a statewide norm of 51%.

Statistical Benchmarks Conceptually, benchmarks represent the level of performance achieved by the highest-performing providers. Benchmarks address a limitation of means or norms as sources of feedback in measurement-based QI. Means encourage comparisons with average performance while, ideally, efforts to improve quality should be focused on achieving excellence. Benchmarks are particularly useful for process measures. When 100% conformance for a measure is not feasible, identifying an attainable level of excellent performance gives providers a realistic goal for improvement. Benchmarks can also be used to identify high-performing providers who may be sources of “best practices” or process innovations that lead to superior performance. Operationally, how does one identify a benchmark? A relatively simple approach used in many quality assessment initiatives is to identify the level

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FIGURE 4–1. Mean performance of Texas health plans on HEDIS measure of acute depression treatment. Source. Reprinted from Texas Health Care Information Council (THCIC). Guide to Texas HMO Quality: 2002, September 2002, p.6. Used with permission.

of performance achieved by a high-performing cohort of providers, such as those at the 75th or 90th percentile. This result can be given as feedback to all participants as a basis for comparing their own performance. This method is useful for large patient samples with relatively few providers and measures that are broadly applicable to a large proportion of the sample. However, under conditions in which each provider treats a smaller number of patients eligible for the measure, benchmarking efforts can encounter a problem with small denominators. Providers treating few patients that meet criteria for a measure are more likely to achieve very high or very low measure conformance (e.g., 3/3 patients =100% or 0/3 patients=0%). Their performance skews results to the outlying ends of the distribution, which can inflate the result at

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the 90th percentile to an unrealistically high level. Data analysts can minimize this effect by setting a minimum number of patients for providers included in the sample, but this further exacerbates sample-size limitations, and different cut-offs among samples can lead to a lack of comparability of results. Kiefe, Weissman, and colleagues developed a method for deriving statistical benchmarks for healthcare that addresses these limitations (Kiefe et al. 1998; Weissman et al. 1999). They defined benchmarks as the performance achieved by the top 10% of providers in a sample, adjusted for the number of patients per provider using Bayesian methods. Their approach has several strengths: it identifies high but achievable levels of performance, it is objective and reproducible, and it reduces the disproportionate impact of smalldenominator cases without eliminating them from the sample. CQAIMH applied this methodology to process measures in mental healthcare using data from State Medicaid Research Files for 1994–1995 for 11,684,089 Medicaid enrollees in six states: California, Georgia, Indiana, Mississippi, Missouri, and Pennsylvania (Hermann et al. 2002). Performance results were aggregated at the provider level using Medicaid provider identification numbers, which represent individual or co-practicing clinicians. Table 4–4 shows statistical benchmarks derived by CQAIMH for three process measures: blood level monitoring for patients receiving lithium, carbamazepine, or valproic acid; acute-phase medication treatment for depression; and outpatient follow-up after hospitalization for a psychiatric disorder. Benchmarks for each measure (67.3%–85.6%) were well below 100%, suggesting that full conformance on these measures may not be achievable. On the other hand, each benchmark was well above the mean performance among providers for the corresponding measure, suggesting that the benchmarks may provide a better target for quality improvement than statistics that represent central tendency. The variation in benchmarks among the three measures also suggests that the one-size-fits-all approach of administrative standards is not adequate. The benchmark of 86% for the HEDIS measure of acute-phase antidepressant treatment provides additional information for the community mental health center described earlier. Although average performance was not far removed from the center’s results, the much-higher benchmark in this Medicaid sample suggests that achievable performance is considerably higher and that a QI intervention may be indicated. Statistical benchmarks are not yet widely available for mental health measures, although their use is expanding in other areas of healthcare. In a randomized, controlled study, Kiefe et al. (2001) demonstrated that primary care physicians participating in a QI initiative achieved greater rates of improvement when provided feedback on individual performance compared to statistical benchmarks as opposed to feedback comparing individual performance

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TABLE 4–4. Statistical benchmarks for mental health quality measures among Medicaid beneficaries Cases, N

Providers, N

One or more mood-stabilizer blood levels for individuals with bipolar disorder who had one or more moodstabilizer claims during at least three of four consecutive quarters

8,907

12-week or longer duration of antidepressant drug treatment for individuals with depression One or more outpatient visits attended within 7 days after discharge for a mental health disorder

Measure

Mean result

Statistical benchmark

2,344 (outpatient)

14.9%

67.3%

13,028

4,494 (outpatient)

45.8%

85.6%

78,627

1,371 (hospitals)

25.0%

82.4%

to mean results. It should be noted that benchmarking does not obviate the need for risk adjustment. Credible, risk-adjusted comparisons may be crucial to the successful use of benchmarks to motivate change in provider practices.

❚ CONCLUSION Measure developers and users of measure results need to be cognizant of the potential for patient factors to influence comparisons of quality among providers. A series of questions can be used to evaluate a proposed measure or a report of comparative results. • Does the measure specify a sufficiently homogenous patient sample, so that case-mix factors are unlikely to vary across providers? • Are remaining differences in case mix likely to influence results for reasons outside a provider’s control? • If case-mix factors do influence results for reasons outside the provider’s control, and the patient samples under evaluation vary in the prevalence of these factors, is the measure accompanied by an analytic strategy for adjusting results? • Has the adequacy of the risk adjustment model been assessed?

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TABLE 4–5. Characteristics of metrics for interpreting quality measurement results Thresholds

Strengths

Limitations

Standard

Sets an explicit expectation for May lack credibility among stakeholders performance Can establish an expectation Can be used to identify that is either unrealistic or too opportunities for easily achieved improvement Does not require data analysis

Mean

Sampling and case-mix factors Available from comparative may limit utility as basis for assessment or published comparison results Provides a basis for preliminary Comparison to average results provides a limited goal for comparison improvement Results from multiple samples increases utility

Norm

Useful for comparison of measure results from large, heterogeneous populations May be stratified to report performance in specific subpopulations

Less useful in smaller, nonrepresentative samples Available for few mental health measures Comparison to average results provides a limited goal for improvement

Statistical benchmark

Represents excellent yet achievable care Can be derived using an objective, reproducible method

Available for few mental health measures Measures influenced by patient characteristics may still require case-mix adjustment

Source. Adapted from Hermann RC and Provost SE: “Best Practices: Interpreting Measurement Data for Quality Improvement: Standards, Means, Norms, and Benchmarks.” Psychiatric Services 54:655–657, 2003. Used with permission.

Interpretation of measure results can also be hampered by the lack of knowledge of what level of performance is clearly inferior, typical, or the best achievable. Standards, means, norms, and benchmarks each provide feedback that can be useful in interpreting results. Table 4–5 summarizes the strengths and weaknesses of each approach.

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❚ REFERENCES American Psychiatric Association Task Force for the Handbook of Psychiatric Measures: Handbook of Psychiatric Measures. Washington, DC, American Psychiatric Association, 2000 Dixon L: Dual diagnosis of substance abuse in schizophrenia: prevalence and impact on outcomes. Schizophr Res 35(suppl):S93–S100, 1999 Ettner S, Hermann R: Inpatient psychiatric treatment of elderly Medicare beneficiaries, 1990–91. Psychiatr Serv 18:1173–1179, 1998 Hermann RC: Risk adjustment for mental health care, in Risk Adjustment for Measuring Healthcare Outcomes. Edited by Iezzoni LI. Chicago, IL, Health Administration Press, 2003a, pp 349–361 Hermann RC: Template for Risk Adjustment Information Transfer (TRAIT). Report of the Working Group on Methods and Implementation, Forum on Performance Measures in Behavioral Healthcare, 2003b. Available at: http://www.cqaimh.org/ research.html. Accessed August 2005. Hermann RC, Provost SE: Best practices: interpreting measurement data for quality improvement: standards, means, norms, and benchmarks. Psychiatr Serv 54:655–657, 2003 Hermann R, Ettner S, Dorwart R: The influence of psychiatric disorders on patients’ ratings of satisfaction with health care. Med Care 36:720–727, 1998 Hermann RC, Chan J, Chiu WT, et al: Interpreting findings from quality measurement initiatives in mental health and substance abuse: use of prior results and statistical benchmarks. Report for the U.S. Substance Abuse and Mental Health Services Administration, Center for Quality Assessment and Improvement in Mental Health. Available at http://www.cqaimh.org/research.html. Accessed June 25, 2002. Horgan C, Jencks S: Research on psychiatric classification and payment systems. Med Care 25(suppl):S22–S36, 1987 Iezzoni LE: Risk Adjustment for Measuring Healthcare Outcomes. Chicago, IL, Health Administration Press, 2003 Kerr E, McGlynn E, Van Vorst K, et al: Measuring antidepressant prescribing practice in a health care system using administrative data: implications for quality measurement and improvement. Jt Comm J Qual Improv 26:203–216, 2000 Kiefe CI, Weissman NW, Allison JJ, et al: Identifying achievable benchmarks of care: concepts and methodology. Int J Qual Health Care 10:443–447, 1998 Kiefe CI, Allison JJ, Williams O, et al: Improving quality improvement using achievable benchmarks for physician feedback: a randomized controlled trial. JAMA 285:2871–2879, 2001 Melfi C, Chawla A, Croghan T, et al: The effects of adherence to antidepressant treatment guidelines on relapse and recurrence of depression. Arch Gen Psychiatry 55:1128–1132, 1998 National Committee for Quality Assurance: Health Plan Data and Information Set (HEDIS 2000). Washington, DC, National Committee for Quality Assurance, 1999 National Committee for Quality Assurance: Quality Compass 2000. Washington, DC, National Committee for Quality Assurance, 2000

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Norquist G, Wells KB, Rogers WH, et al: Quality of care for depressed elderly patients hospitalized in the specialty psychiatric units or general medical wards. Arch Gen Psychiatry 52:695–702, 1995 Rosenthal MB, Fernandopulle R, Song HR, et al: Paying for quality: providers’ incentives for quality improvement. Health Aff (Millwood). 23(2):127–141, 2004 Sabin J, Daniels N: Public-sector managed behavioral health care, II: contracting for Medicaid services. The Massachusetts experience. Psychiatr Serv 50:39–41, 1999 Schneeweiss S, Maclure M: Use of comorbidity scores for control of confounding in studies using administrative databases. Int J Epidemiol 29:891–898, 2000 Schneider E, Zaslavsky A, Epstein A: Racial disparities in the quality of care for enrollees in Medicare managed care. JAMA 287:1288–1294, 2002 Veterans Health Administration Office of Quality and Performance: FY2002 VHA Performance Measurement System: Technical Manual. Washington, DC, Veterans Health Administration, 2002 Weissman NW, Allison JJ, Kiefe CI, et al: Achievable benchmarks of care: the ABCs of benchmarking. J Eval Clin Pract 5:269–281, 1999

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C H A P T E R

5

Role of Measurement in Quality Improvement

M

easurement-based quality improvement (QI) is a method of evaluating and making changes to structures and processes of care with the goal of improving health outcomes and reducing adverse events. It can be used to address suboptimal clinical outcomes, reduce variability in the performance of critical tasks, and narrow gaps between evidence-based guidelines and actual practice. Measurement-based QI is generally conducted at the level of the healthcare system where care is delivered. Participants in QI generally include managers, clinicians, and staff providing care. However, such “internal QI” may be influenced by activities of external organizations, such as performance comparisons, mandates, incentives, and oversight. Measurementbased QI is an empirical process, drawing on hypothesis development, testing through intervention, and quantitative assessment to evaluate results. Although it is derived from principles and practices of scientific investigation, measurement-based QI differs from research in that its goal is to produce change through intervention rather than to prove causation between intervention and the outcome. In the manufacturing industry in which measurement-based QI originated, specific models have been formulated and applied, including continuous quality improvement, total quality management, and six-sigma quality (Berwick et al. 1990; Chassin 1998; Kaluzny and Shortell 1999). However, no single model has demonstrated superior effectiveness in healthcare. For this reason, general principles and stages of QI activity are emphasized here rather than a specific model. These principles and steps provide a framework

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for QI that is compatible with diverse approaches to measurement and intervention. This chapter begins with a discussion of measurement-based QI in context of a broader set of approaches to improving quality of care. It then describes general principles and stages of QI activity. Next, research studies are summarized on the use and effectiveness of QI as well as organizational determinants of QI outcomes. The final section emphasizes practical issues in conducting QI in mental healthcare organizations, discussing its compatibility with different types of measures and with interventions of proven effectiveness.

❚ MEASUREMENT-BASED QUALITY IMPROVEMENT IN A BROADER CONTEXT Measurement-based QI is not the only means of improving healthcare. A community mental health clinic, for example, may improve care for a previously underserved population (such as adolescents with substance use disorders) by starting a new program tailored specifically to meet their needs. Nor is measurement-based QI the only way for external organizations to encourage providers to improve quality. The Leapfrog Group, an employer-based coalition, encourages providers to adopt innovations that improve care, using methods that in many cases do not involve measurement. For example, Leapfrog is currently working with hospitals on implementation of computerized medication order-entry systems, which have been shown to reduce the occurrence of serious medication errors (Doolan and Bates 2002). Measurementbased QI can be placed in the context of broader approaches to quality improvement using an Institute of Medicine framework of factors affecting quality at four levels of the healthcare system: 1) the patient’s experience, 2) microsystems, 3) healthcare organizations, and 4) environmental factors (Berwick 2002).

Patient Experience Measurement-based QI can draw on assessments of patients’ experience, such as reports on barriers to care and providers’ interpersonal styles, communication skills, and inclusiveness in clinical decision making. Patients can also provide information on technical processes and clinical outcomes resulting from care. There are many aspects of patients’ experience that are not currently well measured, such as their values, preferences, and cultural context, but that nonetheless need to be addressed. Healthcare organizations can gather insight into these aspects of patients’ experience in other ways, such as

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through participation of patients, families, and community members on boards and advisory panels as well as through community-based needs assessment.

Microsystems A microsystem is “a small team of people, combined with their local information system, a client population, and a defined set of work processes” (Berwick 2002, p. 84) An inpatient psychiatric unit consisting of clinicians, managers, staff, and patients composes a microsystem within a hospital. The defining features of a microsystem make it well suited to measurementbased QI. Its size allows for self-evaluation and collaborative approaches to change. Well-defined work processes lend themselves to measuring conformance to established standards. Some of these work processes are under local control, and thus can be subject to reevaluation and modification. Other processes, however, may be determined by factors external to the microsystem.

Healthcare Organizations Health plans, hospitals, or state mental health systems are composed of component microsystems. A hospital may have multiple inpatient units, while an integrated delivery system may provide care across a number of inpatient, ambulatory, and intermediate service units. Each of these are microsystems capable of conducting measurement-based QI. This method can also be applied to enhance coordination of care across microsystems, for example, between inpatient and outpatient clinicians. However, organizations can also address quality issues via methods not reliant on measurement, such as providing infrastructure, allocating resources, training workers, and developing new clinical services.

Environmental Factors Environmental factors that have been used to promote measurement-based QI include requirements imposed by accreditors, government regulators, payers, and managed care organizations. Many of these groups have also sought to encourage measurement-based QI through training, providing feedback on comparative performance, and more recently by linking financial incentives to good performance. Other external activities unrelated to measurement can also enhance quality, such as professional education, licensure, legislation, and litigation.

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❚ PRINCIPLES OF MEASUREMENT-BASED QUALITY IMPROVEMENT The central precept of measurement-based QI is to view quality of healthcare as comprising all of the processes that occur between a patient and the healthcare system. Outcomes result not only from specific actions of individual clinicians but also from the cumulative impact of all interactions between the patient and clinicians, their technical content and interpersonal qualities, as well as access to services and coordination among them. Additional principles emanate from this fundamental perspective. • Many problems with quality of care result from poorly designed processes rather than individual failures. • Measuring important healthcare processes and outcomes can enhance their visibility and permit assessment of their quality. • Statistical analysis of data resulting from measurement can reveal suboptimal outcomes, variability in basic processes, and gaps between evidencebased recommendations and observed practices. • Quality of care can be improved through diagnosis and intervention to address problems with the processes underlying care. • Efforts to improve quality should address processes and outcomes highly important to patients and other key stakeholders. These should be selected with consideration of the potential benefits of improvement and costs. • Collaboration among participants in the delivery of care—that is, clinicians, managers, staff members, and patients—is critical to understanding problems underlying clinical processes and the success of interventions to address them.

❚ STAGES OF MEASUREMENT-BASED QUALITY IMPROVEMENT Stages of measurement-based QI activity have been formulated in terms of specific models such as FOCUS (find-organize-collect-understand-select), PDCA (plan-do-check-act), and PDSA (plan-do-study-act). Figure 5–1 depicts and defines five stages common to most of these models. The aim identifies the quality problem to be addressed. A primary measure is selected and implemented to determine the magnitude of the problem and monitor change over time. A collaborative process is undertaken to diagnose processes underlying the problem and generate ideas about possible solutions. Based on the resulting insights, a plan is developed that consists of interventions that address hy-

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pothesized causes of the problem. Prioritizing among these interventions requires assessment of the potential impact and resource requirements of each. To intervene is to take action to address one or more causes. Intervention is followed by remeasurement to assess for improvement. Achieving the aim of a QI initiative may require multiple interventions conducted through an iterative process of generating hypotheses, testing them through intervention, and using the results to guide subsequent actions.

Aim

Intervene Plan

Measure Diagnose

Aim:

What problem does one seek to improve?

Measure:

What is the magnitude of the problem? Is it getting better or worse?

Diagnose:

What are the underlying causes of the problem?

Plan:

Which of these causes can be addressed?

Intervene:

What will be done differently that may result in improvement?

FIGURE 5–1. General model for measurement-based quality improvement.

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❚ ADOPTION OF MEASUREMENT-BASED QUALITY IMPROVEMENT Measurement-based QI has been widely adopted by health plans and hospitals, driven by mandates from major payers such as Medicare (Centers for Medicare and Medicaid Services 2000) and accreditation requirements of the National Committee for Quality Assurance (2002) and the Joint Commission on Accreditation of Healthcare Organizations (JCAHO; 2000). JCAHO’s accreditation standards (2003), for example, describe explicit expectations for QI in accredited psychiatric and general hospitals: During the on-site survey, surveyors assess the hospital’s use of its selected measures in its performance improvement activities. A hospital is expected to demonstrate, for each measure, the ability to collect data reliably, conduct credible analyses and interpretation of the data, and initiate appropriate system and process improvements.

Surveys demonstrate high rates of QI adoption, with 90%–98% of hospitals reporting implementation of formal QI programs (Chan et al. 1997; Shortell et al. 1995b). By the late 1990s more than half of Medicaid managed care plans had implemented measurement-based QI (Landon et al. 1998; McManus et al. 2000). Reports indicate that most state mental health authorities and commercial managed care organizations have implemented quality measures for mental health and substance abuse, but the extent of their use in QI activities is unclear (Horgan et al. 2003; Levy Merrick et al. 2002; NASMHPD Research Institute 2002). Although lacking information about the prevalence of use, scores of case reports describe measurement-based QI activities for mental health and substance-related care in a wide range of settings, quality domains, and treatment modalities. These activities employ a broad range of assessment tools, including measures of technical and interpersonal processes and instruments assessing clinical outcomes and patient satisfaction.

❚ EFFECTIVENESS OF MEASUREMENT-BASED QUALITY IMPROVEMENT Controlled trials of measurement-based QI have not found these programs to be consistently effective in healthcare. Systematic reviews of the research literature have found “pockets of improvement” rather than widespread change across healthcare organizations and systems of care (Blumenthal and Kilo 1998; Shortell et al. 1995a, 1995b, 1998). Reports from the early 1990s noted that most QI initiatives focused on administrative processes supporting care (e.g., information transfer between healthcare settings). A decade later, appli-

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cation of QI to clinical processes was more common. However, a 1998 review of 55 studies of the effectiveness of clinical QI showed mixed findings (Shortell et al. 1998). The majority of studies had positive results—QI was associated with improved outcomes—but these findings were more favorable in pre/ post studies than they were in a handful of more rigorous, randomized, controlled trials. Three controlled trials of routine, measurement-based QI initiatives in mental healthcare showed largely negative results, including initiatives to reduce no-show rates among adolescents scheduled for mental health appointments; to improve depression recognition, treatment, and outcomes in primary care; and to increase conformance with Agency for Healthcare Research and Quality clinical practice guidelines for depression ( J. Brown et al. 2000; Goldberg et al. 1998; Pellegrin et al. 1995). These findings raise an interesting question. Why would an improvement model that emphasizes empirical testing and evidence-based practice be implemented throughout the U.S. healthcare system in the absence of convincing evidence of its effectiveness? In part, the answer may lie with QI’s advance having been driven more by business than clinical concerns. Although individual physicians have long championed QI, its widespread adoption coincided with changes to the business of healthcare, including shifts in incentives to favor efficiency as well as mergers and other consolidations that allowed for active management of costs and care. The embrace of QI at high levels of healthcare management was not an empirically driven decision. As Flood and Fennell (1995) have written from the perspective of organizational sociology, “new forms of management are adopted, not because they are known to help the organization, but because they reflect current norms and beliefs about what modern managers do…this type of environment promotes rapid dissemination of strategies believed to be industry standards, regardless of their proven efficacy” (p. 163). QI is not the first major innovation the U.S. healthcare system has adopted in the absence of advance knowledge of its influence. The transition from fee-for-service to fixed-rate reimbursement and utilization management provide two recent examples of innovations for which widespread implementation preceded rigorous evaluation. Other factors may also have contributed to QI’s adoption. To some, QI has compelling face validity, even in the absence of rigorous evidence. Limited findings of effectiveness may reflect the healthcare system’s lack of experience with QI, limited measures, and other manifestations of early development. Furthermore, in an era of expanding expectations for managing costs and care, some managers view QI as a means of promoting organizational development. This perspective may be particularly attractive to organizations whose clinical services had functioned under fee-for-service financing more as individual entrepreneurial units than partners in a shared system of care.

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Quality improvement process

External factors

Diagnose

Selected aims and measures

Measure

Plan Intervene

Quality improvement outcomes

Strategic

Organizational factors Key

Structural

Cultural

Technical

Prior research Research under way

FIGURE 5–2. Factors influencing quality improvement outcomes in healthcare organizations.

Organizational Determinants of Quality Improvement Outcomes Studies of organizational characteristics associated with effective QI can provide insight into paths to better outcomes. Shortell and colleagues developed and tested a model examining strategic, cultural, structural, and technical characteristics of healthcare organizations associated with QI outcomes (Figure 5–2; O’Brien et al. 1995; Shortell et al. 1995b, 2000). The solid-line pathways in Figure 5–2 depict the influence of organizational factors on general outcomes of QI. (The dashed-line pathways depict the fit between organizational characteristics and specific QI objectives; these are discussed later in the chapter.) Table 5–1 summarizes research findings on organizational characteristics and QI outcomes. The goals of the initiatives studied include improved adherence to evidence-based guidelines, reduced costs or utilization, and diffusion of QI methods. Strategic characteristics of healthcare organizations that have been studied for their impact on QI are those that characterize the organization's approach to QI. Superior QI outcomes were observed

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among organizations that identified key processes and outcomes needing improvement (a project-dominant approach) or identified quality as a central priority (a strategy-dominant approach) than among organizations that emphasized cultural features of QI, such as the organization’s vision, values, and staff empowerment. Organizations focusing their activities on emerging opportunities within a planned framework (a “prospector approach”) performed better than those that pursued QI activities without an overall framework or, at the other extreme, were too rigidly organized to allow for adaptation to changing circumstances. Structural features influencing QI outcomes include whether individuals and groups (e.g., councils, committees, and teams) have clearly defined responsibilities for planning and conducting QI. Structural features studied for their influence on QI include characteristics of individuals, teams and committees conducting QI, and the relationships among them. Structural factors associated with better QI outcomes include physician participation within hospital governance, the presence of formalized procedures, the organization’s size, and greater experience with QI. Cultural dimensions of organizations that have been studied are the beliefs, values, and behaviors of the organization’s members with regard to QI. Studies have found that organizations with cultures emphasizing teamwork and innovation achieved better results than more hierarchical or rational cultures. Research has also found that greater commitment of senior managers and physicians to QI increased the likelihood of positive outcomes. Technical features of organizations associated with better QI outcomes include greater staff training in QI, greater analytic expertise, and greater use of computerized information systems. Other research studies have examined associations between organizational characteristics and quality of care (rather than QI). Gittell et al. (2000), for example, studied the concept of “relational coordination” among clinicians and staff in healthcare organizations, which they defined as “coordinating work through frequent, timely, accurate and problem-solving communication, supported by relationships of shared goals, shared knowledge and mutual respect” (p. 807). Their research has demonstrated associations between relational coordination and superior patient functional outcomes. Organizational readiness to change—a construct proposed to predict implementation of evidence-based interventions into clinical practice—was associated with better performance on several indicators of quality of care for substance use disorders (Lehman et al. 2002). Glisson and Hemmelgarn (1998) found characteristics of organizational climate (including low conflict, cooperation, role clarity, and personalization) at children’s service organizations to be associated with better service quality and improved child psychosocial functioning.

Instrument

Setting

QI outcome measure

Studies

Approach to QI (project or strategy-dominant vs. culturedominant)

Site-visit evaluation

Hospitals

Employee and site reviewer assessment of QI outcome

Carman et al. 1996

Approach to QI (prospector vs. analytic, defender, reactor, or opportunistic)

Questionnaire from Hospitals Miles/Snow typology

Degree of QI implementation

Shortell et al. 1995b

Physician participation in hospital governance

AHA/HRET Survey

Hospitals

QI adoption

Weiner et al. 1996

Protocol-specified processes Decentralized decision making

Survey of medical directors

Netherlands agencies

Number of QI projects implemented

Wagner et al. 2001

Longer QI experience Greater volume of QI activity

Scale assessing depth of QI involvement

Hospitals

Employee and site reviewer assessment of QI outcome

Carman et al. 1996

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TABLE 5–1. Characteristics of healthcare organizations associated with better quality improvement (QI) outcomes

Strategic

Greater number of QI teams

–

VA hospitals

Perceived improvement

Lammers et al. 1996

Larger hospital size

–

Hospitals

Degree of QI implementation

Parker et al. 1999

Smaller hospital size

–

Hospitals

Degree of QI implementation, length of stay, charges

Shortell et al. 1995b

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Structural

Characteristic

Instrument

Setting

QI outcome measure

Studies

Hospitals and nursing homes

Degree of QI implementation, patient satisfaction

Berlowitz et al. 2003 Carman et al. 1996 Parker et al. 1999 Shortell et al. 1995b Wakefield et al. 2001

Perceived improvement

Lammers et al. 1996

Degree of QI implementation

Lammers et al. 1996 Parker et al. 1999

Clinician questionnaire Hospitals

Evidence-based AMI treatment

Soumerai et al. 1998

Survey of hospital QI personnel

Degree of QI implementation

Lee et al. 2002

Cultural Zammuto- Krakower Organizational culture (group, developmental vs. hierarchical, Organizational Culture Inventory rational)

Physician commitment to QI

VA Total Quality VA hospitals Improvement Survey

Senior management commitment 10-item questionnaire to QI Participation of clinical opinion leaders

VA hospitals

Role of Measurement in Quality Improvement

TABLE 5–1. Characteristics of healthcare organizations associated with better quality improvement (QI) outcomes (continued)

Technical IS-equipped work units

Hospitals

Note. AHA=American Hospital Association; AMI=acute myocardial infarction; HRET=Health Research and Educational Trust; IS=information systems; VA =Veterans Administration.

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External Determinants of Quality Improvement Outcomes A number of factors external to healthcare organizations potentially influence the outcomes of their QI activities. These include performance goals set by payers or oversight groups, linking financial incentives to performance on quality measures and provision of feedback to provider organizations comparing their performance to their peers (Grol and Grimshaw 2003; Rosenthal et al. 2004). In addition, external groups have sought to enhance provider QI activities by providing staff and leadership training as well as toolkits addressing specific evidence-based practices (Drake et al. 2001). State mental health authorities have led educational efforts in the public sector and in the private sector, organizations such as the Institute for Healthcare Improvement have led collaboratives that provide participating organizations with various combinations of expert guidance, peer experience, assessment instruments, and intervention tools (Montoye et al. 2003). Preliminary evidence on the effectiveness of these collaboratives has been mixed (Baker et al. 2004; Landon et al. 2004; Vargas et al. 2004).

❚ CONDUCTING MEASUREMENT-BASED QUALITY IMPROVEMENT This section draws on QI theory and research, as well as practical experience (Hermann et al. 2000), to describe implementation of measurement-based QI in mental healthcare. The discussion is organized around the five stages illustrated in Figure 5–1: selecting an aim, identifying a measure, diagnosis, planning, and intervention. Approaches to each stage and commonly encountered issues are described.

Selecting an Aim The initial stage of a QI project is to identify and define an aim in terms of a specific quality problem selected for improvement. Although it may seem self-evident, this objective is often not well understood. Illustrative of the misunderstandings are responses from leaders of clinical services within a mental health system. When asked the aim of current QI projects, one nurse manager of an inpatient unit responded, “We are measuring rates of physical restraint use and comparing results to the state average.” In this case, the manager’s understanding of QI is a process of ongoing measurement rather than identifying a problem for improvement. Asked to select a measurable objective for QI activity, staff members at a residential program proposed several measures on which the service had excellent performance, rather than identifying a problem (i.e., a process that the service had performed poorly). In many healthcare organizations, it may run

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counter to instinct and culture to call attention to poor performance. This is why QI advocates often emphasize the need to avoid blaming individuals for poorly performing systems. Another common response came from the director of an outpatient clinic: “We are studying why patients drop out of treatment. We discuss cases each week at our staff meeting. Once we identify reasons for dropping out, we review some charts to examine their prevalence.” In this case, the clinical staff has identified a potential problem (premature termination of treatment), but they have conceptualized QI as a study of the problem rather than a structured, goal-oriented process of improving it. How does an organization go about identifying potential problems that can be addressed? Among the most useful sources of insight are the organization’s employees, who know many of its strengths and weaknesses well. The culture of the organization can influence whether employees will be forthcoming in identifying problems with care. Is assessment of the organization’s performance encouraged? Is there openness to discussing problems? Is such discussion perceived as criticism? Does identifying problems lead to constructive exploration or does it lead to assigning blame to individuals? Problems can also be identified through measurement. Screening measures, such as the Center for Quality Assessment and Improvement in Mental Health (CQAIMH) core measure set described in Chapter 3, can be used to identify areas in which quality may warrant more detailed examination (Hermann et al. 2004). Participation in comparative assessment activities (e.g., report cards or benchmarking collaboratives) provides data that can help identify potential problems. Again, however, the culture of an organization may influence how these data are perceived. If perceived as criticism, measure results can trigger defensive reactions, leading clinicians to focus only on potential inadequacies of the measure, the need for better case-mix adjustment, or the components of the process that are not under their control. On the other hand, if presented as an opportunity to identify aims for providing better care, a more balanced consideration of the results may ensue. Reviews of severe adverse events can also yield insights into processes warranting improvement. Historically, such reviews have focused on circumstances unique to the individual event, but more recently there has been emphasis on identifying routine processes that contributed to the adverse event. For example, JCAHO’s accreditation standards call for hospitals to use a review process known as root cause analysis. Root cause analysis is a process for identifying the basic or causal factors that underlie…a sentinel event. [It] focuses primarily on systems and processes, not individual performance. It progresses from special causes in clinical processes to common causes in organizational processes and identifies potential improvements in processes or systems that would tend to decrease the likelihood of such events in the future. (JCAHO 2005)

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Selection of a QI aim is very much entwined with identifying a measure to monitor progress, because the aim must be operationalizable in the form of a measure. Accordingly, some considerations in selecting an aim parallel the discussion in Chapter 3 of considerations in selecting measures for comparative report cards. The aim should be meaningful to QI participants and other stakeholders: Is it clinically important? Will achieving it improve patient outcomes? Do initial results indicate significant opportunities for improvement? Are processes leading to improvement under the organization’s control? Similarly, an aim must be feasible to measure accurately and reliably. Data sources for the measure must be available and data collection affordable. There is little research on what aims are addressed via QI in healthcare or whether an organization’s choice of aims influences the outcomes of the QI activity. As depicted by the dotted-line pathways added to Shortell’s model in Figure 5–2, CQAIMH’s current research (funded by NIMH grant R34MH074788) hypothesizes that the success of an organization’s QI activities is determined in part by 1) the aims and measures selected and 2) the fit of these aims with strategic, structural, cultural, and technical characteristics of the organization, as well as with characteristics of the external environment. Specific questions derived from this model are presented in the following list. Although research on these questions is in the early stages, organizations embarking on QI activities may want to consider these questions in the course of identifying their QI aims. Strategic Factors • Is achieving the proposed aim for QI critical to the organization’s mission? Designating an aim for QI implies a commitment of sustained attention and resources. In an era of constrained resources and expanding challenges to healthcare organizations, QI activities should not be focused on marginal aims that compete for attention and resources with the organization’s primary objectives. Instead, QI should be employed as a means of working to achieve its primary objectives. We hypothesize that selecting aims regarded as strategically critical to the organization will be associated with better QI outcomes. Structural Factors • Is the aim for QI selected with active participation of clinicians and staff? QI aims may be selected by an organization’s board, senior managers, or through more participatory processes. Because leadership and cooperation from front-line clinical staff are often needed to change a clinical process of care,

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we hypothesize that their active participation in the selection of an aim will be associated with a better outcome for a QI activity. • Is progress toward achieving a QI aim reviewed at regular intervals against explicit quantitative goals and timelines? We hypothesize that regular review and explicit expectations will be associated with better QI outcomes. • Is progress toward achieving a QI aim reviewed at administrative meetings where the organization addresses its primary operational issues or only at separate meetings that focus on QI? Establishment of QI committees has been encouraged as a means of focusing attention on quality problems. However, reviewing progress toward achieving QI aims only at these meetings—and not at meetings where the organization’s primary operational issues are discussed— may contribute to the marginalization of QI objectives. We hypothesize that an integrated approach will be associated with better outcomes. Cultural Factors • Do clinicians and staff regard the QI aim as important to their patients’ outcomes? • If the aim is to improve use of an evidence-based practice, are they knowledgeable about the supporting evidence? Do they agree with the findings? • Do they believe that the organization’s performance in this area represents a significant problem with quality? • Do they believe that the measure provides an adequate indicator of the magnitude of the underlying problem? We hypothesize that each of these factors will be associated with better QI outcomes. Technical Factors • Do clinicians and staff have training in QI? • Does the healthcare organization provide resources for data collection and analysis? • Are the analytic resources available to the organization adequate for the type of measures used for QI? For example, risk adjustment is typically needed to compare performance based on measurement of outcomes. If an organization has elected to use outcome measures, is adequate statistical expertise available to the organization to risk adjusting their results? External Factors • Is the success of QI influenced by the actions of external organizations, such as mandated measures, periodic reviews of progress, incentives or sanctions based on results, or the provision of tools or training?

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Identifying a Measure The primary role of measurement in QI is to assess the magnitude of the problem being addressed and to evaluate progress in addressing the problem over time. However, measurement contributes to QI in other ways as well. The need for an aim be operationalized into a measure can help a workgroup to achieve a common understanding and specificity regarding their aim. For example, a preliminary goal to “improve access to care” can mean different things to different participants. Through agreement on a specific measure (e.g., the number of days between a request for outpatient services and the initial visit) the group can come to a common understanding of their goal. Furthermore, serial assessment with that measure can help maintain the group’s focus on their objective and act as a restraint against the tendency to lose focus or experience “mission creep” over time. In addition to a primary measure that reflects the project’s aim, QI initiatives often make use of secondary measures that inform hypotheses for intervention. For example, an inpatient workgroup seeking to lower the service’s high readmission rate learned through additional measures (drawn from medical records) that a disproportionate number of readmitted patients had eloped during their initial hospitalization while withdrawing from alcohol dependence. This insight led to a change in off-unit privileges for patients experiencing withdrawal and a reduction of readmissions among this subgroup. Secondary measures can be particularly useful for evaluating the progress of efforts to address multifactorial problems. For example, suppose a workgroup seeks to improve adherence to antidepressant medication among depressed outpatients. Through a combination of literature review and local evaluation, its members conclude that factors contributing to poor adherence include inadequate patient knowledge about antidepressants, variability in clinicians’ educational efforts, and inconsistent follow-up during the first few weeks of treatment. They develop and implement measures of each of these processes (knowledge, education, and follow-up), confirming that there are opportunities for improvement in each area. They implement interventions that target each of these processes and remeasure them at subsequent intervals to evaluate their progress over time. Meanwhile, they also use a primary measure of medication adherence to assess the overall effectiveness of their efforts. Graphical presentation of quality measurement data provides tools for evaluating QI progress and communicating results. Run charts showing changes in results over time are among the most common forms of presentation. Figure 5–3 depicts results from a Pennsylvania Office of Mental Health and Substance Abuse Services (2001) initiative to decrease the use of physical restraints and seclusion in state psychiatric hospitals. This run chart also il-

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0.08 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0 1990

1991

1992

1993

1994 Restraint

1995

1996

1997

1998

1999

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Seclusion

FIGURE 5–3. Hours per inpatient day of physical restraint and seclusion use in Pennsylvania state psychiatric hospitals, 1990– 2000. Source. Adapted from Pennsylvania Office of Mental Health and Substance Abuse Services, Division of Hospital Operations: “Pennsylvania State Hospital System Actual Hours of Mechanical Restraint and Seclusion by Calendar Year; 2001.” Harrisburg, PA, Pennsylvania Office of Mental Health and Substance Abuse Services, 2001. Used with permission.

lustrates some of the considerations in deciding how to specify a measure for QI. At first glance, the measure of “hours per inpatient day of physical restraint” seems needlessly cumbersome. The results—for example, 0.015 hours of restraints per inpatient day in 1998—lack intuitive meaning. A simpler measure such as “total hours of restraint use” or, even more simply, “the number of patients restrained annually,” would be much clearer, particularly to external audiences such as consumers or policy makers. However, the Pennsylvania initiative coincided with a dramatic decrease in the use of inpatient psychiatric care. During the 1990s, the number of patients hospitalized in Pennsylvania state hospitals dropped 56%, while the total number of inpatient days per year declined 67%. Fewer hospital patients and shorter hospitalizations would have resulted in declines in the simpler measures regardless of whether restraint practices had changed, while the more complex measure used in Figure 5–3 adjusts for these factors. In addition to depicting an organization’s performance over time, run charts can compare the organization’s performance with average performance among peer institutions (not shown). Confidence intervals can be used to show whether these differences are statistically significant. Statistical methods can also distinguish between random variation in performance and

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significant shifts in a process during an intervention period. Process control charts are used to provide early detection of when a previously stabilized clinical process becomes less well controlled. Control limits, represented by parallel lines above and below the plotted process or outcome, establish thresholds for determining uncontrolled variation (Pfadt and Wheeler 1995). Run charts may also include a horizontal bar indicating an organization’s goal for performance on the measure (Figure 5–4). As discussed in Chapter 4, this goal may reflect an external standard, a statistical benchmark, or an internal target (e.g., 10% improvement over last year’s performance). Quality measurement can provide a foundation for organizations to manage QI activities. The process of selecting a measure can stimulate dialogue between senior managers and front-line staff about what goals both groups consider to be meaningful. Routine review of measure results between managers and clinical staff provides an opportunity to discuss insights gained, interventions applied, obstacles encountered, and needs for resources or support. Establishing a numerical goal for QI to be reached within a defined period of time can underscore the need for a focus on improvement (rather than study) and can foster discussion of what is achievable. Instrument panels, run charts depicting the progress of several measures toward their respective goals, provide managers with a high-level view of multiple QI activities, allowing them to monitor progress and identify where further attention may be needed. The component run charts may display QI initiatives conducted in different operational units within the organization (e.g., several inpatient services within a hospital). Alternatively, they may depict progress in different dimensions of performance that reflect the diverse priorities of the organization. Several models for using performance measurement in managing organizations advocate that senior managers adopt instrument panels that reflect each of the organization’s major goals. This approach is recommended to guard against focusing on one area at the expense of others. Kaplan and Norton’s (1992) Balanced Scorecard model calls for adopting measures in four dimensions of organizational activity: internal processes, customer satisfaction, cost, and outcomes. Applying a similar approach specifically to healthcare, Nelson et al.’s (1996) Clinical Value Compass addresses four “compass points”: functional status, satisfaction/perceived benefit, costs, and clinical outcomes. Figure 4-5 illustrates CQAIMH’s balanced scorecard approach to mental healthcare, summarizing progress on measures of access, quality, satisfaction, and cost/utilization. There is some debate in healthcare about whether financial aims should be integrated into QI activities. In other industries, promotion of efficiency and elimination of wasteful processes are fundamental to QI, freeing up resources for use in more productive areas. Addressing financial aims as part of QI also promotes the concept of value—the product of quality and cost—and may pro-

Access : % indicating easy to reach intake by phone 100%

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FIGURE 5–4. CQAIMH’s balanced scorecard approach to quality measurement in mental healthcare.

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vide insights into trade-offs between these component factors. In healthcare, efforts to integrate measures of cost, utilization, and efficiency into QI have been more tentative, perhaps to avoid exacerbating lingering suspicions among some clinicians that quality management is principally a euphemism for cost control.

Diagnosis Having identified a problem to address and adopted a measure of its magnitude, participants in a QI initiative next turn to a diagnostic process of understanding the processes underlying the quality problem. Further data collection through surveys, chart review, and other types of measurement can provide additional information to inform the diagnostic process. However, workgroups may want to maintain a middle ground between two extremes. In addressing a complex problem, one does not want to jump too quickly to a solution before the process is well understood and alternative approaches to intervention can be weighed. On the other hand, groups that seek definitive answers regarding all causes of complex problems may fail to progress to intervention. The goal at this stage is to establish hypotheses about some likely causes, particularly remediable causes, that can be tested through intervention and re-measurement. A multifactorial problem will lead to a long list of potential causes that need to be prioritized in terms of their potential to lead to improvement. Facilitating this inquiry is an arsenal of tools that have been developed to help groups generate, discuss, and prioritize ideas and conduct analyses of complex topics. These techniques are intended to harness the strengths of groups—the collective energy of participants, the diversity of perspectives, and potential for synergies—while avoiding some of the pitfalls such as lack of focus or dominance by a few participants with strongly expressed views. One approach is the nominal group process, a structured, multistage approach for generating and rating ideas regarding complex topics. An initial brainstorming stage proceeds systematically, with each participant contributing in turn his or her suggestion of a factor contributing to the problem. Dialogue at this stage is limited to clarification of each idea rather than debate in order to stimulate as many ideas as possible from all participants. Each proposal is recorded, often using large wall charts or posted slips of paper, which allows the group to scan the accumulating contributions. The next stage, affinity grouping and consolidation, involves the sorting of these ideas into clusters of related items that can be summarized under a single heading. Discussion of the strengths and limitations of these summary ideas then proceeds, providing further insights into their potential utility. Rank ordering reverts to a structured process to ensure input from all participants. Each group member individually rates the ideas based on what they perceive as most important. The items are then ranked by their average

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score across participants. Decision matrices can be useful when more than one consideration is crucial to determining an item’s ranking. For example, issues contributing to the rank of a potential QI objective include the importance of the process to patient care, the degree to which current performance is perceived to be a problem, and the organization’s ability to influence the process. Asking participants to rate proposed objectives on each of the dimensions encourages them to consider each in their judgments. Summative processes and cut-offs can be established to consolidate results into a single rank-ordered list (Navy Medical Quality Institute 2003). Diagramming processes underlying quality problems can inform a workgroup’s diagnosis. Process-flow diagrams provide visual depiction of the problem that can contribute to a shared understanding among participants regarding contributing factors. This depiction can initially reflect the process in terms of how it actually functions and then can be modified to consider how it might function better. Cause and effect diagrams are more conceptual than flowcharts, drawn to represent relationships between a quality problem and proposed causes. These are sometimes called “fishbone diagrams” because the diagram places a problem at the head of a horizontal spine, with clusters of potential causes represented by fishbone-like radiations. Pareto charts depict the frequency of processes contributing to a problem in the form of a bar chart, with each bar representing the prevalence of a process. Although causes of some quality problems may be idiosyncratic to a particular organization, many problems are observed repeatedly throughout the healthcare system. QI participants need not address these problems de novo but should conduct literature reviews to learn from past work. For example, 20 years of research on outpatient care for depression has identified frequently observed barriers to quality care and optimal outcomes. Table 5–2 summarizes these barriers by the level of the healthcare system where they occur, using the Institute of Medicine framework of patients, microsystems, organizations, and the external environment (Katon 2003). These findings provide a broad and deep foundation for QI activities that aim to improve primary care treatment for depression. An important discipline for QI participants to acquire is to focus attention on causes of quality problems they can address rather than those they cannot. Clinicians who feel unfairly criticized by poor performance on a quality measure may respond by emphasizing the many factors contributing to the problem that are beyond their control rather than the few that they may be able to address. Improving quality of care, however, requires individuals at each level of the healthcare system to take responsibility for those factors that are under their control. Applying the framework from Table 5–2 helps to identify the factors contributing to poor depression care that can be addressed at each level of the healthcare system. A microsystem comprising the mental health

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TABLE 5–2. Factors contributing to poor quality outpatient care for depression Patient-level barriers • • • • •

Lack of knowledge about depression and treatment options Reluctance to discuss mental illness or symptoms secondary to stigma Often strong preferences for treatments Depression as personal and family issue Preference for depression care within primary care setting

Microsystem barriers • • • • • •

Infrequent visits Total reliance on physician Lack of close follow-up Lack of time to educate and activate Lack of monitoring of adherence and outcomes Lack of time to support behavioral changes (i.e., exercise, problem-solving, interpersonal behaviors)

Organizational barriers • • • •

Lack of electronic technology Quality improvement often a secondary priority Failure to align incentives for clinical systems with care improvement Lack of leadership development in quality improvement methods

Insurance, accreditation, legal issues • • • • •

Insurance payments do not provide incentives for delivery of high-quality care Employers base choice of plans primarily on cost Accreditation agencies are not requiring measurement of evidence-based practices Lack of insurance parity for mental healthcare Behavioral carve-outs restrict integration of care

Source. Reprinted from Katon WJ: “The Institute of Medicine ‘Chasm’ Report: Implications for Depression Collaborative Care Models.” General Hospital Psychiatry 25:222–229, 2003. Used with permission.

clinicians working at an outpatient clinic may not be able to influence the number of visits allowed by a patient’s insurer or acquire new computers with electronic medical record capability—these are issues that must be addressed at the organization or environmental level. However, the clinicians can influence the assessment and treatment patients receive, the availability of educational materials, and the role of each clinical discipline in the treatment process. Groups at different levels of the health system can sometimes partner to improve care. For example, health plans have worked with clinicians to provide timely, patient-specific data on medication adherence, symptoms, and functioning, which clinicians have used in managing their patients’ care (J. Brown et al. 2000; G.S. Brown et al. 2004; Katon et al. 1995).

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Planning and Intervention Planning for improvment begins with generating ideas about possible remedies based on the results of the diagnostic process. Many of the same techniques applied during the diagnostic stage, such as nominal group process, can be used to identify potential solutions. As described earlier, brainstorming ensures that a wide range of possibilities is considered. The resulting list of potential interventions can then be winnowed down by evaluating the following factors: • What is the likelihood that the intervention will result in improvement? • What is the likely magnitude of improvement? • What are the financial and opportunity costs of the intervention relative to its expected benefits? • Are there additional costs, such as disrupting existing processes or other potential adverse consequences? After an initial intervention is selected, further planning is needed to flesh out the precise actions that will be taken. For large groups addressing complex problems, subgroup-planning methods can be useful to address multiple component tasks. The QI group breaks out into smaller subgroups, each charged with defining the actions, resources, and timelines necessary to achieve their assigned objective (Nicholas et al. 2001). This method provides for broad participation in the implementation process while assigning to group leaders the role of prioritizing, coordinating, and supporting subgroup activities. Whenever possible, interventions should be pilot-tested and their effectiveness should be evaluated prior to widespread implementation. The cyclical nature of QI reflects the usefulness of an iterative approach. Cycles of intervention and reassessment allow for hypotheses to be tested. Interventions that prove effective can be retained; those that do not can be modified or discarded. Improvement is often incremental and change can be cumulative over numerous cycles. The relationship between improvement and any one intervention may not always be clear. Unlike a research study, QI will typically lack a control group, statistical power, or other characteristics of experimental design that allow for causality between intervention and improvement to be determined. Where do ideas for QI interventions come from? Useful interventions can be suggested by measure results. An example provided earlier describes one hospital’s finding that elevated readmission rates stemmed, in part, from patients experiencing withdrawal who eloped during detoxification. This observation led to changes in protocols for treatment, privileges, and escort services provided during the at-risk period. Collectively, these changes led to

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fewer readmissions. Frontline clinicians and staff are critical sources of ideas for interventions. Structured approaches such as a nominal group process provide a forum for broad input of ideas from diverse perspectives. Peer organizations that have achieved high levels of performance on the same problem may be sources of “best practices,” process innovations leading to superior performance. Thus an inpatient team seeking to reduce physical restraint use may benefit from site visits to hospitals that have already achieved significant reductions in use. Early models of industrial QI emphasized a relatively narrow approach to intervention. As more experience is gained applying measurement-based QI to healthcare, it is becoming clear that QI should be viewed as a framework for organizational change compatible with diverse approaches to intervention. Several modalities for improving care have been shown through controlled trials to be effective; these are part of the armamentarium available to QI teams. Table 5–3 describes these modalities and summarizes evidence of their effectiveness. The nature of the modalities in the table varies. Some of these approaches, such as audit and feedback, continuing medical education, and academic detailing, have fairly well-defined principles and protocols. Others are heterogeneous groups of strategies. For example, practice guideline implementation can involve a diverse array of approaches, each intended to reduce variations and improve conformance to guideline recommended practices. Use of a local consensus process or local opinion leaders are not interventions themselves but are processes that have been shown to enhance the effectiveness of QI interventions. Studies of multimodal interventions have demonstrated improvements in a number of mental health processes and outcomes. These studies provide a rich array of different types of interventions may be of use to teams conducting measurement-based QI. Table 5–4 describes several interventions that illustrate diverse processes of care: treatment, assessment, continuity, safety, and access. Approaches to intervention used in these studies range from technological (drug utilization review) to education and training (Partners in Care) to regulatory (Pennsylvania’s model for restraint reduction). Many empirically tested interventions have focused on depression because of its prevalence, morbidity, and known problems with quality. Although these interventions have common goals—improvement in treatment, adherence, and outcomes—they incorporate diverse approaches: teaching patients cognitive-behavioral techniques; training clinicians in evidence-based therapies; specialty collaboration, consultation, or referral; and encouraging adherence through pharmacist counseling, case management by nurses, or telephonebased counselors. That many of these programs have shown evidence of effectiveness suggest there are multiple pathways to achieving successful results. Accordingly, QI teams needing to select among alternative approaches

Intervention type

Description

Effectiveness

Practice guideline implementation

“Practice guidelines are systematically Reviews of more than 50 studies concluded that simple dissemination does not improve care, but effectiveness has been shown when guidelines were developed statements to implemented through active strategies such as academic detailing and assist...decisions about reminders (Davis and Taylor-Vaisey 1997; Grimshaw and Russell 1993). appropriate...care under specific circumstances.” (Institute of Medicine 1990, p. 8)

Local consensus process

Inclusion of local clinicians in the process of developing or modifying practice guidelines (Grimshaw and Russell 1993)

Local opinion leaders

Eight randomized controlled trials (RCTs) examined the influence of local Use of “educationally influential” opinion leaders on clinical practice through educational meetings, workshops, clinicians identified through surveys and community outreach activities. Although most of the studies found at least of peers to disseminate information some improvement in experimental groups, only two provided strong from guidelines and other sources to evidence of clinically important effects (Thomson O’Brien et al. 2000b). colleagues (Oxman et al. 1995).

Audit and feedback

More than 80 studies of audit and feedback have shown mixed results in Systematic measurement of clinical improving clinical practices, typically small-to-moderate positive effects. practices over time, with results Absolute change in improvement was greater when baseline performance rates provided to clinicians, often were low (Grol and Grimshaw 2003; Jamtvedt et al. 2003) comparing individual to peer performance (Grimshaw et al. 2001).

Compared with guidelines developed by national organizations, studies suggest that guidelines developed with participation of local clinicians were associated with better implementation and conformance (Grimshaw and Russell 1993; Nuffield Institute for Health 1994).

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TABLE 5–3. Effectiveness of modalities for improving quality of care

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Academic detailing

Also known as educational outreach, academic detailing has been shown to be Educators provide clinicians with effective in several clinical trials when used independently and when information intended to change combined with other modalities. Effective applications include reducing clinical practice. Intervention is benzodiazepine use in primary care practices and antipsychotic drug use in typically preceded by study of clinician practice patterns, knowledge nursing homes. Features associated with effectiveness included use of objective sources of information, highlighting essential messages, and reinforcing and beliefs (Grimshaw et al. 2001; improved practices in follow-up visits (Oxman et al. 1995; Thomson O’Brien Soumerai and Avorn 1990). et al. 2000a).

Continuing medical education

Studies have found that passive, didactic approaches and dissemination of Educational activities aimed at improving clinician knowledge, skills, educational materials were not associated with improved clinician and performance (American Medical performance, whereas small-group interactive approaches moderately improved practice (Davis et al. 1995, 1999; Thomson O’Brien et al. 2001). Association 2003).

Reminders

“Any intervention (manual or computerized) that prompts the healthcare provider to perform a clinical action” (Oxman et al. 1995, p. 1424)

Disease management

Most incorporate multiple interventions including provider feedback, education Interventions to manage or prevent chronic conditions through systematic of patients and providers, and reminders. A majority of published studies show significant improvements in provider adherence to practice guidelines approaches that include use of and patient disease control (Badamgarav et al. 2003; Weingarten et al. 2002) evidence-based guidelines (Ellrodt et al. 1997).

Effectiveness

Studies have found reminders effective in improving clinical practice, particularly for preventive practices such as screening and vaccination. Research also supports effectiveness of computerized physician order-entry systems in reducing medication errors and adverse drug events, and clinical decision support systems in improving a variety of practices (Grimshaw et al. 2001; Kaplan 2001; Kaushal et al. 2003; Walton et al. 2001).

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TABLE 5–3. Effectiveness of modalities for improving quality of care (continued)

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should base their decision, in part, on an assessment of their resources and capabilities. For example, in an outpatient clinic seeking to improve depression care, what type of staff might be available within the organization to perform case management? Is there access to pharmacy data for monitoring patient adherence to medications? Are resources available to train clinicians in evidence-based psychotherapy? Multimodal interventions that require significant resource investment and system redesign have seen limited adoption despite their proven effectiveness. In some cases, large-scale dissemination projects have been undertaken to demonstrate generalizability. Efforts are under way to examine whether financial incentives and regulatory, policy, and competitive forces can be aligned to encourage adoption. It is not clear how these top-down approaches to improving care will relate to bottom-up efforts such as local measurementbased QI. Certainly there are potential synergies between approaches. Participation in measurement-based QI may increase awareness among managers and clinicians of quality deficits within healthcare organizations and encourage them to consider adopting models requiring more extensive investment and redesign. Conversely, individual components of multimodal interventions could be adopted incrementally in the course of local QI initiatives.

❚ CONCLUSION A healthcare organization’s implementation of measurement-based QI is an evolutionary process (Shortell et al. 1995a; Hermann et al. 2000). Early stages of development tend to focus on structural issues such as development of effective QI teams and implementation of a reporting process that encourages accountability. Cultural issues that arise include the need to develop consensus around organizational goals and the role of QI in achieving them. Technical issues requiring early attention include staff training in QI methods, identification of data sources available for quality measurement, establishing procedures for data analysis, and dissemination of results. Perspectives differ regarding what types of quality measures are most useful early in the development of a QI program. Some organizations have chosen to use process measures initially because they tend to require fewer resources to implement and less analytic sophistication to interpret results (Hermann et al. 2000). Other organizations have employed clinical outcome measures from the outset with the expectation that they would be more likely to engage clinicians (Smith et al. 1997). During the intermediate stages of developing a QI program, cultural factors tend to dominate, including the need to overcome “middle management resistance, an unwillingness to communicate openly and a…tendency to per-

TABLE 5–4. Selected multimodal interventions to improve the quality of mental healthcare

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Intervention/Population

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Components

Outcomes

Collaborative management: Primary care patients with depression (Katon et al. 1995; Von Korff et al. 1997)a

Patient education on depression, treatment and expectations PCP education on treating depression Increased intensity and frequency of visits over first 4–6 weeks Increased consultation between psychiatrists and PCP Monitoring pharmacy data for adherence

Increased patient satisfaction Increased antidepressant adherence Improved depressive symptoms Improved cost effectiveness

Partners in Care: Primary care patients with depression (Wells et al. 2000)a

Patient education on depression and treatment Joint decision-making between clinicians and patients Clinician education on medication treatments and CBT Reduced co-payments for therapy Follow-up by nurses to support medication adherence

Increased likelihood of appropriate medication dosage at 6 months Increased likelihood of continued medication or therapy at 6 months Increased likelihood of seeing a mental health specialist Decreased likelihood of depressive disorder at 6 and 12 months Increased proportion employed at 12 months

Treatment

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Intervention/Population

Components

Outcomes

Program for relapse prevention: Patients with schizophrenia in a community support program (Herz et al. 2000)a

Patient and family education on recognition of prodrome and relapse Monitoring for prodromal symptoms by clinicians and families Crisis intervention after detection Supportive psychotherapy to enhance patient coping skills Group psychoeducation groups for family members

Earlier detection of prodromal episodes Decreased rate of relapse Decreased rate of rehospitalization

Assessment Screening for problem drinking: VA Patient administration of Alcohol Use Disorders internal medicine outpatients (Conigliaro Identification Test (AUDIT) prior to visit et al. 1998)b Physician notification of AUDIT results prior to visit

Decrease in reported alcohol consumption

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TABLE 5–4. Selected multimodal interventions to improve the quality of mental healthcare (continued)

Continuity Aftercare compliance following psychiatric- Fixed appointment time for aftercare emergency visit: Patients evaluated at a Motivational counseling general hospital emergency department Participation of aftercare clinician in treatment (Spooren et al. 1998)a planning Education and treatment planning with family

Greater initial and continued attendance in outpatient psychiatric care

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TABLE 5–4. Selected multimodal interventions to improve the quality of mental healthcare (continued)

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Components

Outcomes

Safety 95% decrease statewide in restraint hours per Revised procedures on R&S ordering, duration, inpatient day observation, and discontinuation criteria Informed patients and families of hospital policies 98% decrease statewide in seclusion hours per inpatient day on R&S use Staff training on identifying escalating behaviors, assessing risk, assisting patients to maintain control, and coping with emotions Debriefing after R&S focused on averting future use Measurement-based QI techniques

Computerized drug utilization review education and intervention program: National sample of elderly patients (Monane et al. 1998)b

56% of alerts resulted in pharmacist contact with Automated screening of prescriptions with alert sent to pharmacist when drug is contraindicated physician 24% resulted in change to drug regimen Pharmacist-initiated telephone outreach to physician Explanatory letter sent to patient and physician if prescription is changed

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Pennsylvania model to reduce R&S use: State psychiatric hospital inpatients (Curie 2001; Pennsylvania Office of Mental Health and Substance Abuse Services 2001)b

Intervention/Population

Components

Outcomes

Adjusted appointment supply to patient needs Reduced backlog Reduced appointment types Contingency plans for high demand Used email and multifocal visits to reduce number of visits Transferred some duties from physicians to nonphysician staff

Decreased waiting time for nonurgent visits from 35 to 3 days Increased patient satisfaction from 72nd to 85th percentile Increased proportion of patient visits with his or her own PCP from 40% to 75%

Access Advanced access: Primary care patients (Murray et al. 2003)b

Note. CBT=cognitive-behavioral therapy; PCP=primary care physician; QI=quality improvement; R&S =restraint and seclusion; VA=Veterans Administration. aRandomized controlled trial bDescriptive cohort study

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TABLE 5–4. Selected multimodal interventions to improve the quality of mental healthcare (continued)

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fectionism” in measurement (Shortell et al. 1995a, p. 19). Another key task during the intermediate stage is to integrate QI into the organization’s clinical and operational management. Without integration, QI tends to be regarded as an additional activity of secondary importance rather than a means of achieving the organization’s primary goals. During the intermediate stage of development, one would expect an organization to begin to achieve measurable improvement in some areas of performance. Later stages of QI development include expansion of activities to address a broader range of conditions, domains of quality, and levels of care. Shortell et al. (1995a, p. 19) emphasize the importance of “aligning performance appraisal and reward systems and budgeting and planning” with QI activities, an appropriate task for this period. The organization should also step back and assess whether its QI objectives are aligned with its primary strategic goals. For instance, do current QI activities address critical external mandates and internal priorities? If the organization has heretofore focused on process measures, they might consider broadening their scope to include clinical outcomes. If the focus has been on technical processes, it might be broadened to include interpersonal processes. Finally, in an advanced developmental stage, one would expect that the mechanical steps of conducting QI would be coalescing into an ongoing organizational capacity to learn and change.

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Grimshaw JM, Shirran L, Thomas R, et al: Changing provider behavior: an overview of systematic reviews of interventions. Med Care 39 (suppl 2):II2–II45, 2001 Grol R, Grimshaw J: From best evidence to best practice: effective implementation of change in patients’ care. Lancet 362:1225–1230, 2003 Hermann R, Regner J, Yang D, et al: Developing a quality management system for behavioral healthcare: the Cambridge Health Alliance experience. Harv Rev Psychiatry 8:251–260, 2000 Hermann RC, Palmer RH, Leff HS, et al: Achieving consensus across diverse stakeholders on quality measures for mental healthcare. Med Care 42(12):1246–1253, 2004 Herz MI, Lamberti JS, Mintz J, et al: A program for relapse prevention in schizophrenia: a controlled study. Arch Gen Psychiatry 57:277–283, 2000 Horgan CM, Merrick EL, Garnick DW, et al: The Provision of Mental Health Services in Managed Care Organizations. Rockville, MD, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, 2003 Institute of Medicine: Clinical Practice Guidelines: Directions for a New Program. Washington, DC, Institute of Medicine, 1990 Jamtvedt G, Young JM, Kristoffersen DT, et al: Audit and feedback: effects on professional practice and health care outcomes. Cochrane Database Syst Rev (3):CD000259, 2003 Joint Commission on Accreditation of Healthcare Organizations (JCAHO): Comprehensive Accreditation Manual for Behavioral Health Care, 2000 Supplement. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2000 Joint Commission on Accreditation of Healthcare Organizations (JCAHO): Facts about ORYX for hospitals. Available at http://www.jcaho.org/accredited+organizations/hospitals/oryx/oryx+facts.htm. Accessed June 25, 2003. Joint Commission on Accreditation of Healthcare Organizations (JCAHO): Sentinal event policy and procedures. Available at: http://www.jcaho.com/accredited+organizations/sentinel+event/se_pp.htm. Accessed July 7, 2005. Kaluzny AD, Shortell SM (eds): Health Care Management: Organization Design and Behavior. Albany, NY, Delmar Learning, 1999 Kaplan B: Evaluating informatics applications: clinical decision support systems literature review. Int J Med Inf 64:15–37, 2001 Kaplan R, Norton D: The balanced scorecard: measures that drive performance. Harvard Business Review (Jan–Feb):71–79, 1992 Katon W: The Institute of Medicine Chasm report: implications for depression collaborative care models. Gen Hosp Psychiatry 25:222–229, 2003 Katon W, Von Korff M, Lin E, et al: Collaborative management to achieve treatment guidelines: impact on depression in primary care. JAMA 273:1026–1031, 1995 Kaushal R, Shojania KG, Bates DW: Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch Intern Med 163:1409–1416, 2003 Lammers JC, Creiten S, Gilman S, et al: Total quality management in hospitals: the contributions of commitment, quality councils, teams, budgets, and training to perceived improvement at Veterans Health Administration hospitals. Med Care 34:463–478, 1996

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Landon BE, Tobias C, Epstein AM: Quality management by state Medicaid agencies converting to managed care: plans and current practice. JAMA 279:211–216, 1998 Landon BE, Wilson IB, McInnes K, et al: Effects of a quality improvement collaborative on the outcome of care of patients with HIV infection: the EQHIV study. Ann Intern Med 140:887–896, 2004 Lee S, Choi K, Kang H, et al: Assessing the factors influencing continuous quality improvement implementation: experience in Korean hospitals. Int J Qual Health Care 14:383–391, 2002 Lehman WEK, Greener JM, Simpson DD: Assessing organizational readiness for change. J Subst Abuse Treat 22:197–209, 2002 Levy Merrick E, Garnick DW, Horgan C, et al: Quality measurement and accountability for substance abuse and mental health services in managed care organizations. Med Care 40:1238–1248, 2002 McManus M, Graham R, Fox H, et al: How far have state Medicaid agencies advanced in performance measurement for children? Arch Pediatr Adolesc Med 154:665–671, 2000 Monane M, Matthias DM, Nagle BA, et al: Improving prescribing patterns for the elderly through an online drug utilization review intervention: a system linking the physician, pharmacist, and computer. JAMA 280:1249–1252, 1998 Montoye CK, Mehta RH, Baker PL, et al: A rapid-cycle collaborative model to promote guidelines for acute myocardial infarction. Jt Comm J Qual Saf 29:468–478, 2003 Murray M, Bodenheimer T, Rittenhouse D, et al: Improving timely access to primary care: case studies of the advanced access model. JAMA 289:1042–1046, 2003 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: Implementation of the NASMH PD Framework of Mental Health Performance Measures by States to Measure Community Performance: 2001. Alexandria, VA, NASMHPD Research Institute, 2002 National Committee for Quality Assurance: Standards and Guidelines for the Accreditation of MBHOs: Effective July 1, 2003. Washington, DC, National Committee for Quality Assurance, 2002 Navy Medical Quality Institute: Group Process Techniques. Bethesda, MD, Naval School of Health Sciences, 2003 Nelson E, Mohr J, Batalden P, et al: Improving health care, part 1: the clinical value compass. Jt Comm J Qual Improv 22:243–258, 1996 Nicholas W, Farley DO, Vaiana ME, et al: Putting Practice Guidelines to Work in the Department of Defense Medical System: A Guide for Action. Santa Monica, CA, RAND Corporation, 2001 Nuffield Institute for Health: Implementing clinical guidelines: can guidelines be used to improve clinical practice? Eff Health Care 1:1–12, 1994 O’Brien JL, Shortell SM, Hughes EFX, et al: An integrative model for organizationwide quality improvement: lessons from the field. Qual Manag Health Care 3:19–30, 1995 Oxman A, Thomson M, Davis D, et al: No magic bullets: a systematic review of 102 trials of interventions to improve professional practice. CMAJ 153:1423–1431, 1995 Parker VA, Wubbenhorst WH, Young GJ, et al: Implementing quality improvement in hospitals: the role of leadership and culture. Am J Med Qual 14:64–69, 1999

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Pellegrin KL, Carek D, Edwards J: Use of experimental and quasi-experimental methods for data-based decisions in QI. Jt Comm J Qual Improv 21:683–691, 1995 Pennsylvania Office of Mental Health and Substance Abuse Services: Pennsylvania State Hospital System Actual Hours of Mechanical Restraint and Seclusion by Calendar Year. Harrisburg, PA, Pennsylvania Office of Mental Health and Substance Abuse Services, 2001 Pfadt A, Wheeler D: Using statistical process control to make data-based clinical decisions. J Appl Behav Anal 28:349–370, 1995 Rosenthal MB, Fernandopulle R, Song HR, et al: Paying for quality: providers’ incentives for quality improvement. Health Affairs 23:127–141, 2004 Shortell SM, Levin DZ, O’Brien JL, et al: Assessing the evidence of CQI: is the glass half empty or half full? Hosp Health Serv Admin 40:4–24, 1995a Shortell SM, O’Brien JL, Carman JM, et al: Assessing the impact of Continuous Quality Improvement/Total Quality Management: concept versus implementation. Health Serv Res 30:377–401, 1995b Shortell SM, Benett CL, Byck GR: Assessing the impact of continuous quality improvement on clinical practice: what will it take to accelerate progress. Milbank Q 76:593–624, 1998 Shortell SM, Jones RH, Rademaker AW, et al: Assessing the impact of total quality management and organizational culture on multiple outcomes of care for coronary bypass graft surgery patients. Med Care 38:207–217, 2000 Smith GR, Fischer EP, Nordquist CR, et al: Implementing outcomes management systems in mental health settings. Psychiatr Services 48:364–368, 1997 Soumerai S, Avorn J: Principles of educational outreach (“academic detailing”) to improve clinical decision making. JAMA 263:549–556, 1990 Soumerai SB, McLaughlin TJ, Gurwitz JH, et al: Effect of local medical opinion leaders on quality of care for acute myocardial infarction: a randomized controlled trial. JAMA 279:1358–1363, 1998 Spooren D, Van Heeringen C, Jannes C: Strategies to increase compliance with outpatient aftercare among patients referred to a psychiatric emergency department: a multi-center controlled intervention study. Psychol Med 28:949–956, 1998 Thomson O’Brien MA, Oxman AD, Davis DA, et al: Educational outreach visits: effects on professional practice and health care outcomes. Cochrane Database Syst Rev (2):CD000409, 2000a Thomson O’Brien MA, Oxman AD, Haynes RB, et al: Local opinion leaders: effects on professional practice and health care outcomes. Cochrane Database Syst Rev (2):CD000125, 2000b Thomson O’Brien MA, Freemantle N, Oxman AD, et al: Continuing education meetings and workshops: effects on professional practice and health care outcomes. Cochrane Database Syst Rev (2): CD003030, 2001 Vargas R, Mangione C, Keesey J, et al: Do Collaborative Quality Improvement programs reduce cardiovascular risk for persons with diabetes? AcademyHealth Annual Research Meeting, San Diego, CA, June, 2004 Von Korff M, Katon W, Bush T, et al: Treatment costs, cost offset and cost-effectiveness of collaborative management of depression. Psychosomatics 38:S2–S25, 1997 Wagner C, Groenewegen PP, de Bakker DH, et al: Environmental and organizational determinants of quality management. Qual Manag Health Care 9:63–76, 2001

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Wakefield BJ, Blegen MA, Uden-Holman T, et al: Organizational culture, continuous quality improvement, and medication administration error reporting. Am J Med Qual 16:128–134, 2001 Walton RT, Harvey E, Dovey S, et al: Computerised advice on drug dosage to improve prescribing practice. Cochrane Database Syst Rev (1):CD002894, 2001 Weiner BJ, Alexander JA, Shortell SM: Leadership for quality improvement in health care: empirical evidence on hospital boards, managers, and physicians. Med Care Res Rev 53:397–416, 1996 Weingarten SR, Henning JM, Badamgarav E, et al: Interventions used in disease management programmes for patients with chronic illness—which ones work? Meta-analysis of published reports. BMJ 325:925, 2002 Wells K, Sherbourne C, Schoenbaum M, et al: Impact of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial. JAMA 283:212–220, 2000

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P A R T

I I

National Inventory of Mental Health Quality Measures

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Guide to Inventory Data

S

ection I I presents results from the National Inventory of Mental Health Quality Measures, a federally funded evaluation of the status of quality measurement for mental health and substance-related care (Hermann and Palmer 2002; Hermann et al. 2000, 2002a, 2004). The National Inventory includes 275 single-item measures of technical processes. In focusing on singleitem measures, a commonly used type, the Inventory does not cover multidimensional surveys or fidelity scales, although some measures draw from these data sources. Other inclusion criteria for the Inventory were that the measure was proposed or implemented by one or more stakeholder groups, it has a face relationship to quality of care (excluding, for example, measures of illness prevalence or service utilization), and it meets a minimal threshold of development (defined as having a specified numerator, denominator, and data source). For each measure meeting these criteria, an inventory was developed describing the measure’s clinical rationale and specifications and summarizes available data on its measurement properties. Of 308 measures in the Inventory, the 275 presented here examine unique processes (e.g., consolidating into a single inventory of measures that evaluate 7-day and 30-day rates of continuity of care). The seven chapters that follow present the resulting measure inventories grouped by domain of process. This chapter first describes the methods used for measure collection and evaluation, and then the operational definitions of inventory terms.

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❚ MEASURE IDENTIFICATION Research staff at the Center for Quality Assessment and Improvement in Mental Health (CQAIMH) identified measures available as of November 2000 using primary and secondary-source review, chain-referral, and snowball methods. A total of 348 organizations—accreditors, government agencies, researchers, provider organizations, health systems/facilities, payers, employer purchasers, consumer coalitions, and commercial organizations—were contacted via letters, phone calls, and website reviews. Research on quality of care was reviewed using the MEDLINE, PsychLit, and CRISP databases. CQAIMH staff initially identified 567 process measures used for quality assessment from more than 50 organizations nationwide. After eliminating insufficiently developed measures (90), duplicates (120), and measures lacking a face relationship to quality (49), 308 measures were inventoried.

❚ MEASURE EVALUATION Developers were contacted for documentation supporting each measure. A literature review was then conducted to obtain background information on the subject and clinical context of the measure and to evaluate the scientific evidence relating to the underlying clinical process. Based on training and guidelines, CQAIMH staff inventoried each measure with regard to its rationale, specifications, development, scientific properties, and use. Inventories were based on a format developed for the Computerized Needs-Oriented Quality Measurement Evaluation System (CONQUEST) (Lawthers and Palmer 1997), modified to include information relevant to mental healthcare and other features of this evaluation. Measure attributes defined by explicit criteria, such as data source requirements, were abstracted directly from documentation obtained from developers. Assessment of other attributes required reviewer judgment (e.g., evidence level); these were subject to interrater reliability testing of a 10% sample of measures. Reliability for these “implicit reviews” ranged from kappa scores of 0.5 (moderate) to 1.0 (excellent) (Landis and Koch 1977).

❚ INVENTORY ORGANIZATION Chapters 7–13 present measure inventories organized by domain of quality: prevention, access, assessment, treatment, coordination, continuity, and safety. Where relevant, inventories are further categorized by diagnostic category or process type. Measures on specific topics can be located through indices listing measures by domain of quality, diagnosis, demographic group,

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treatment modality, and data source. Measure attributes evaluated in the Inventory are described in the sections that follow.

Clinical Rationale The clinical rationale statement summarizes the clinical context of a measure and the justification for regarding it as an indicator of quality. To the extent available, research findings are presented on the magnitude of problems observed with the process measured as well as findings on the association between variations in the process and patient outcomes.

Specifications For a rate-based measure, denominator specifications describe sampling, inclusion, and exclusion criteria that determine an individual’s eligibility for a measure, such as age, clinical diagnosis, acuity, service use, and setting. Numerator specifications define the subset of individuals from the denominator receiving a designated process of care. The data source identifies each of the sources needed to construct the measure as specified. Data sources include administrative data from enrollment and billing claims, medical records, pharmacy claims, patient surveys, laboratory records, patient contact data, proprietary data systems, occurrence reports, and program enrollment data. Alternate versions refers to variations on the measure that have been developed to address additional populations, settings, or time intervals.

Development Organizations or individuals known to have proposed or developed a measure are identified under developer; contact information for each developer is provided in the Appendix. Other stakeholders represented in the workgroup that developed a measure are also provided; these include consumers and family members, clinicians, provider organizations, delivery system managers, public sector payers and purchasers, employer purchasers, managed care organizations, accrediting organizations, and researchers. Many measures are part of sets that evaluate different aspects of mental healthcare. In these cases, the name of the measure set is identified. Users are organizations that have implemented the measure for quality assessment or improvement. Development describes the extent to which the measure’s specifications are adequate to implement the measure for routine use: fully operationalized, incomplete, or under development.

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Properties The evidence basis of a measure is assessed based on an AHRQ rating scale that evaluates research on the relationship between the clinical process and patient outcomes (Hermann et al. 2002b; West 2002). Level A reflects support by strong research evidence (e.g., randomized, controlled studies). Level B indicates support by fair research evidence (e.g., quasi-experimental and observational studies). Level C denotes an absence of research evidence; however, there may still be evidence of expert consensus or other organizational support. When available, information is provided on the measure’s reliability in terms of the type of testing (test-retest, interrater, data accuracy, and internal consistency) and findings (positive, negative, or mixed). Types of validity testing and findings are also described. Types of analyses include comparisons with other measures of quality (concurrent validity) and statistical associations between measure conformance and patient outcomes (predictive validity) (Hermann 2002).

Use Current status describes whether a measure is in routine use, pilot-tested (in a research study or applied use), used but discontinued, or has been defined but not used. Routinely used measures are further categorized as used in external or internal quality improvement activities, health plan purchasing and contracting, informing consumer decisions, or research studies of quality of care. Selected results for measures are presented when available, as are other metrics for comparison and interpretation of results, including standards and statistical benchmarks (Hermann and Provost 2003). Information on available methods for case-mix adjustment are presented in terms of the method of adjustment (stratification or multivariate adjustment) and patient risk factors used, such as illness severity, comorbid conditions, and socioeconomic status (Hermann 2003). Cost data provides information on the cost or cost-effectiveness of measurement when available.

References and Instruments Citations accompanying each measure inventory point to sources providing detailed measure specifications, instruments used in measure construction, and reports of relevant research findings, results of testing, measure properties, or results from measure use.

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❚ REFERENCES Hermann RC: Linking outcome measurement with process measurement for quality improvement, in Outcome Measurement in Psychiatry: A Critical Review. Edited by IsHak W, Burt T, Sederer L. Washington, DC, American Psychiatric Publishing, 2002 Hermann RC: Risk adjustment for mental health care, in Risk Adjustment for Measuring Health Care Outcomes. Edited by Iezzoni LI. Chicago, IL, Health Administration Press, 2003 Hermann RC, Palmer RH: Common ground: a framework for selecting core quality measures. Psychiatr Serv 53:281–287, 2002a Hermann RC, Provost SE: Interpreting measurement data for quality improvement: means, norms, benchmarks, and standards. Psychiatr Serv 54:655–657, 2003 Hermann RC, Leff HS, Palmer RH, et al: Quality measures for mental health care: results from a national inventory. Med Care Res Rev 57 (suppl 2):135–154, 2000 Hermann RC, Finnerty M, Provost S, et al: Process measures for the assessment and improvement of quality of care for schizophrenia. Schizophr Bull 28:95–104, 2002a Hermann RC, Leff HS, Provost SE, et al: Process measures used in quality assessment and improvement: are they based on research evidence? Presented at the 15th National Institute of Mental Health Services Research Conference, Washington, DC, April 2002b Hermann RC, Palmer RH, Leff HS, et al: Achieving consensus across diverse stakeholders on quality measures for mental healthcare. Med Care 42:1246–1253, 2004 Landis J, Koch G: The measurement of observer agreement for categorical data. Biometrics 33:159–174, 1977 Lawthers AG, Palmer RH: In search of a few good performance measures: CONQUEST and the typology of clinical performance measures, in Models for Measuring Quality in Managed Care: Analysis and Impact. Edited by Seltzer J, Nash D. New York, Faulkner and Gray, 1997, pp 121–150 West S, King V, Carey TS, et al: Systems to Rate the Strength of Scientific Evidence. Evidence Report No. 47. AH RQ Publication No. 02-E016. Rockville, M D, Agency for Healthcare Research and Quality, 2002

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Prevention Measures

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TABLE 7–1.

IMPROVING MENTAL HEALTHCARE

Availability of alcohol counseling and education

1. Summary

This measure assesses patient-reported adequacy of provider communication about alcohol use.

Clinical rationale:

Brief interventions by primary care clinicians have been found to reduce alcohol abuse in randomized, controlled trials. Interventions include motivational counseling, advice, education and contracting information, and use of drinking diaries. However, a recent national survey found that many primary care clinicians do not routinely offer interventions to problem drinkers.

2. Specifications Denominator:

Number of FACCT Questionnaire respondents 18 years or older with continuous plan enrollment and at least one provider contact in the past 12 months

Numerator:

Sum of all numeric responses (0 [never]–3 [always]) from individuals in the denominator to questions 4d and 5d: 4d) How often in the last 12 months did you have as much time as you needed to talk to your doctor or health care provider about issues having to do with your alcohol use?; 5d) How often in the last 12 months did you get as much information as you needed from your doctor or health care provider when discussing issues having to do with your alcohol use? [Omit from denominator individuals who responded “does not apply to me” to both questions.]

Data sources:

Administrative data; patient survey/instrument

3. Development Developer:

Foundation for Accountability (FACCT)

Stakeholders:

Consumers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

FACCT Alcohol Misuse

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Prevention Measures

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Availability of alcohol counseling and education (continued)

References and Instruments Fleming MF, Barry KL, Manwell LB, et al: Brief physician advice for problem alcohol drinkers: a randomized controlled trial in community-based primary care practices. JAMA 277:1039–1045, 1997 Foundation for Accountability: FACCT Quality Measures Guide [Alcohol Misuse] Version 1.0. Portland, OR, Foundation for Accountability, November 1998 Friedman PD, McCullough D, Chin MH, et al: Screening and intervention for alcohol problems: a national survey of primary care physicians and psychiatrists. J Gen Intern Med 15:84–91, 2000 Wallace P, Cutler S, Haines A: Randomized controlled trial of general practitioner intervention in patients with excessive alcohol consumption. BMJ 297:663–668, 1988 Wilk AI, Jensen NM, Havighurst TC: Meta-analysis of randomized control trials addressing brief interventions in heavy alcohol drinkers. J Gen Intern Med 12:274–283, 1997

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TABLE 7–2.

IMPROVING MENTAL HEALTHCARE

Consumer participation in preventive services

1. Summary

This measure assesses the proportion of consumers with identified risk factors for psychiatric problems who are enrolled in support programs during a specified 12-month period.

Clinical rationale:

Preventive approaches have been found to be effective in reducing the incidence of drug and alcohol disorders as well as certain medical conditions. Psychosocial and educational interventions may reduce rates of mental disorders, but research in this area is at an early stage.

2. Specifications Denominator:

Total number of consumers enrolled in a plan during a specified 12-month period

Numerator:

Consumers from the denominator with identified risk factors (e.g., job loss, bereavement, subclinical depressive symptoms) who are enrolled in mutual help or other support programs during the specified 12-month period

Data sources:

Administrative data; patient survey/instrument

3. Development Developer:

Center for Mental Health Services

Stakeholders: Measure set:

Public-sector payers and purchasers, consumers, clinicians, delivery system managers, researchers Mental Health Statistics Improvement Program

Development:

Incomplete

4. Properties Evidence basis: 5. Use Current status: Used in:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion In routine use Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan/provider contracting, external quality improvement

References and Instruments Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Dusenbury L, Botvin GJ: Substance abuse prevention: competence enhancement and the development of positive life options. J Addict Disord 11:29–45, 1992 Greenfield SF, Shore MF: Prevention of psychiatric disorders. Harv Rev Psychiatry 3:115–129, 1995 Munoz RF, Mrazek PJ, Haggerty RJ: Institute of Medicine Report on Prevention of Mental Disorders: summary and commentary. Am Psychol 51:1116–1122, 1996

Prevention Measures

TABLE 7–3.

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Relapse monitoring plan for stable-phase schizophrenia

1. Summary

This measure assesses the proportion of patients diagnosed with schizophrenia in a stable phase and discontinued from antipsychotic medications whose medical record includes a written relapse-monitoring plan.

Clinical rationale:

Practice guidelines for the treatment of schizophrenia recommend that patients in a stable phase be given a trial off antipsychotic medications if they have had only one episode with at least 1 subsequent year free of positive symptoms or multiple episodes and 5 years without positive symptoms. During the drug-free period, clinical management should include a plan to monitor and respond to early signs of relapse.

2. Specifications Denominator:

All plan members age 18 or older who have a diagnosis of schizophrenia in stable phase and have been discontinued from antipsychotic medications during a specified period

Numerator:

Patients in the denominator whose medical record contains a written relapse-monitoring plan designed for use in recognizing and responding to early signs of new episodes

Data sources:

Administrative data; medical record

3. Development Developer:

American Psychiatric Association

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

American Psychiatric Association Practice Guidelines

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot tested

Used in:

Internal quality improvement, external quality improvement

References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Herz MI, Lamberti JS: Prodromal symptoms and relapse prevention in schizophrenia. Schizophr Bull 21:541–551, 1995

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TABLE 7–4.

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Screening for depression

1. Summary

This measure assesses the proportion of patients seen in medical clinics who were screened for depression during a 12-month period.

Clinical rationale:

Research studies have shown that depression is underdetected in primary care settings. Untreated depression is associated with diminished quality of life, impaired work productivity, and decreased social functioning. Screening for depression in primary care settings has been shown to improve detection rates but has not been shown to improve outcomes unless coupled with initiatives to improve treatment and follow-up. The U.S. Preventive Services Task Force recommends screening adults for depression in clinical practices that have systems in place to assure accurate diagnosis, effective treatment, and follow-up. The Veterans Affairs (VA) healthcare system has implemented screening in conjunction with practice guidelines and routine assessments of quality of care.

2. Specifications Denominator:

All patients seen at least three times in a medical clinic (primary care, general medicine, internal medicine, family practice, flight medicine, gynecology, women’s or mental health clinics) during a 12-month period

Numerator:

Patients from the denominator for whom medical records show documentation of at least one screening for depression with a structured screening instrument or a progress note of documented presence or absence of depression symptoms during the 12-month period

Data sources:

Administrative data; medical record

3. Development Developer:

Veterans Health Administration/Department of Defense (VHA/DOD)

Stakeholders:

Public sector payers and purchasers, employer purchasers, clinicians, delivery system managers, researchers

Measure set:

VHA/DOD Performance Measures for the Management of Major Depressive Disorder in Adults

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Prevention Measures

TABLE 7–4.

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Screening for depression (continued)

Selected results:

62%, patients from VA medical centers (Veterans Affairs National Performance Data Resource and Customer Feedback Centers 1999) 81%, patients from VA medical centers (Veterans Health Administration 2001)

Standards:

60% (Veterans Affairs Office of Quality and Performance 1999)

References and Instruments Coyne J, Klinkman M, Gallo S, et al: Short-term outcomes of detected and undetected depressed primary care patients and depressed psychiatric patients. Gen Hosp Psychiatry 19:333–343, 1997 Joseph R, Hermann RC: Screening for psychiatric disorders in primary care. Harv Rev Psychiatry 6:165–170, 1998 Rost K, Zhang M, Fortney J, et al: Persistently poor outcomes of undetected major depression in primary care. Gen Hosp Psychiatry 20:12–20, 1998 U.S. Preventive Services Task Force: Guide to Clinical Preventive Services. Baltimore, MD, Department of Health and Human Services, 1996 Veterans Affairs National Performance Data Resource and Customer Feedback Centers: FY1999 Network Performance Report. Washington, DC, Veterans Affairs Office of Quality and Performance, 1999 Veterans Health Administration/Department of Defense: Performance Measures for the Management of Major Depressive Disorder in Adults, Version 2.0. Washington, DC, Veterans Health Administration/Department of Defense, 2000 Veterans Health Administration Office of Quality and Performance: FY2002 VHA Performance Measurement System, Technical Manual. Washington, DC, Veterans Health Administration Office of Quality and Performance, 2001

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TABLE 7–5.

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Substance abuse detection

1. Summary

This measure assesses the prevalence of treated substancerelated disorders among members of a health plan.

Clinical rationale:

Alcohol and drug disorders frequently lead to decreased individual functioning, family disruption, and increased medical utilization and costs; however, they often go undetected and untreated. Healthcare visits provide an important opportunity for detection, intervention, or referral to appropriate care. The U.S. Preventive Services Task Force recommends routine screening for alcohol and drug use in primary care settings. Routine screening for problem drinking combined with brief counseling interventions has been shown to reduce drinking and rates of hospitalization. This measure produces a utilization-based estimate of detection intended to be compared with regional population estimates derived from the National Household Survey on Drug Abuse.

2. Specifications Denominator:

All enrollees in a health plan over a 12-month period × 1,000

Numerator:

Those enrollees who received an alcohol- or drug-related diagnosis or received at least one substance abuse–related plan service during the same period.

Data sources:

Administrative data

3. Development Developer:

Washington Circle Group (WCG)

Stakeholders:

Accrediting organizations, public sector payers and purchasers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

WCG Core Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

References and Instruments Conigliaro J, Lofgren RP, Hanusa BH: Screening for problem drinking: impact on physician behavior and patient drinking habits. J Gen Intern Med 13:251–256, 1998

Prevention Measures

TABLE 7–5.

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Substance abuse detection (continued)

McCorry F, Garnick D, Bartlett J, et al: Improving Performance Measurement for Alcohol and Other Drug Services: Report of the Washington Circle Group. Rockville, MD, Washington Circle Group and the Center for Substance Abuse Treatment, 2000 U.S. Preventive Services Task Force: Guide to Clinical Preventive Services. Baltimore, MD, Department of Health and Human Services, 1996 Weisner C, Schmidt L: Alcohol and drug problems among diverse health and social service populations. Am J Public Health 83:824–829, 1993

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TABLE 7–6.

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Substance abuse education in primary care

1. Summary

This measure assesses the proportion of patients who were provided education about substance abuse at a primary care visit.

Clinical rationale:

The primary care setting provides opportunities for clinicians to educate patients regarding alcohol and/or drug abuse. Clinicians should evaluate a patient’s current use and, if indicated, provide education, counseling, and other services. Randomized, controlled studies have shown that brief outpatient counseling for nondependent drinkers can reduce rates of consumption as well as some of the medical and social problems associated with alcohol abuse. There is less evidence for the effectiveness of brief primary care interventions for dependent drinkers or for drug abuse.

2. Specifications Denominator:

All enrollees of a health plan age 18 and older who had a primary care visit and responded to an enrollee survey within a specified time period

Numerator:

The total number of patients in the denominator who report that they were advised or given information about alcohol and/or drug abuse by the primary care provider

Data sources:

Administrative data; patient survey/instrument

3. Development Developer:

Washington Circle Group (WCG)

Stakeholders:

Accrediting organizations, public sector payers and purchasers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

WCG Core Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

References and Instruments Fleming MF, Mundt MP, French MT, et al: Benefit-cost analysis of brief physician advice with problem drinkers in primary care settings. Med Care 38:7–18, 2000 Friedman PD, McCullough D, Chin MH, et al: Screening and intervention for alcohol problems: a national survey of primary care physicians and psychiatrists. J Gen Intern Med 15:84–91, 2000

Prevention Measures

TABLE 7–6.

❚ 153

Substance abuse education in primary care (continued)

McCorry F, Garnick D, Bartlett J, et al: Improving Performance Measurement for Alcohol and Other Drug Services: Report of the Washington Circle Group. Rockville, MD, Washington Circle Group and the Center for Substance Abuse Treatment, 2000 U.S. Preventive Services Task Force: Guide to Clinical Preventive Services. Baltimore, MD, Department of Health and Human Services, 1996

154

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TABLE 7–7.

IMPROVING MENTAL HEALTHCARE

Timely psychosocial screening

1. Summary

This measure assesses the proportion of inpatients whose medical records include documentation of psychosocial screening within 3 days of admission.

Clinical rationale:

One component of inpatient care is a psychosocial screening of patients early in the inpatient stay. Such a screening is intended to identify “immediate high risk issues (for example, job loss, unattended children, treatment noncompliance, and problematic discharge)” (NASW Commission on Health and Mental Health 1990). This information can be useful both for immediate intervention and discharge planning, and for these reasons it should be collected expeditiously. There is no empirical research evidence demonstrating a link between the timeliness of psychosocial screenings and treatment outcomes.

2. Specifications Denominator:

The total number of individuals admitted to a psychiatric inpatient service during a specified period of time

Numerator:

The number of individuals from the denominator with a psychosocial screening evaluation documented in the medical record within 3 days of admission

Data sources:

Administrative data; medical record

3. Development Developer:

National Association of Social Workers (NASW)

Stakeholders:

Accrediting organizations, clinicians, provider organizations

Measure set:

NASW Clinical Indicators for Social Work

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot tested

Used in:

Internal quality improvement

Standards:

95% (National Association of Social Workers 1990)

References and Instruments Gannt AB, Cohen NL, Sainz A: Impediments to the discharge planning effort for psychiatric inpatients. Soc Work Health Care 29:1–14, 1999 Loveland Cook CA, Chadiha L, Schmidt B, et al: High risk screening mechanisms: patient characteristics as predictors of social work utilization in the VA. Soc Work Health Care 16:101–117, 1992

Prevention Measures

TABLE 7–7.

❚ 155

Timely psychosocial screening (continued)

National Association of Social Workers (NASW) Commission on Health and Mental Health: NASW clinical indicators for social work and psychosocial services in the acute psychiatric hospital. 1990. Available at: http:// www.naswdc.org/practice/standards/acute_psych_hospital.asp#process1. Accessed June 24, 2005. Vourlekis BS: Quality assurance indicators for monitoring social work in psychiatric acute care hospitals. Hosp Community Psychiatry 42:460–461, 1991

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C H A P T E R

8

Access Measures

157

158

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TABLE 8–1.

IMPROVING MENTAL HEALTHCARE

Access to child specialty care for depression

1. Summary

This measure assesses the proportion of children who are treated for depression or dysthymia by clinicians with specialized training in child mental healthcare.

Clinical rationale:

Depression in children can lead to poor social, academic, and family functioning and may persist later in life. Clinical practice guidelines developed by the American Academy of Child and Adolescent Psychiatry recommend that the evaluation and treatment of children be performed by clinical professionals with training and experience in childcentered care. The supply of child mental health specialists is limited in many parts of the country. Observational studies suggest some benefit with mental health specialty care compared with nonspecialty care but have not examined access to clinicians specializing in mental healthcare for children.

2. Specifications Denominator:

The number of children age 12 or under with a primary diagnosis of major depression or dysthymia in a given health plan during a specified year

Numerator:

Those members of the denominator who saw a clinician with specialized training in the mental healthcare of children (appropriate skills and qualifications to be determined by the health plan)

Data sources:

Administrative data; clinician training/certification records

3. Development Developer:

American Psychiatric Association

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

American Psychiatric Association Task Force on Quality Indicators

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

90% (American Psychiatric Association 1999)

Access Measures

TABLE 8–1.

❚ 159

Access to child specialty care for depression (continued)

References and Instruments American Academy of Child and Adolescent Psychiatry: Practice parameters for the assessment and treatment of children and adolescents with depressive disorders. J Am Acad Child Adolesc Psychiatry 37(suppl):63S–83S, 1998 American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1999 Angold A, Costello EJ, Burns BJ, et al: Effectiveness of nonresidential specialty mental health services for children and adolescents in the “real world.” J Am Acad Child Adolesc Psychiatry 39:154–160, 2000 Kelleher K, Starfield B: Health care use by children receiving mental health services. Pediatrics 85:114–118, 1990 McGuire T, Trupin E, Rothenberg MB: Survey of the utilization of psychiatrists and psychologists for hospitalized children. Child Health Care 14:114–117, 1985

160

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TABLE 8–2.

IMPROVING MENTAL HEALTHCARE

Access to medication management by a psychiatrist

1. Summary

This measure assesses the proportion of individuals requesting an initial appointment with a psychiatrist for medication management who are offered an appointment within 10 days of request.

Clinical rationale:

A number of factors may influence waiting times for medication management visits with psychiatrists, including geographic variation in the availability of psychiatrists and the inclusion of psychiatrists on health plan provider panels. Little is known about the relationship between waiting times and outcome. A study of mental health visits found increased waiting times to be associated with higher noshow rates.

2. Specifications Denominator:

The number of individuals requesting an initial appointment with a psychiatrist for medication assessment or management during a 3-month period

Numerator:

The number of individuals from the denominator who are offered an appointment within 10 business days of their request

Data sources:

Administrative data; patient contact/appointment data

3. Development Users:

Comprehensive Behavioral Care

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments Institute of Medicine: Managing Managed Care: Quality Improvement in Behavioral Health. Washington, DC, National Academy Press, 1997 Knesper D, Wheeler J, Pagnucco D: Mental health services providers’ distribution across counties in the United States. Am Psychol 39:1424–1434, 1984 Wilkinson LK, Blixen CE, Mallasch NI, et al: Mental health problems in hospitalbased clinics: patient profile and referral patterns. J Am Psychiatr Nurses Assoc 1:140–145, 1995

❚ 161

Access Measures

TABLE 8–3.

Access to psychological testing

1. Summary

This measure assesses the proportion of individuals requesting psychological testing who are offered an appointment within 10 days of request.

Clinical rationale:

A number of factors may influence waiting times for psychological testing, including variation in the availability of psychologists, a limited proportion of psychologists trained to perform testing, and inclusion of trained psychologists on health plan provider panels.

2. Specifications Denominator:

The number of individuals requesting an initial appointment with a psychologist for psychological testing during a 3-month period

Numerator:

The number of individuals from the denominator who are offered an appointment within 10 business days of their request

Data sources:

Administrative data; patient contact/appointment data

3. Development Users:

Comprehensive Behavioral Care

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments Institute of Medicine: Managing Managed Care: Quality Improvement in Behavioral Health. Washington, DC, National Academy Press, 1997 Knesper D, Wheeler J, Pagnucco D: Mental health services providers’ distribution across counties in the United States. Am Psychol 39:1424–1434, 1984 Wilkinson LK, Blixen CE, Mallasch NI, et al: Mental health problems in hospitalbased clinics: patient profile and referral patterns. J Am Psychiatr Nurses Assoc 1:140–145, 1995

162

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TABLE 8–4.

IMPROVING MENTAL HEALTHCARE

Access to substance abuse treatment

1. Summary

This measure compares the number of medically indigent state residents, age 18 and older, reporting alcohol- or drug-related problems and a desire for treatment with the number of individuals admitted to a state substance abuse treatment program.

Clinical rationale:

Studies of substance abuse treatment support the effectiveness of a diverse array of interventions. However, two national surveys on access to care for substance abuse have shown a marked decrease over the past decade in the number and diversity of services clients reported receiving. This measure compares current enrollment in state-funded substance abuse programs with estimates of need from an epidemiologic survey.

2. Specifications Denominator:

Estimate (based on survey of random-digit dialing sample of households) of state residents age 18 and older who report having alcohol- or drug-related problems (abuse or dependence as defined by DSM-IV criteria) who are medically indigent (annual household income <$10,000; receiving Medicaid or other public assistance; and have no medical insurance) and who desire substance-related treatment at a specified point in time

Numerator:

Number of residents (based on unduplicated count of client billings) from the denominator who have received services from a substance abuse treatment program funded by the state substance abuse agency

Data sources:

Administrative data; patient survey/instrument

Alternate versions: Population: Adolescents (ages 12–17) 3. Development Developer:

Texas Commission on Alcohol and Drug Abuse

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, researchers

Measure set:

Texas Commission on Alcohol and Drug Abuse Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Access Measures

TABLE 8–4.

❚ 163

Access to substance abuse treatment (continued)

References and Instruments Etheridge RM, Craddock SG, Dunteman GH, et al: Treatment services in two national studies of community-based drug abuse treatment programs. J Subst Abuse 7:9–26, 1995 McLellan AT, Kushner H, Metzger D, et al. The fifth edition of the Addiction Severity Index. J Subst Abuse Treat 9:199–213, 1992 Texas Commission on Alcohol and Drug Abuse (TCADA). Definition source: Automated Budget and Evaluation System of Texas. Data Source: TCADA Texas School of Substance Abuse, Grades 7–12. Texas Commission on Alcohol and Drug Abuse: Administrative Code, Chapter 144, Contract Administrative Requirements Rules for Funded Providers. 2004. Available at: http://www.tcada.state.tx.us/rules/144_Final_Rules.doc. Accessed June 28, 2005. Substance Abuse and Mental Health Services Administration Office of Applied Studies: National Household Survey on Drug Abuse: United States Department of Health and Human Services; 1998.

164

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IMPROVING MENTAL HEALTHCARE

TABLE 8–5.

Access to substance abuse treatment for pregnant women

1. Summary

This measure assesses the proportion of pregnant women who are offered and accept a face-to-face appointment for substance abuse treatment within 48 hours of their first request for services.

Clinical rationale:

Substance abuse and dependency during pregnancy is strongly associated with poor maternal and infant health outcomes. Some empirical evidence suggests prenatal substance abuse treatment can improve perinatal outcomes. A significant barrier is a high rate of early attrition of individuals with substance abuse disorders from treatment. One strategy that has been tested is to schedule appointments proximally to the time of the first request for services; however, research on the impact of this strategy has been mixed.

2. Specifications Denominator:

The number of pregnant women requesting new substance abuse services (i.e., intake appointment or admission)

Numerator:

The number of pregnant women who were offered and accepted a face-to-face appointment (including an intake appointment/admission) within 48 hours of the first request for services

Data sources:

Administrative data; patient contact/appointment data

3. Development Developer:

Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

Virginia Performance and Outcomes Measurement System

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

47.1%–63.2% (mean: 56.4%) (Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services 2002)

Cost data:

Estimates from reported expenses

Access Measures

TABLE 8–5.

❚ 165

Access to substance abuse treatment for pregnant women (continued)

References and Instruments Alterman AI, Bedrick J, Howden D, et al: Reducing waiting time for substance abuse treatment does not reduce attrition. J Subst Abuse 6:325–332, 1994 Chang G, Carroll KM, Behr HM, et al: Improving treatment outcome in pregnant opiate-dependent women. J Subst Abuse Treat 9:327–330, 1992 Chazotte C, Youchah J, Freda MC: Cocaine using during pregnancy and low birth weight: the impact of prenatal care and drug treatment. Semin Perinatol 19:293– 300, 1995 Kelly RH, Danielsen BH, Golding JM, et al: Adequacy of prenatal care among women with psychiatric diagnoses giving birth in California in 1994 and 1995. Psychiatr Serv 50:1584–1590, 1999 Stark MJ, Campbell BK, Brinkerhoff CV: “Hello may we help you?” A study of attrition prevention at the time of the first phone contact with substance abusing clients. Am J Drug Alcohol Abuse 16:67–76, 1990 Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services: Performance and Outcomes Measurement System (POMS): Specification of Performance and Outcomes Indicators, Version 1.1. Richmond, VA, Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services, 1999 Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services: Performance and Outcomes Measurement System (POMS) 2001 Annual Report. Richmond, VA, Office of Research and Evaluation, Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services, 2002

166

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TABLE 8–6.

IMPROVING MENTAL HEALTHCARE

Convenience of appointment times

1. Summary

This measure assesses the proportion of consumers using mental health services who reported that services were available at convenient times.

Clinical rationale:

The healthcare system is placing increasing importance on quality of care from the consumer’s perspective. This trend reflects the results of consumer advocacy, respect for individual autonomy, and the adoption of a continuous quality improvement model that focuses on serving the customer. Convenience of medical care is associated with increased patient satisfaction in research studies.

2. Specifications Denominator:

Consumers completing a Mental Health Statistics Improvement Program (MHSIP) Consumer Survey who received a mental health service during a specific period of time

Numerator:

Consumers in the denominator responding “strongly agree” or “agree” to the statement “Services were available at times that were good for me” on the MHSIP survey (question 8)

Data sources:

Administrative data; patient survey/instrument

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

MHSIP

Users:

American College of Mental Health Administration, Rhode Island Department of Mental Health, Retardation, and Hospitals

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

References and Instruments Bjoerkman T, Hansson L, Svensson B, et al: What is important in psychiatric outpatient care? Quality of care from the patient’s perspective. Int J Qual Health Care 7:355–362, 1995

Access Measures

TABLE 8–6.

❚ 167

Convenience of appointment times (continued)

Campbell J: How consumers/survivors are evaluating the quality of psychiatric care. Eval Rev 21:357–363, 1997 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Jatulis DE, Bundek NI, Legorreta AP: Identifying predictions of satisfaction with access to medical care and quality of care. Am J Med Qual 12:8–11, 1997 Magruder KM, Norquist GS: Structural issues and policy in the primary care management of depression. J Clin Psychiatry 60(suppl):45–51, 1999

168

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TABLE 8–7.

IMPROVING MENTAL HEALTHCARE

Convenience of location of services

1. Summary

This measure assesses the proportion of consumers using mental health services who reported that the location of services was convenient.

Clinical rationale:

The healthcare system is placing increasing importance on quality of care from the consumer’s perspective. This trend reflects the results of consumer advocacy, respect for individual autonomy, and the adoption of a continuous quality improvement model that focuses on serving the customer. Research studies have found a relationship between geographic proximity to medical services and patient outcomes. Other studies have found a relationship between the availability of transportation and service utilization.

2. Specifications Denominator:

Consumers who received a mental health service and who have completed a Mental Health Statistics Improvement Program (MHSIP) Consumer Survey during a specific period of time

Numerator:

Consumers in the denominator responding “strongly agree” or “agree” to the statement “The location of services was convenient” on the MHSIP survey (question 5)

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

MHSIP

Users:

American College of Mental Health Administration, Virginia Department of Mental Health

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

Access Measures

TABLE 8–7.

❚ 169

Convenience of location of services (continued)

References and Instruments Bjoerkman T, Hansson L, Svensson B, et al: What is important in psychiatric outpatient care? Quality of care from the patient’s perspective. Int J Qual Health Care 7:355–362, 1995 Campbell J: How consumers/survivors are evaluating the quality of psychiatric care. Eval Rev 21:357–363, 1997 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Cunningham WE, Hays RD, Ettl MK, et al: The prospective effect of access to medical care on health-related quality-of-life outcomes in patients with symptomatic HIV disease. Med Care 36:295–306, 1998 Fortney J: The impact of geographic accessibility on the intensity and quality of depression treatment. Med Care 37:884–893, 1999 Fortney JC, Owen R, Clothier J: Impact of travel distance on the disposition of patients presenting for emergency psychiatric care. J Behav Health Serv Res 26:104–108, 1999

170

❚

TABLE 8–8.

IMPROVING MENTAL HEALTHCARE

Employee assistance program (EAP) referrals for mental health and substance abuse

1. Summary

This measure assesses the proportion of individuals in a given EAP who have been referred to a mental health and/or substance abuse provider.

Clinical rationale:

EAPs are workplace-based treatment and referral services designed to assist workers with personal and behavioral health problems. Goals of EAPs include helping employees make improvements in personal and family life and improve workplace productivity. EAPs typically provide short-term therapy services and referrals for more extensive treatment. They may also serve as gatekeepers, managing the utilization of external services. A study of one large employer found that implementation of EAP services was associated with increased utilization of external mental health services, suggesting that in this case EAP facilitated access. The generalizability of these findings is not known, nor is the impact of EAP services and referrals on employee mental health outcomes.

2. Specifications Denominator:

The number of cases opened for individuals older than 18 in a given EAP during a specified year

Numerator:

Those individuals in the denominator who have been referred to a mental health and/or substance abuse provider or who will begin to utilize their mental health/substance abuse benefits

Data sources:

Administrative data

3. Development Developer:

American Managed Behavioral Healthcare Association

Stakeholders:

Accrediting organizations, consumers, researchers

Measure set:

PERMS 2.0

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

External quality improvement

References and Instruments American Managed Behavioral Healthcare Association: PERMS 2.0: Performance Measures for Managed Behavioral Healthcare Programs. Washington, DC, American Managed Behavioral Healthcare Association, 1998

Access Measures

TABLE 8–8.

❚ 171

Employee assistance program (EAP) referrals for mental health and substance abuse (continued)

Davidson BN: Managing behavioral health care: an employer’s perspective. J Clin Psychiatry 59(suppl):9–12, 1998 Zarkin GA, Garfinkel SA: The relationship between employer health insurance characteristics and the provision of employee assistance programs. Inquiry 31:102–114, 1994 Zarkin GA, Bray JW, Qi J: The effect of employee assistance programs use on healthcare utilization. Health Serv Res 35:77–100, 2000

172

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TABLE 8–9.

IMPROVING MENTAL HEALTHCARE

Financial barriers to care

1. Summary

This measure assesses the proportion of consumers using mental health services who reported cost was a barrier to care.

Clinical rationale:

Healthcare costs can impose a barrier to service use through the lack of health insurance, inadequate coverage from public or private programs, and high copayments. Out-ofpocket costs have been associated with decreased service use in research studies.

2. Specifications Denominator:

Consumers completing a Mental Health Statistics Improvement Program (MHSIP) Consumer Survey who received a mental health service during a 12-month period

Numerator:

Consumers in the denominator responding “strongly agree” or “agree” to the statement “I was unable to get some services I wanted because I could not pay for them” on the MHSIP survey (question 4)

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

MHSIP

Users:

Tennessee Department of Mental Health and Mental Retardation

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

References and Instruments Campbell J: How consumers/survivors are evaluating the quality of psychiatric care. Eval Rev 21:357–363, 1997 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Melfi C, Croghan T, Hanna M: Access to treatment for depression in a Medicaid population. J Health Care Poor Underserved 10:201–215, 1999

Access Measures

TABLE 8–9.

❚ 173

Financial barriers to care (continued)

Newhouse JP, Insurance Experiment Group: Free for All? Lessons From the RAND Health Insurance Experiment. Cambridge, MA, Harvard University Press, 1993 Simon GE, VonKorff M, Durham ML: Predictors of outpatient mental health utilization by primary care patients in a health maintenance organization. Am J Psychiatry 151:908–913, 1994

174

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TABLE 8–10.

IMPROVING MENTAL HEALTHCARE

Mental health utilization: percentage of members receiving inpatient, day/night care, and ambulatory services

1. Summary

This measure assesses the proportion of health plan enrollees who use mental health services over a 1-year period.

Clinical rationale:

Many managed care organizations and health plans use utilization management techniques to determine access to mental health services. Because financial incentives may favor limiting service use, there is widespread interest in monitoring access to services. Researchers and accreditation organizations have used penetration rates (i.e., the proportion of plan beneficiaries using mental health services over a specified period) as a crude indicator of access. At present, little is known about what would be an “appropriate” penetration rate or how this rate should be adjusted for population characteristics.

2. Specifications Denominator:

The number of members receiving mental health services during the measurement year

Numerator:

The number of members receiving services in the following categories: any mental health services (inpatient, day/night, ambulatory), day/night mental health services, and ambulatory mental health services; reported by age and sex.

Data sources:

Administrative data

3. Development Developer:

National Committee for Quality Assurance

Stakeholders:

Accrediting organizations, public sector payers and purchasers, employer purchasers, consumers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Health Plan Employer Data and Information Set

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Selected results:

0.02%–5.14% enrollees in Kaiser Permanente health plans (Kaiser Permanente 1999); 7.0%–21.5% among Medicaid managed care enrollees in four states(General Accounting Office 1999)

❚ 175

Access Measures

TABLE 8–10.

Case-mix adjustment: Type:

Mental health utilization: percentage of members receiving inpatient, day/night care, and ambulatory services (continued) Yes Analysis by subgroup: level of care, age, sex

References and Instruments General Accounting Office: Medicaid Managed Care: Four States’ Experiences With Mental Health Carveout Programs (GAO/HEHS-99–118). Washington, DC, General Accounting Office, 1999 Grazier KL, Eselius LL: Mental health carve-outs: effects and implications. Med Care Res Rev 56(suppl):37–59, 1999 Kaiser Permanente: Making an Informed Choice With HEDIS 1999 Performance Measures, Program Overview. Portland, OR, Kaiser Permanente, 1999 National Committee for Quality Assurance: Health Plan Employer Data and Information Set (HEDIS) 2003, Vol 2. Washington, DC, National Committee for Quality Assurance, 2002 Weissman E, Pettigrew K, Sotsky S, et al: The cost of access to mental health services in managed care. Psychiatr Serv 51:664–666, 2000

176

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TABLE 8–11.

IMPROVING MENTAL HEALTHCARE

Chemical dependency utilization: percentage of members receiving inpatient, day/night care, and ambulatory services

1. Summary

This measure assesses the proportion of health plan enrollees who use substance abuse services over a 1-year period.

Clinical rationale:

Many managed care organizations and health plans use utilization management techniques to determine access to substance abuse services. Because financial incentives typically favor limiting service utilization, there is an interest in monitoring access to care. Researchers and accrediting organizations have used penetration rates (i.e., the proportion of plan beneficiaries using substance abuse services over a specified period) as a crude indicator of access. At present, little is known about what would be an “appropriate” penetration rate or how this rate should be adjusted for characteristics of beneficiary populations.

2. Specifications Denominator:

The number of members receiving chemical dependency services during the measurement year

Numerator:

The number of members receiving services in the following categories: any chemical dependency services, day/night chemical dependency services, ambulatory chemical dependency services; reported by age and sex

Data sources:

Administrative data

3. Development Developer:

National Committee for Quality Assurance

Stakeholders:

Accrediting organizations, public sector payers and purchasers, employer purchasers, consumers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Health Plan Employer Data and Information Set

Users:

Department of Veterans Affairs Substance Abuse Measures

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Selected results:

0.06%–0.63% (Kaiser Permanente 1999)

❚ 177

Access Measures

TABLE 8–11.

Case-mix adjustment: Type:

Chemical dependency utilization: percentage of members receiving inpatient, day/night care, and ambulatory services (continued) Yes Analysis by subgroup: level of care, age, sex

References and Instruments Grazier KL, Eselius LL: Mental health carve-outs: effects and implications. Med Care Res Rev 56(suppl):37–59, 1999 Kaiser Permanente: Making an Informed Choice With HEDIS 1999 Performance Measures, Program Overview. Portland, OR, 1999 National Committee for Quality Assurance: Health Plan Employer Data and Information Set (HEDIS) 2003, Vol 2. Washington, DC, National Committee for Quality Assurance, 2002 Weissman E, Pettigrew K, Sotsky S, et al: The cost of access to mental health services in managed care. Psychiatr Serv 51:664–666, 2000

178

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TABLE 8–12.

IMPROVING MENTAL HEALTHCARE

Response time for crisis intervention teams

1. Summary

This measure assesses the average time period between contacting a crisis intervention team and receipt of outreach or stabilization services.

Clinical rationale:

A 1993 survey found that 39 of 50 states had implemented mobile crisis programs for individuals with mental health– related problems. These programs provide communitybased crisis intervention and stabilization. There are no published reports evaluating the responsiveness of these teams or the association between response time and outcome.

2. Specifications Denominator:

The number of presentations of adults ages 18 and older in crisis leading to interventions by the assigned crisis intervention team during a specified 90-day period

Numerator:

For all events in the denominator, the number of hours elapsing between initial contact with the crisis intervention team and receipt of formal outreach or stabilization services

Data sources:

Administrative data, patient contact/appointment data

Alternate versions:

Population: Children and youth < age 18

3. Development Developer:

Maine Department of Mental Health, Mental Retardation and Substance Abuse Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers, provider organizations, legislative members

Measure set:

Mental Health Performance Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments Campos DY, Gieser MT: The psychiatric emergency/crisis disposition and community networks. Emergency Health Services Research 3:117–128, 1985 Geller JL, Fisher WH, McDermeit M: A national survey of mobile crisis services and their evaluation. Psychiatr Serv 46:893–897, 1995

Access Measures

TABLE 8–12.

❚ 179

Response time for crisis intervention teams (continued)

Maine Department of Mental Health, Mental Retardation, and Substance Abuse: Mental Health Performance Indicators (Draft Document). Augusta, ME, Maine Department of Mental Health, Mental Retardation, and Substance Abuse 1999 Merson S, Tyrer P, Onyett S, et al: Early intervention in psychiatric emergencies: a controlled clinical trial. Lancet 339:555, 1992

180

❚

TABLE 8–13.

IMPROVING MENTAL HEALTHCARE

Urgent mental healthcare offered within 48 hours

1. Summary

This measure assesses the proportion of patients meeting criteria for urgent mental healthcare who are offered an appointment for a visit within 48 hours of request.

Clinical rationale:

Ready access to requested mental healthcare is a priority for consumers. Potential barriers to accessible care include availability of appropriate clinicians in a geographic area, the inclusion of a sufficient number of clinicians on provider panels, and clinician waiting lists. The triage or gate-keeping role performed by utilization management could facilitate access by helping patients to find appropriate and available treaters or could contribute to delays by imposing restrictions. A number of mental healthcare facilities and health plans have begun to establish goals for access to routine, urgent, and emergent care and are measuring their performance against these goals. There is little empirical evidence about the association between conformance to these goals and outcomes of care. One study of completion rates of mental healthcare referrals suggests that longer waiting times are associated with a lower likelihood of patients completing the referral.

2. Specifications Denominator:

The total number of patients requesting a mental health appointment who meet criteria for urgent care during a monthly reporting period

Numerator:

The patients from the denominator who are offered an appointment within 48 hours of request

Data sources:

Patient contact/appointment data

3. Development Users:

Comprehensive Behavioral Care, Florida Council for Community Healthcare, M-CARE

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Standards:

100% (M-CARE 2000)

Access Measures

TABLE 8–13.

Urgent mental healthcare offered within 48 hours (continued)

References and Instruments Institute of Medicine: Managing Managed Care: Quality Improvement in Behavioral Health. Washington, DC, National Academy Press, 1997 M-CARE: Central Diagnostic and Referral Agency Quality Improvement Performance Measurement Report. Ann Arbor, MI, M-CARE, 2000

❚ 181

182

❚

TABLE 8–14.

IMPROVING MENTAL HEALTHCARE

Urgent mental healthcare received within 24 hours

1. Summary

This measure reflects the proportion of patients who receive face-to-face contact with an appropriate provider within 24 hours during urgent situations.

Clinical rationale:

Ready access to mental healthcare is a priority for consumers and purchasers of care. Potential barriers to accessible care include availability of appropriate clinicians in a geographic area, health insurance, utilization management and triage, and waiting times after arrival. A number of state mental health systems and private health plans have begun to establish goals for urgent, emergent, and routine access to care and are measuring their performance against these goals. There is little empirical evidence about the association between conformance to these goals and outcomes of care.

2. Specifications Denominator:

The total number of urgent service encounters during a specified period

Numerator:

Those encounters in the denominator in which a face-to-face contact with an appropriate provider occurred within 24 hours of the initial contact for services

Data sources:

Administrative data, patient contact/appointment data

3. Development Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Health plan provider contracting, external quality improvement

References and Instruments Institute of Medicine: Managing Managed Care: Quality Improvement in Behavioral Health. Washington, DC, National Academy Press, 1997

❚ 183

Access Measures

TABLE 8–15.

Access to emergent mental healthcare

1. Summary

This measure assesses the proportion of patients with a risk of harm to self or others requesting emergent mental healthcare who are provided care within 2 hours of request.

Clinical rationale:

Ready access to mental healthcare is a priority for consumers and policy makers. Triage services could facilitate access by helping patients find appropriate and available treatment. A number of mental healthcare facilities and health plans have begun to establish goals for access to emergent, urgent, and routine care and are measuring their performance against these goals. For this purpose emergent care has been defined as necessary due to imminent risk of harm to the patient or others. The risk has been further categorized as life threatening or non–life threatening. There is no empirical evidence on the association between conformance to timeliness goals and outcomes of care.

2. Specifications Denominator:

The total number of patients with a life-threatening risk to themselves or others who request emergent care during a monthly reporting period

Numerator:

The patients from the denominator who are provided care within 2 hours of request

Data sources:

Administrative data; patient contact/appointment data

Alternate versions:

Risk status: non-life threatening, within 6 hours Geographic region: urban area, within 1 hour; nonurban, within 4 hours

3. Development Users:

Comprehensive Behavioral Care, Florida Council for Community Mental Healthcare, M-CARE

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Standards:

Non-life threatening care: 100% (M-CARE 2000)

References and Instruments Institute of Medicine: Managing Managed Care: Quality Improvement in Behavioral Health. Washington, DC, National Academy Press, 1997 M-CARE: Central Diagnostic and Referral Agency Quality Improvement Performance Measurement Report. Ann Arbor, MI, M-CARE, 2000

184

❚

TABLE 8–16.

IMPROVING MENTAL HEALTHCARE

Access to routine mental healthcare

1. Summary

This measure assesses the proportion of patients requesting routine mental healthcare who are offered an appointment for a visit within 10 days of request.

Clinical rationale:

Ready access to requested mental healthcare is a priority for consumers. Potential barriers to accessible care include availability of appropriate clinicians in a geographic area, the inclusion of a sufficient number of clinicians on provider panels, and clinician waiting lists. The triage or gate-keeping role performed by utilization management could facilitate access by helping patients to find appropriate and available treaters or could contribute to delays by imposing restrictions. A number of mental healthcare facilities and health plans have begun to establish goals for access to routine, urgent, and emergent care and are measuring their performance against these goals. There is little empirical evidence about the association between conformance to these goals and outcomes of care. One study of completion rates of mental healthcare referrals suggests that longer waiting times are associated with a lower likelihood of patients completing the referral.

2. Specifications Denominator:

The total number of patients requesting a mental health appointment who meet criteria for routine care during a monthly reporting period

Numerator:

The patients from the denominator who are offered an appointment within 10 business days of request

Data sources:

Administrative data, patient contact/appointment data

3. Development Users:

Comprehensive Behavioral Care, Florida Council for Community Healthcare, M-CARE

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Standards:

90% (M-CARE 2000)

Access Measures

TABLE 8–16.

❚ 185

Access to routine mental healthcare (continued)

References and Instruments Institute of Medicine: Managing Managed Care: Quality Improvement in Behavioral Health. Washington, DC, National Academy Press, 1997 M-CARE: Central Diagnostic and Referral Agency Quality Improvement Performance Measurement Report. Ann Arbor, MI, M-CARE, 2000 Wilkinson LK, Blixen CE, Mallasch NI, et al: Mental health problems in hospitalbased clinics: patient profile and referral patterns. J Am Psychiatr Nurs Assoc 1:140–145, 1995

186

❚

TABLE 8–17.

IMPROVING MENTAL HEALTHCARE

Waiting time for case management services (mental retardation)

1. Summary

This measure assesses the proportion of adults with mental retardation who have a first planning session with a case management program within 7 days of the initial request for services.

Clinical rationale:

Case management services for adults with mental retardation provide assessment, referral, and coordination of services to address medical, developmental, and psychosocial needs. Research indicates that family members rely heavily on professional help to provide support for adults with mental retardation. Although there is no empirical research on the effectiveness of timely access to service coordination programs, some program evaluation research suggests that case management programs decreased institutional placements and had a positive impact on consumer and family satisfaction.

2. Specifications Denominator:

The total number of adults with mental retardation for whom case management services were requested within a specified duration

Numerator:

Those consumers from the denominator who had their first service planning session with the case management program within 7 days of the initial contact

Data sources:

Administrative data, case management assignment/contact data

3. Development Users:

Chesterfield Community Services Board

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

95% (Chesterfield County Community Services Board 1999)

Standards:

100% (Chesterfield County Community Services Board 1999)

Access Measures

TABLE 8–17.

❚ 187

Waiting time for case management services (mental retardation) (continued)

References and Instruments Chesterfield County Community Services Board: FY99 Outcome Management Report. Chesterfield, VA, Chesterfield County Community Services Board, 1999 Criscione T, Kastner TA, Walsh KK, et al: Managed health care services for people with mental retardation: impact on inpatient utilization. Ment Retard 31:297–306, 1993 Levy JM, Rimmerman A, Botuck S, et al: The support network of mothers of younger and adult children with mental retardation and developmental disabilities receiving case management. British Journal of Developmental Disabilities 42:24– 31, 1996 Rudolph C, Lakin KC, Oslund JM, et al: Evaluation of outcomes and costeffectiveness of a community behavioral support and crisis response demonstration project. Ment Retard 36:187–197, 1998

188

❚

TABLE 8–18.

IMPROVING MENTAL HEALTHCARE

Waiting time for child case management services

1. Summary

This measure assesses the average waiting time between a determination of a child or adolescent’s need for case management services and their first contact with a case manager.

Clinical rationale:

Case management services for children with psychiatric disorders and their families provide assessment, referral, and coordination of services to address medical, developmental, and psychosocial needs. There is relatively little research data evaluating the effectiveness of this approach, but an evaluation of the New York State’s Children and Youth Intensive Case Management Program found the program to be associated with reduced symptoms, improved functioning, and decreased hospitalizations. Access to case management programs is limited by waiting lists in some states, but there has been no study of the association between waiting time for services and outcomes.

2. Specifications Denominator:

The number of children/youth completing an initial intake/ screening during a specified 90-day period and found to be in need of case management services

Numerator:

For each child/youth included in the denominator, the number of days elapsing between initial intake/screening and first contact with a case manager

Data sources:

Administrative data, case management assignment/contact data, medical record

3. Development Developer:

Maine Department of Mental Health, Mental Retardation and Substance Abuse Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers, provider organizations, legislative members

Measure set:

Children’s Mental Health Performance Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Access Measures

TABLE 8–18.

❚ 189

Waiting time for child case management services (continued)

References and Instruments Evans ME, Huz S, McNulty T, et al: Child, family, and system outcomes of intensive case management in New York State. Psychiatr Q 67:273–286, 1996 Maine Department of Mental Health, Mental Retardation, and Substance Abuse Services: Children’s Mental Health Performance Indicators (Draft Document). Augusta, ME, 1999 Stroul BA, Goldman SK: Study of community-based services for children and adolescents who are severely emotionally disturbed. J Ment Health Adm 17:61–77, 1990

190

❚

TABLE 8–19.

IMPROVING MENTAL HEALTHCARE

Waiting time for mental health services

1. Summary

This measure assesses the average time between a consumer’s request for services and contact with a mental health professional during a 12-month period.

Clinical rationale:

Ready access to requested mental healthcare is a priority for consumers. Potential barriers to accessible care include availability of appropriate clinicians in a geographic area, the inclusion of a sufficient number of clinicians on provider panels, and clinician waiting lists. The triage or gate-keeping role performed by utilization management could facilitate access by helping patients to find appropriate and available treaters or could contribute to delays by imposing restrictions. There is little empirical evidence about the association between timely access and outcomes of care. One study of completion rates of mental healthcare referrals suggests that longer waiting times are associated with a lower likelihood of patients completing the referral.

2. Specifications Denominator:

The total number of consumers newly requesting mental health services from a health plan during a specified 12-month reporting period

Numerator:

The total time between request for services and the first faceto-face contact with a mental health professional for individuals included in the denominator

Data sources:

Administrative data, patient contact/appointment data

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

Mental Health Statistics Improvement Program

Users:

American College of Mental Health Administration, Connecticut Department of Mental Health and Addiction Services, Delaware Health and Social Services, Kentucky Department for Mental Health and Mental Retardation Services, Maine Department of Mental Health, Nevada Department of Mental Health, Tennessee Department of Mental Health

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

❚ 191

Access Measures

TABLE 8–19.

Waiting time for mental health services (continued)

5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age, illness severity, mental health/ substance abuse comorbidity, emergent vs. non-emergent situations

References and Instruments Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Wilkinson LK, Blixen CE, Mallasch NI, et al: Mental health problems in hospitalbased clinics: patient profile and referral patterns. J Am Psychiatr Nurs Assoc 1:140–145, 1995

192

❚

TABLE 8–20.

IMPROVING MENTAL HEALTHCARE

Clinician response to phone contact

1. Summary

This measure assesses the proportion of individuals using mental health services who attempted to contact their clinician by phone and reported that their call was answered or returned within 24 hours.

Clinical rationale:

The healthcare system is placing increasing importance on quality of care from the consumer’s perspective. This trend reflects the results of consumer advocacy, respect for individual autonomy, and the adoption of a continuous quality improvement model that focuses on serving the customer. This measure addresses consumers’ need for timely access to their clinicians. There is no empirical evidence evaluating the association between timeliness of response and clinical outcomes.

2. Specifications Denominator:

Individuals completing a Mental Health Statistics Improvement Program (MHSIP) Consumer Survey who received a mental health service during a specified reporting period and indicated an attempt to contact their clinician or case manager by phone during the reporting period

Numerator:

Consumers from the denominator who reported that their call was returned within 24 hours (MHSIP survey question 7)

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

MHSIP

Users:

American College of Mental Health Administration

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinions

5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

Access Measures

TABLE 8–20.

❚ 193

Clinician response to phone contact (continued)

References and Instruments Bjoerkman T, Hansson L, Svensson B, et al: What is important in psychiatric outpatient care? Quality of care from the patient’s perspective. Int J Qual Health Care 7:355–362, 1995 Campbell J: How consumers/survivors are evaluating the quality of psychiatric care. Eval Rev 21:357–363, 1997 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Druss BG, Rosenheck RA, Stolar M: Patient satisfaction and administrative measures as indicators of the quality of mental health care. Psychiatr Serv 50:1053–1058, 1999 Hansson L, Bjorkman T, Berglund I: What is important in psychiatric inpatient care? Quality of care from the patient’s perspective. Qual Assur Health Care 5:41– 47, 1993

194

❚

TABLE 8–21.

IMPROVING MENTAL HEALTHCARE

Emergent phone access to managed behavioral healthcare organization (MBHO) clinicians

1. Summary

This measure assesses the proportion of incoming calls for emergency clinical inquiries that were answered by a clinician in 5 minutes or less.

Clinical rationale:

Health plans often have phone triage services to refer enrollees to providers and approve services for reimbursement. While initial calls may be screened by nonclinical personnel, clinically urgent calls may be triaged to a clinician. In the case of a clinical emergency, it is important that the triage is completed quickly. There is no research examining the association of rapid triage for urgent mental health services with outcomes.

2. Specifications Denominator:

Incoming emergency clinical inquiries (includes a lifethreatening injury to a health plan member, a serious injury to a member, adolescent elopement, a serious threat of violence or injury to others, or a serious threat of property destruction) to the MBHO call center during a quarterly period

Numerator:

The number of calls from the denominator that were answered by a clinician in 5 minutes or less

Data sources:

Utilization Management Database

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Standards:

At least 95% (Performance Measures Workgroup 1999); 95%–99% (Oss 1994)

Access Measures

TABLE 8–21.

❚ 195

Emergent phone access to managed behavioral healthcare organization (MBHO) clinicians (continued)

References and Instruments Oss ME: Industry analysis: what performance standards are used to evaluate managed behavioral health plans? OPEN MINDS, The Behavioral Health and Social Service Industry Analyst 7:4–5, 1994 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999

196

❚

TABLE 8–22.

IMPROVING MENTAL HEALTHCARE

Managed behavioral healthcare organization (MBHO) rate of live response

1. Summary

This measure assesses the proportion of incoming calls to a behavioral health organization that were placed on hold for a prolonged period.

Clinical rationale:

MBHOs serve a gate-keeping role in the provision of mental healthcare. Patients (or clinicians, on their behalf) contact MBHOs to access their insurance benefits and obtain referrals to clinicians. The proportion of phone requests addressed expeditiously is a commonly used measure of administrative process, albeit one node in a series of processes comprising access to care. This measure is not currently measured by the developing organization.

2. Specifications Denominator:

All incoming calls to the MBHO which were placed on hold during a quarterly reporting period

Numerator:

The number of calls from the denominator that were placed on hold for more than 45 seconds

Data sources:

Utilization Management Database

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Standards:

2% (Performance Measures Workgroup 1999) < 2% (Oss 1994)

References and Instruments Oss ME: Industry analysis: what performance standards are used to evaluate managed behavioral health plans? OPEN MINDS, The Behavioral Health and Social Service Industry Analyst 7:4–5, 1994 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999

Access Measures

TABLE 8–22.

❚ 197

Managed behavioral healthcare organization (MBHO) rate of live response (continued)

Sabin M: Telephone triage improves demand management effectiveness. Healthc Financ Manage 52:49–51, 1998

198

❚

TABLE 8–23.

IMPROVING MENTAL HEALTHCARE

Rapidity of managed behavioral healthcare organization (MBHO) call answering

1. Summary

This measure assesses the number of incoming calls to a behavioral health organization that are answered within five rings.

Clinical rationale:

MBHOs serve a gate-keeping role in the provision of mental healthcare. Patients (or clinicians, on their behalf) contact MBHOs to access their insurance benefits and obtain referrals to clinicians. The proportion of phone calls answered quickly is a commonly used measure of administrative process, albeit one node in a series of processes comprising access to care.

2. Specifications Denominator:

All incoming calls to an MBHO in one quarterly reporting period

Numerator:

The number of incoming calls that are answered within five rings

Data sources:

Utilization Management Database

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Users:

ValueOptions

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Standards:

At least 95% (Performance Measures Workgroup 1999) 95%–98% (Oss 1994)

References and Instruments Oss ME: Industry analysis: what performance standards are used to evaluate managed behavioral health plans? OPEN MINDS, The Behavioral Health and Social Service Industry Analyst 7:4–5, 1994 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999

Access Measures

TABLE 8–23.

❚ 199

Rapidity of managed behavioral healthcare organization (MBHO) call answering (continued)

Stirewalt CF, Linn MW, Godoy G, et al: Effectiveness of an ambulatory care telephone service in reducing drop-in visits and improving satisfaction with care. Med Care 20:739–748, 1982

200

❚

TABLE 8–24.

IMPROVING MENTAL HEALTHCARE

Unanswered utilization review calls

1. Summary

This measure assesses the number of calls to a behavioral healthcare organization for utilization review that were unanswered.

Clinical rationale:

Utilization management serves a gate-keeping role in the provision of mental healthcare. Patients (or clinicians, on their behalf) contact behavioral healthcare organizations to request mental health services. Because clinical problems can require immediate attention, the rate of unanswered phone calls is a common indicator of administrative process, albeit one node in a complex series of processes comprising access to care. There is no research assessing the association between utilization management phone answering and patient outcomes.

2. Specifications Denominator:

All incoming calls to a behavioral healthcare organization during one quarterly reporting period

Numerator:

The number of incoming calls in the denominator for utilization review that were unanswered

Data sources:

Utilization Management Database

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Users:

Comprehensive Behavioral Care, M-CARE

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

≤5% (Performance Measures Workgroup 1999) <2%–3% (Oss 1994)

Access Measures

TABLE 8–24.

❚ 201

Unanswered utilization review calls (continued)

References and Instruments Oss ME: Industry analysis: what performance standards are used to evaluate managed behavioral health plans? OPEN MINDS, The Behavioral Health and Social Service Industry Analyst 7:4–5, 1994 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999 Sabin M: Telephone triage improves demand management effectiveness. Healthc Financ Manage 52:49–51, 1998

202

❚

TABLE 8–25.

IMPROVING MENTAL HEALTHCARE

Timeliness of utilization management response

1. Summary

This measure assesses the proportion of incoming calls to a behavioral health organization that are answered within 30 seconds.

Clinical rationale:

Managed behavioral healthcare organizations (MBHOs) serve a gate-keeping role in the provision of mental healthcare. Patients (or clinicians, on their behalf) contact MBHOs to access their insurance benefits and obtain referrals to clinicians. The proportion of phone calls answered quickly is a commonly used measure of administrative process, albeit one node in a series of processes comprising access to care.

2. Specifications Denominator:

All incoming telephone calls to the MBHO in a 1-month period

Numerator:

Telephone calls from the denominator answered within 30 seconds

Data sources:

Utilization Management Database

Alternate versions:

Answer time: 60 seconds

3. Development Users:

Comprehensive Behavioral Care

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Standards:

30 seconds: 95% (Comprehensive Behavioral Care 2000)

References and Instruments Anctil B, Winters M: Linking customer judgments with process measures to improve access to ambulatory care. Jt Comm J Qual Improv 22:345–357, 1996 Comprehensive Behavioral Care: National Quality Council Workplan. Tampa, FL, Comprehensive Behavioral Care, 2000 Oss ME: What performance standards are used to evaluate managed behavioral health plans? OPEN MINDS, The Behavioral Health and Social Service Industry Analyst 7:4–5, 1994 Stirewalt CF, Linn MW, Godoy G, et al: Effectiveness of an ambulatory care telephone service in reducing drop-in visits and improving satisfaction with care. Med Care 20:739–748, 1982

❚ 203

Access Measures

TABLE 8–26.

Rate of appeals and denials for substance abuse treatment

1. Summary

This measure assesses the rate of denials and appeals for substance abuse and dependency treatment services within a health plan in a specified year.

Clinical rationale:

Health plans employ utilization review to serve a gate-keeping role in the provision of substance abuse treatment and other healthcare services. A patient (or their clinician) contacts the health plan to request a type of substance abuse services. Using information about the patient’s status and level of care criteria, plan personnel review the request and decide whether to authorize the care. If a preliminary request for services is denied, a patient typically has the opportunity to appeal. There has been little systematic research of the prevalence of service denials, appeals, or their administrative and clinical outcomes, although anecdotal case reports have been described.

2. Specifications Denominator:

The number of members enrolled in a health plan, per 1,000, in a specified year

Numerator:

The number of 1) denials and 2) appeals specifically related to substance abuse or chemical dependency treatment services in that year

Data sources:

Administrative data

3. Development Users:

Washington Circle Group

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

References and Instruments Domino ME, Salkever DS, Zarin DA, et al: The impact of managed care on psychiatry. Adm Policy Ment Health 26:149–157, 1998 Weisner C, McCarty D, Schmidt L: New directions in alcohol and drug treatment under managed care. Am J Manag Care 5:SP57–SP69, 1999 Young GP, Lowe RA: Adverse outcomes of managed care gatekeeping. Acad Emerg Med 4:1129–1136, 1997

204

❚

TABLE 8–27.

IMPROVING MENTAL HEALTHCARE

Access to appeal procedures

1. Summary

This measure assesses the proportion of plan beneficiaries who were denied services and indicated that they received information regarding the appeals process.

Clinical rationale:

Health plans employ utilization review to serve a gate-keeping role in the provision of substance abuse treatment and other healthcare services. A patient (or their clinician) contacts the health plan to request a type of substance abuse services. Using information about the patient’s status and level of care criteria, plan personnel review the request and decide whether to authorize the care. If a preliminary request for services is denied, a patient typically has the opportunity to appeal. There has been little systematic research of the prevalence of service denials, appeals, or their administrative and clinical outcomes, although anecdotal case reports have been described.

2. Specifications Denominator:

The number of consumers (or parents of consumers under age 18) who were denied services and received a biannual satisfaction survey

Numerator:

The number of survey respondents in the denominator who confirmed that they had received information regarding the appeals process

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

75% (Performance Measures Workgroup 1999)

Access Measures

TABLE 8–27.

❚ 205

Access to appeal procedures (continued)

References and Instruments Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999 Sbaraini S, Carpenter J: Barriers to complaints: a survey of mental health service users. J Manag Med 10:36–41, 1996

206

❚

TABLE 8–28.

IMPROVING MENTAL HEALTHCARE

Review of mental health service denials

1. Summary

This measure assesses the proportion of service denials that were reviewed and signed by a medical director at a managed behavioral healthcare organization (MBHO).

Clinical rationale:

Health plans employ utilization review to serve a gate-keeping role in the provision of substance abuse treatment and other healthcare services. A patient (or their clinician) contacts the health plan to request a type of substance abuse services. Using information about the patient’s status and level of care criteria, plan personnel review the request and decide whether to authorize the care. If a preliminary request for services is denied, a patient typically has the opportunity to appeal. There has been little systematic research of the prevalence of service denials, appeals, or their administrative and clinical outcomes, although anecdotal case reports have been described.

2. Specifications Denominator:

Service denials during a quarterly reporting period

Numerator:

The number of service denials from the denominator that were reviewed and signed by the MBHO’s medical director

Data sources:

Administrative data

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Users:

M-CARE

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

100% (Performance Measures Workgroup 1999)

Access Measures

TABLE 8–28.

❚ 207

Review of mental health service denials (continued)

References and Instruments Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999 Young GP, Lowe RA: Adverse outcomes of managed care gatekeeping. Acad Emerg Med 4:1129–1136, 1997

208

❚

TABLE 8–29.

IMPROVING MENTAL HEALTHCARE

Upheld appeals of managed behavioral healthcare organization (MBHO) service denials

1. Summary

This measure assesses the proportion of individuals who appealed a mental health services denial by an MBHO and received a decision overturning the denial.

Clinical rationale:

Health plans employ utilization review to serve a gate-keeping role in the provision of substance abuse treatment and other healthcare services. A patient (or their clinician) contacts the health plan to request a type of substance abuse services. Using information about the patient’s status and level of care criteria, plan personnel review the request and decide whether to authorize the care. If a preliminary request for services is denied, a patient typically has the opportunity to appeal. There has been little systematic research of the prevalence of service denials, appeals, or their administrative and clinical outcomes, although anecdotal case reports have been described.

2. Specifications Denominator:

The number of individuals enrolled in a health insurance plan that were denied service and appealed the decision during a quarterly reporting period

Numerator:

The number of people in the denominator whose service denial was overturned on appeal

Data sources:

Administrative data

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Standards:

Less than 2% (Performance Measures Workgroup 1999)

Access Measures

TABLE 8–29.

❚ 209

Upheld appeals of managed behavioral healthcare organization (MBHO) service denials (continued)

References and Instruments Cuffel B, McCullough J, Wade R, et al: Patients’ and providers’ perceptions of outpatient treatment termination in a managed behavioral health organization. Psychiatr Serv 51:469–473, 2000 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999 Young GP, Lowe RA: Adverse outcomes of managed care gatekeeping. Acad Emerg Med 4:1129–1136, 1997

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C H A P T E R

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Assessment Measures

211

212

❚

TABLE 9–1.

IMPROVING MENTAL HEALTHCARE

Assessment of major depressive symptoms

1. Summary

This measure assesses the proportion of patients with a diagnosis of major depression who have qualifying criteria documented in the medical record.

Clinical rationale:

The diagnosis of major depressive disorder is based on DSMIV criteria defining signs and symptoms, course of illness, and a threshold level of functional impairment. Clinical trials have demonstrated the responsiveness of this syndrome to medication and psychotherapy. Subthreshold or atypical variants of depression tend to respond less completely. Documentation of key criteria in a patient’s medical record provides support for a treatment plan, a basis for later comparison, and a means of communicating with other clinicians. Medical record documentation of positive signs and symptoms by the assessing clinician can provide a basis for later comparison and communicate important information to co-treaters. Nevertheless, documentation of presenting features of depression is often lacking in the medical record.

2. Specifications Denominator:

All members enrolled in a health plan diagnosed with major depression in a specified time period

Numerator:

All patients from the denominator for whom at least five of the nine diagnostic criteria for major depression are identified and documented at the time of, or prior to, the initial diagnosis (DSM-IV codes 296.2x, 296.3x, 296.5x)

Data sources:

Administrative data, medical record

3. Development Developer:

Joint Commission on Accreditation of Healthcare Organizations (JCAHO)

Stakeholders:

Accrediting organizations, researchers

Measure set:

JCAHO National Library of Healthcare Indicators

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Assessment Measures

TABLE 9–1.

❚ 213

Assessment of major depressive symptoms (continued)

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 1: Detection and Diagnosis. Rockville, MD, U.S. Department of Health and Human Services, 1993 Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5. Rockville, MD, U.S. Department of Health and Human Services, 1993 Joint Commission on Accreditation of Healthcare Organizations: National Library of Healthcare Indicators. Oakbrook Terrace, IL, Joint Commission on Accreditation of Healthcare Organizations, 1997 Joyce PR, Paykel ES: Predictors of drug response in depression. Arch Gen Psychiatry 46:89–99, 1989 McGrath PJ, Stewart JW, Harrison WM, et al: Predictive value of symptoms of atypical depression for differential drug treatment outcome. J Clin Psychopharmacol 12:197–202, 1992

214

❚

TABLE 9–2.

IMPROVING MENTAL HEALTHCARE

Assessment of psychiatric history in treating depression

1. Summary

This measure assesses the proportion of individuals who are admitted to a hospital with a diagnosis of depression and whose medical record includes an assessment of their psychiatric history.

Clinical rationale:

A psychiatric history is an important part of an inpatient admission assessment, with implications for diagnosis, treatment, and discharge planning. Clinical practice guidelines recommend that this assessment include previous episodes of psychiatric illness (including symptoms, functioning, and duration) and previous treatment (including dose, duration, and response).

2. Specifications Denominator:

Patients age 65 and older discharged from a hospital with a primary diagnosis of depression (unipolar or unspecified) during a specified period

Numerator:

The subset of patients in the denominator who received an assessment of their psychiatric history (including history of psychiatric diagnoses, symptoms, and treatment) before admission

Data sources:

Administrative data, medical record

3. Development Developer:

Wells et al. 1993

Stakeholders:

Clinicians, researchers

Measure set:

RAND Depressed Elderly

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Reliability testing:

Positive

Type:

Interrater reliability results available

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

80.9%, 2,746 elderly in 297 acute-care general medical hospitals (Wells et al. 1993)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, race, Medicaid status, and illness severity at admission

Assessment Measures

TABLE 9–2.

❚ 215

Assessment of psychiatric history in treating depression (continued)

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Palmer RM: Geriatric assessment. Med Clin North Am 83:1503–1523, 1999 Rothschild AJ: The diagnosis and treatment of late-life depression. J Clin Psychiatry 57:5–11, 1996 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993

216

❚

TABLE 9–3.

IMPROVING MENTAL HEALTHCARE

Assessment of psychosis in depression treatment

1. Summary

This measure assesses the proportion of patients age 65 or older admitted to a hospital with depression who are assessed for psychotic symptoms on admission.

Clinical rationale:

Psychotic symptoms such as delusions or hallucinations are present in approximately 10%–15% of major depressive episodes. The presence of psychotic symptoms has implications for treatment: psychotic depression is more than twice as likely to respond to a combination of antidepressant and antipsychotic medication than to antidepressant drugs alone. Research has shown that in many cases patients with psychotic depression do not receive an antipsychotic medication.

2. Specifications Denominator:

Patients age 65 and older discharged from a hospital with a primary diagnosis of depression (unipolar or unspecified) during a specified period

Numerator:

The subset of patients in the denominator with an assessment of psychosis, including an assessment for hallucinations, delusions, and bizarre behavior, documented in the admission note of the inpatient medical record

Data sources:

Administrative data, medical record

3. Development Developer:

Wells et al. 1993

Stakeholders:

Clinicians, researchers

Measure set:

RAND Depressed Elderly

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Reliability testing:

Positive

Type:

Interrater reliability results available

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

49.9%, 2,746 elderly in 297 acute-care general medical hospitals (Wells et al. 1993)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, race, Medicaid status, and illness severity at admission

Assessment Measures

TABLE 9–3.

❚ 217

Assessment of psychosis in depression treatment (continued)

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Kroessler D: Relative efficacy rates for therapies of delusional depression. Convuls Ther 1:173–182, 1985 Lacro JP, Jeste DV: Geriatric psychosis. Psychiatr Q 68:247–260, 1997 Mulsant B, Haskett R, Prudic J, et al: Low use of neuroleptic drugs in the treatment of psychotic major depression. Am J Psychiatry 154:559–561, 1997 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993

218

❚

TABLE 9–4. 1.

Summary

Clinical rationale:

IMPROVING MENTAL HEALTHCARE

Assessment of risk to self/others This measure assesses the proportion of patients with a new diagnosis of depression whose medical record includes an assessment of the patient’s potential to harm themselves or others. Individuals with major depression are at higher risk for suicide than individuals in the general population. Practice guidelines recommend that assessment of individuals with depression include evaluation of suicidal/homicidal ideation and associated risks. This information can inform decisions regarding level of care, clinical intervention, and community responsibilities. There are no research studies evaluating the association between documentation of suicidal/homicidal ideation assessment and clinical outcome.

2. Specifications Denominator:

The number of patients diagnosed with a depressive disorder during a formal evaluation (ICD-9 codes 290.2, 290.21, 296.2, 300.4, and 311.0.)

Numerator:

Patients from the denominator whose medical record of the formal evaluation contains specific documentation of the patient’s potential to harm self or others

Data sources:

Administrative data, medical record

3. Development Developer:

Joint Commission on Accreditation of Healthcare Organizations (JCAHO)

Stakeholders:

Accrediting organizations, researchers

Measure set:

JCAHO National Library of Healthcare Indicators

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Selected results:

53.5%, 2,746 elderly patients in 297 acute-care general medical hospitals (Wells et al. 1993)

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Flannery RB Jr, Hanson MA, Penk WE: Risk factors for psychiatric inpatient assaults on staff. J Mental Health Adm 21:24–31, 1994

Assessment Measures

TABLE 9–4.

❚ 219

Assessment of risk to self/others (continued)

Joint Commission on Accreditation of Healthcare Organizations: National Library of Healthcare Indicators. Oakbrook Terrace, IL, Joint Commission on Accreditation of Healthcare Organizations, 1997 Simon GE, VonKorff M: Suicide mortality among patients treated for depression in an insured population. Am J Epidemiol 147:155–160, 1998 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993

220

❚

TABLE 9–5.

IMPROVING MENTAL HEALTHCARE

Assessment of suicide status and risk in depression

1. Summary

This measure assesses the proportion of elderly individuals admitted to a hospital with a diagnosis of depression whose medical chart contains documentation of a suicide assessment within the first 2 days after admission.

Clinical rationale:

Depression is the most frequent psychiatric diagnosis among hospitalized elderly individuals. Depressed elderly individuals also experience higher rates of suicide than any other age group. Clinical practice guidelines recommend that an inpatient admission assessment include an assessment of suicide ideation and plan (and capacity to carry it out) as well as recent and prior attempts. This information contributes to an assessment of illness severity, risk, treatment needs, and observation status.

2. Specifications Denominator:

Patients age 65 and older discharged from a hospital with a primary diagnosis of depression (unipolar or unspecified) during a specified period

Numerator:

The subset of patients in the denominator with suicide attempt or ideation assessment (or its absence) documented in the medical record at the time of admission or during the first 2 days of hospital care

Data sources:

Administrative data, medical record

3.

Development

Developer:

Wells et al. 1993

Stakeholders:

Clinicians, researchers

Measure set:

RAND Depressed Elderly

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Reliability testing:

Positive

Type:

Interrater reliability results available

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

53.5%, 2,746 elderly in 297 acute-care general medical hospitals (Wells et al. 1993)

Assessment Measures

TABLE 9–5. Case-mix adjustment: Type:

❚ 221

Assessment of suicide status and risk in depression (continued) Yes Multivariate: age, sex, race, Medicaid status, and illness severity at admission

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 1: Detection and Diagnosis (Publication No 93– 0550). Washington, DC, U.S. Department of Health and Human Services, 1993 Callahan CM, Hendrie HC, Nienber NA, et al: Suicidal ideation among older primary care patients. J Am Geriatr Soc 44:1205–1209, 1996 Conwell Y: Suicide among elderly persons. Psychiatr Serv 46:563–564, 1995 Skoog I, Aevarsson O, Beskow J, et al: Suicidal feelings in a population sample of nondemented 85-year-olds. Am J Psychiatry 153:1015–1020, 1996 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993

222

❚

TABLE 9–6.

IMPROVING MENTAL HEALTHCARE

Follow-up assessment of depression

1. Summary

This measure assesses the proportion of patients seen in a 12-month period at a mental health clinic for a primary diagnosis of major depression for whom documentation of a systematic follow-up assessment is present in the medical record within 12 weeks of diagnosis.

Clinical rationale:

Clinical practice guidelines recommend that clinical assessment of depression include questions about signs and symptoms of the condition, including depressed mood, anhedonia, poor sleep, appetite, energy, and concentration as well as feelings of worthlessness and thoughts of suicide. Such an assessment should be performed initially and at subsequent visits to assess the course of the disorder, response to treatment, and possible need for changes in the treatment regimen.

2. Specifications Denominator:

All patients seen at least once in a mental health clinic (mental health primary care, psychiatry, psychology, substance abuse, posttraumatic stress disorder [PTSD], substance use disorder/PTSD, women’s stress disorder, psycho-geriatric, social work) in the past 12 months with a primary diagnosis of major depressive disorder (ICD-9-CM codes 296.2x or 296.3x)

Numerator:

Patients in the denominator for whom a systematic assessment documenting the presence or absence of at least five of the nine core DSM-IV symptoms of depression is present in the medical record within 12 weeks after initial recording of diagnosis

Data sources:

Administrative data, medical record

3. Development Developer:

Veterans Health Administration/Department of Defense (VHA/DOD)

Stakeholders:

Public sector payers and purchasers, employer purchasers, clinicians, delivery system managers, researchers

Measure set:

VHA/DOD Performance Measures for the Management of Major Depressive Disorder in Adults

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Assessment Measures

TABLE 9–6.

❚ 223

Follow-up assessment of depression (continued)

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, history of major depressive disorder, psychosis, substance abuse, lithium or antipsychotic use, number of visits in primary care

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Washington, DC, U.S. Department of Health and Human Services, 1993 Bull SA, Hu XH, Hunkeler EM, et al: Discontinuation of use and switching of antidepressants: influence of patient-physician communication. JAMA 288:1403– 1409, 2002 Frank E, Prien RF, Jarrett JB, et al: Conceptualization and rationale for consensus definitions of terms in major depressive disorder: response, remission, recovery, relapse, and recurrence. Arch Gen Psychiatry 48:851–855,1991 Veterans Health Administration/Department of Defense (VHA/DOD): VHA/ DOD Performance Measures for the Management of Major Depressive Disorder in Adults, Version 2.0. Washington, DC, Veterans Health Administration/ Department of Defense, 2000

224

❚

TABLE 9–7. 1.

Summary

Clinical rationale:

IMPROVING MENTAL HEALTHCARE

Tardive dyskinesia assessment with antipsychotic use This measure assesses the proportion of individuals prescribed an antipsychotic medication who receive an Abnormal Involuntary Movement Scale (AIMS) assessment at intake and every 6 months thereafter. Patients treated with antipsychotic medication are at risk of developing tardive dyskinesia (TD), an involuntary movement disorder. The disorder occurs at a rate of approximately 3%–4% per year among adult populations prescribed traditional antipsychotic medication and possibly to a lesser extent among those using atypical agents, although long-term data are not yet available. Practice guidelines recommend a periodic screening, at least every 6 months, to evaluate for the presence or progression of TD and to inform treatment decisions. This measure is not currently in use by the developing organization.

2. Specifications Denominator:

Total number of consumers enrolled in a health plan and prescribed antipsychotic medication at a specified point in time

Numerator:

The total number of consumers from the denominator who received an AIMS assessment at intake and every 6 months thereafter

Data sources:

Administrative data, medical record

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

98% (Performance Measures Workgroup 1999)

Assessment Measures

TABLE 9–7.

❚ 225

Tardive dyskinesia assessment with antipsychotic use (continued)

References and Instruments American Psychiatric Association: Tardive Dyskinesia: A Task Force Report of the American Psychiatric Association. Washington, DC, American Psychiatric Press, 1992 American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Benjamin S, Munetz MR: CMHC practices related to tardive dyskinesia screening and informed consent for neuroleptic drugs. Hosp Community Psychiatry 45:343–345, 1994 Guy W (ed): Abnormal Involuntary Movements Scale (AIMS) ECDEU Assessment Manual for Psychopharmacology (Publication ADM 76–338). Washington, DC, U.S. Department of Health, Education, and Welfare, 1976 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999 van Harten PN, Kahn RS: Tardive dystonia. Schizophr Bull 25:741–748, 1999

226

❚

TABLE 9–8.

IMPROVING MENTAL HEALTHCARE

Assessment for substance abuse problems of psychiatric patients

1. Summary

This measure assesses the proportion of patients who receive a psychiatric evaluation that includes a drug and alcohol use assessment.

Clinical rationale:

Substance abuse and dependence disorders are common comorbid conditions among people with a major mental illness and are associated with poorer patient outcomes. Studies have found that 25% of individuals with severe mental illness have current substance abuse or dependence and 50% will have a substance-related disorder in their lifetime. Substance-related disorders can present with psychiatric symptoms, complicate the presentation and treatment of mental disorders, and require concurrent treatment along with treatment of mental illness. Clinical practice guidelines recommend that psychiatric evaluation of a newly presenting patient include a thorough assessment of the patient’s alcohol and drug use.

2. Specifications Denominator:

Total number of patients in a plan who received psychiatric evaluations within a specified period of time

Numerator:

Number of patients in the denominator whose medical record indicates explicit evidence of assessment of current and/or past substance use disorders

Data sources:

Administrative data, medical record

3. Development Developer:

American Psychiatric Association

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

American Psychiatric Association Task Force on Quality Indicators

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

90% of patients age 15 and older (American Psychiatric Association 1999)

Assessment Measures

TABLE 9–8.

❚ 227

Assessment for substance abuse problems of psychiatric patients (continued)

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1999 Lehman AF, Myers CP, Corty E, et al: Prevalence and patterns of “dual diagnosis” among psychiatric patients. Compr Psychiatry 35:106–112, 1994 RachBeisel J, Scott J, Dixon L: Co-occurring severe mental illness and substance use disorders: a review of recent research. Psychiatr Serv 50:1427–1434, 1999 Siegfried N: A review of comorbidity: major mental illness and problematic substance use. Aust N Z J Psychiatry 32:707–717, 1998

228

❚

TABLE 9–9.

IMPROVING MENTAL HEALTHCARE

Screening for alcohol abuse in primary care

1. Summary

This measure assesses the proportion of surveyed health plan members who report being asked about alcohol use by a health plan clinician in the prior year.

Clinical rationale:

Alcohol abuse and dependence are prevalent public health problems in the United States, with high rates of morbidity, including reduced social functioning, reduced work productivity, poorer health status, and higher medical costs. These problems often go undetected and untreated. The U.S. Preventive Services Task Force recommends screening for drinking problems in the primary care setting on the basis of evidence demonstrating the effectiveness of detection coupled with brief counseling for non-dependent drinkers.

2. Specifications Denominator:

All members of a health plan who respond to a telephone or mail screening survey at a specified point in time

Numerator:

Those members who report being asked about alcohol use by a health plan clinician in the prior year

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Washington Circle Group

Stakeholders:

Public sector payers and purchasers, clinicians, managed care organizations, delivery system managers, researchers

Measure set:

Washington Circle Group Year 1 Performance Measures

Users:

Foundation for Accountability

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Health plan purchasing, health plan/provider choice by consumers, decisions by health plans about provider contracting

Assessment Measures

TABLE 9–9.

❚ 229

Screening for alcohol abuse in primary care (continued)

References and Instruments Conigliaro J, Lofgren RP, Hanusa BH: Screening for problem drinking: impact on physician behavior and patient drinking habits. J Gen Intern Med 13:251–256, 1998 Fielin DA, Reid MC, O’Connor PG: Screening for alcohol problems in primary care: a systematic review. Arch Intern Med 169:1977–1989, 2000 Friedman PD, McCullough D, Chin MH, et al: Screening and intervention for alcohol problems: a national survey of primary care physicians and psychiatrists. J Gen Intern Med 15:84–91, 2000 U.S. Preventive Services Task Force: Guide to Clinical Preventive Services. Baltimore, MD, Department of Health and Human Services, 1996 Washington Circle Group: Improving Performance Measurement by Managed Care Plans for Substance Abuse: Year 1 Report of the Washington Circle Group. Rockville, MD, Washington Circle Group, 1999

230

❚

TABLE 9–10. 1.

Summary

Clinical rationale:

IMPROVING MENTAL HEALTHCARE

Substance abuse assessment in schizophrenia This measure assesses the proportion of individuals discharged from a hospital with a primary diagnosis of schizophrenia whose inpatient admission or discharge assessment note includes an assessment of substance abuse or dependence. The prevalence of substance abuse in individuals with schizophrenia is nearly fivefold greater than the general population. In the inpatient setting, the prevalence of a current substance disorder among inpatients with schizophrenia has been estimated at 30%–50%. Despite these high rates, substance abuse and dependence are often not detected or documented among this population in the clinical setting. When documented, a positive assessment is often not followed up by a treatment plan or referral for treatment of the problem. Comorbid substance abuse has been associated with poorer treatment outcomes, poorer treatment compliance, homelessness, increased medical morbidity, violence, and greater use of crisis services.

2. Specifications Denominator:

All patients discharged from a hospital with a primary diagnosis of schizophrenia during a specified period of time

Numerator:

Patients from the denominator who have received an assessment of substance abuse or dependence (documentation in the inpatient admission assessment or discharge note of the presence or absence of current or past substance abuse or dependence, or documentation of an unsuccessful attempt to ascertain this information)

Data sources:

Administrative data, medical record

3. Development Developer:

Center for Quality Assessment and Improvement in Mental Health (CQAIMH)

Stakeholders:

Clinicians, researchers

Measure set:

CQAIMH Quality Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Research study

Assessment Measures

TABLE 9–10.

❚ 231

Substance abuse assessment in schizophrenia (continued)

References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Dixon L: Dual diagnosis of substance abuse in schizophrenia: prevalence and impact on outcomes. Schizophr Res 35(suppl):S93–S100, 1999 Drake RE, Alterman AI, Rosenberg SR: Detection of substance use disorders in severely mentally ill patients. Community Ment Health J 29:175–192, 1993 Schwartz LS, Lyons JS, Stulp F, et al: Assessment of alcoholism among dually diagnosed psychiatric inpatients. J Subst Abuse Treat 10:255–261, 1993

❚

232

TABLE 9–11.

IMPROVING MENTAL HEALTHCARE

Annual physical examination for persons with mental illness

1. Summary

This measure assesses the proportion of individuals using mental health services who have received a physical examination within the past 12 months.

Clinical rationale:

Individuals with severe and persistent mental illness have higher rates of medical comorbidity and have shorter life spans than the general population. Despite this, medical comorbidities often go undetected and undertreated in this population, even when in active psychiatric treatment. Untreated medical comorbidities are associated with greater functional impairment and lower mental health status. Clinical practice guidelines recommend that comprehensive psychiatric evaluations include a medical history and physical examination.

2.

Specifications

Denominator:

The total number of individuals receiving services for a primary psychiatric disorder during a specified 12-month reporting period

Numerator:

Individuals from the denominator whose medical record documents receipt of a physical examination within the specified 12-month period

Data sources:

Administrative data, medical record

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

Mental Health Statistics Improvement Program

Users:

American Psychiatric Association Rhode Island Department of Mental Health

Development:

Incomplete

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

Assessment Measures

TABLE 9–11.

❚ 233

Annual physical examination for persons with mental illness (continued)

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Dixon L, Postrado L, Delahanty J, et al: The association of medical comorbidity in schizophrenia with poor physical and mental health. J Nerv Ment Dis 187:496– 502, 1999 Druss BG, Rosenheck RA: Mental disorders and access to medical care in the United States. Am J Psychiatry 155:1775–1777, 1998 Jeste DV, Gladsjo JA, Lindamer LA, et al: Medical comorbidity in schizophrenia. Schizophr Bull 22:413–430, 1996 Rabinowitz J, Mark M, Popper M, et al: Physical illness among all discharged psychiatric inpatients in a national case register. J Ment Health Adm 24:82–89, 1997

234

❚

IMPROVING MENTAL HEALTHCARE

TABLE 9–12.

Assessment for medical problems of psychiatric patients

1. Summary

This measure assesses the proportion of adult patients receiving a psychiatric evaluation that includes an assessment of the patient’s medical history and current medical conditions.

Clinical rationale:

Clinical practice guidelines recommend that a psychiatric evaluation of a newly presenting patient include an assessment of the patient’s medical history and current medical conditions. Medical problems can present with psychiatric symptoms, represent complications of psychiatric conditions, and be contraindications to certain psychiatric treatments. In addition, research shows that individuals with severe and persistent mental illness have higher rates of physical disorders, lower rates of treatment, and shorter life spans than the general population. Although some studies have examined the adequacy of assessment of medical problems in psychiatric evaluations, there is little research assessing its impact on patient outcome.

2. Specifications Denominator:

All individuals age 18 and older who undergo a psychiatric evaluation during a specified period

Numerator:

Individuals from the denominator whose psychiatric evaluation includes a past medical history and current general medical condition

Data sources:

Administrative data, medical record

3.

Development

Developer:

American Psychiatric Association

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

American Psychiatric Association Practice Guidelines

Development:

Under development

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Jeste DV, Gladsjo JA, Lindamer LA, et al: Medical comorbidity in schizophrenia. Schizophr Bull 22:413–430, 1996

Assessment Measures

TABLE 9–12.

❚ 235

Assessment for medical problems of psychiatric patients (continued)

Karasu T, Waltzman S, Lindenmayer J, et al: The medical care of patients with psychiatric illness. Hosp Community Psychiatry 31:463–472, 1980 Maricle R, Hoffman W, Bloom J, et al: The prevalence and significance of medical illness among chronically mentally ill patients. Community Ment Health J 23:81– 90, 1987 Rabinowitz J, Mark M, Popper M, et al: Physical illness among all discharged psychiatric inpatients in a national case register. J Ment Health Adm 24:82–89, 1997

236

❚

TABLE 9–13.

IMPROVING MENTAL HEALTHCARE

Diagnostic evaluation of new cognitive impairment

1. Summary

This measure assesses the proportion of individuals newly diagnosed with dementia who receive a full battery of clinical tests within 30 days of the dementia diagnosis.

Clinical rationale:

Demographic projections foresee a rapid growth in the number of individuals age 65 and older in the coming years. With the expansion of this cohort comes increases in the incidence of dementia, posing challenges to clinicians with regard to detection, evaluation, treatment, and care management. Clinical practice guidelines recommend that individuals with new cognitive impairment receive a comprehensive diagnostic assessment to distinguish between reversible and irreversible etiologies and to identify opportunities for treatment.

2. Specifications Denominator:

The number of members in a plan newly diagnosed with dementia (DSM-IV codes 290.xx) during a specified period

Numerator:

The number of patients in the denominator who have received the following tests to diagnose and treat the dementia-related condition within 30 days of the initial diagnosis: evaluation should minimally include a history of onset and progression of symptoms; a complete physical and neurological examination; a psychiatric examination including a cognitive evaluation (e.g., Mini-Mental State Examination); a review of the patient’s medications; laboratory tests (i.e., complete blood count; blood chemistry battery including glucose, electrolytes, calcium, and kidney and liver function tests; measurement of vitamin B12 level; syphilis serology; thyroid function tests; and determination of erythrocyte sedimentation rate])

Data sources:

Administrative data, laboratory data/results, medical record

3.

Development

Developer:

American Psychiatric Association

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

American Psychiatric Association Task Force on Quality Indicators

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Assessment Measures

TABLE 9–13.

❚ 237

Diagnostic evaluation of new cognitive impairment (continued)

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

100% (American Psychiatric Association 1999)

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1999 Costa PT, Williams TF, Albert MS, et al: Recognition and Initial Assessment of Alzheimer’s Disease and Related Disorders: Clinical Practice Guideline No. 19 (AHCPR Publication No. 97–0702). Rockville, MD, Agency on Health Care Policy and Research, 1996 Somerfield MR, Weisman CS, Ury W, et al: Physician practices in the diagnosis of dementing disorders. J Am Geriatr Soc 39:172–175, 1991

238

❚

TABLE 9–14.

IMPROVING MENTAL HEALTHCARE

Examination of cognitive functioning for depression treatment

1. Summary

This measure assesses the proportion of elderly individuals admitted to a hospital with a diagnosis of depression whose medical record contains documentation of a cognitive assessment at the time of admission.

Clinical rationale:

Depression is the most frequent psychiatric diagnosis among hospitalized elderly individuals. Clinical practice guidelines recommend that a cognitive assessment be performed as part of an admission assessment of patients hospitalized for depression. Depression can present with impairment of cognitive status. Cognitive dysfunction can also be indicative of other psychiatric or medical conditions or adverse effects from treatment. A thorough cognitive assessment can also provide information about a patient’s level of functioning, serving as a baseline for subsequent assessment, informing treatment decisions, and providing information for discharge planning.

2. Specifications Denominator:

Patients age 65 and older discharged from a hospital with a primary diagnosis of depression (unipolar or unspecified) during a specified period

Numerator:

The subset of patients in the denominator who receive a cognitive status assessment at admission documented in the medical record, including an assessment of orientation to time, person, and place; an assessment concerning level of alertness or confusion; and an assessment of acute neurological abnormality or coma status (1=any assessment, 0=no assessment)

Data sources:

Administrative data, medical record

3. Development Developer:

Wells et al. 1994

Stakeholders:

Clinicians, researchers

Measure set:

RAND Depressed Elderly

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Reliability testing:

Positive

Type:

Interrater reliability results available

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Assessment Measures

TABLE 9–14.

❚ 239

Examination of cognitive functioning for depression treatment (continued)

Selected results:

74.3%, 2,746 elderly in 297 acute-care general medical hospitals (Wells et al. 1993)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, race, Medicaid status, and illness severity at admission

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Harvey PD, Powchik P, Parrella M, et al: Symptom severity and cognitive impairment in chronically hospitalized geriatric patients with affective disorders. Br J Psychiatry 170:369–374, 1997 Palmer RM: Geriatric assessment. Med Clin North Am 83:1503–1523, 1999 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993 Wells KB, Rogers WH, Davis LM, et al: Quality of care for depressed elderly prepost prospective payment system: differences in response across treatment settings. Med Care 32:257–276, 1994

240

❚

TABLE 9–15.

IMPROVING MENTAL HEALTHCARE

Heart sound examination for depressed inpatients

1. Summary

This measure assesses the proportion of elderly individuals admitted to a hospital with a diagnosis of depression whose medical chart contains documentation of a heart sound examination within the first 2 days after examination.

Clinical rationale:

Depression is the most frequent psychiatric diagnosis among hospitalized elderly individuals. Clinical practice guidelines recommend that a physical examination be performed as part of an admission assessment of patients hospitalized for depression. The examination contributes to an understanding of potential causes of psychiatric symptoms, potential comorbid medical problems, detection of adverse effects from treatment, or contraindications to certain treatments. Assessment of heart sounds is a routine, meaningful, and clearly documented component of a physical examination and can serve as an explicit “proxy” for physical examination performance. Older antidepressants are associated with adverse cardiac effects. In addition, depression has been shown to have a higher prevalence among individuals with some cardiac conditions.

2. Specifications Denominator:

Patients age 65 and older discharged from a hospital with a primary diagnosis of depression (unipolar or unspecified) during a specified period

Numerator:

The subset of patients in the denominator with an examination of heart sounds documented in the medical record at the time of admission or during the first 2 days of hospital care

Data sources:

Administrative data, medical record

3. Development Developer:

Wells et al. 1993

Stakeholders:

Clinicians, researchers

Measure set:

RAND Depressed Elderly

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Reliability testing:

Positive

Type: 5.

Interrater reliability results available

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Assessment Measures

TABLE 9–15.

❚ 241

Heart sound examination for depressed inpatients (continued)

Selected results:

55.1%, 2,746 elderly in 297 acute-care general medical hospitals (Wells et al. 1993)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, race, Medicaid status, and illness severity at admission

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Norquist G, Wells KB, Rogers WH, et al: Quality of care for depressed elderly patients hospitalized in the specialty psychiatric units or general medical wards. Arch Gen Psychiatry 52:695–702, 1995 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993

242

❚

TABLE 9–16. 1.

Summary

Clinical rationale:

IMPROVING MENTAL HEALTHCARE

Documentation of current medications at assessment This measure assesses the proportion of individuals initiating mental health treatment whose chart contains documentation of current medication use. Clinical practice guidelines recommend that an initial patient assessment include documentation of the patient’s current medications. This information can influence the differential diagnosis of psychiatric symptoms and subsequent treatment decisions. It can also facilitate communication among clinicians sharing a common patient record.

2. Specifications Denominator:

The number of individuals who initiate mental health treatment during a specified period of time

Numerator:

Consumers from the denominator whose chart contains documentation of current medication use that is entered within 24 hours of admission for inpatients and the day of the first appointment for outpatients

Data sources:

Administrative data, medical record

3. Development Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Baker JG, Shanfield SB, Schnee S: Using quality improvement teams to improve documentation in records at a community mental health center. Psychiatr Serv 51:239–242, 2000 Soreff S, Gulkin T, Pike JG: The evolving clinical chart: how it reflects and influences psychiatric and medical practice and the quality of care. Psychiatr Clin North Am 13:127–133, 1990

Assessment Measures

TABLE 9–17. 1.

Summary

Clinical rationale:

❚ 243

Medical transfer within 72 hours of admission This measure assesses the proportion of individuals hospitalized on a psychiatric inpatient unit who are transferred to a medical or surgical inpatient service within 72 hours of admission. Transfers from a psychiatric inpatient service to a general medical or surgical service typically occur when a physical condition requires acute inpatient care. Many of these transfers—even those occurring shortly after admission—are unavoidable and result from a change in the patient’s status after admission. Some may result from the failure to detect clinical problems that were present at admission, leading to the development of this indicator. There is little empirical data available regarding the prevalence of such transfers, their causes, or their association with service utilization or outcome.

2. Specifications Denominator:

Inpatient admissions to an adult inpatient psychiatric unit during a specified period of time

Numerator:

Patients from the denominator who are transferred to an inpatient medical or surgical unit within 72 hours of admission

Data sources:

Administrative data

3. Development Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Feister SJ, Shefferman MM: Medical problems in hospitalized psychiatric patients. New Dir Ment Health Serv 63:59–70, 1994 Popli AP, Hegarty JD, Siegel AJ, et al: Transfer of psychiatric inpatients to a general hospital due to adverse drug reactions. Psychosomatics 38:35–37, 1997

244

❚

TABLE 9–18. 1.

IMPROVING MENTAL HEALTHCARE

Neurological examination in depression treatment

Summary

Clinical rationale:

This measure assesses the proportion of elderly individuals admitted to a hospital with a diagnosis of depression whose medical record contains documentation of a neurological examination within the first 2 days of admission. Depression is the most frequent psychiatric diagnosis among hospitalized elderly individuals. Clinical practice guidelines recommend that a neurological examination be performed on admission for inpatients with depression. The examination can detect causes of psychiatric symptoms, potential comorbid neurological problems, and adverse effects from treatment.

2. Specifications Denominator:

Patients ages 65 and older discharged from a hospital with a primary diagnosis of depression (unipolar or unspecified) during a specified period

Numerator:

The subset of patients in the denominator who receive a neurological examination, including an examination of the pupils, deep tendon reflexes in limbs, and coordination or gait, documented in the medical record at the time of admission or during the first 2 days of hospital care

Data sources:

Administrative data, medical record

3.

Development

Developer:

Wells et al. 1993

Stakeholders:

Clinicians, researchers

Measure set:

RAND Depressed Elderly

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Reliability testing:

Mixed or fair

Type:

Interrater reliability results available

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

2,746 elderly in 297 acute-care general medical hospitals (Wells et al. 1993)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, race, Medicaid status, and illness severity at admission

Assessment Measures

TABLE 9–18.

❚ 245

Neurological examination in depression treatment (continued)

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Norquist G, Wells KB, Rogers WH, et al: Quality of care for depressed elderly patients hospitalized in the specialty psychiatric units or general medical wards. Arch Gen Psychiatry 52:695–702, 1995 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993

246

❚

TABLE 9–19.

IMPROVING MENTAL HEALTHCARE

Housing assessment for individuals with schizophrenia

1. Summary

This measure assesses the proportion of individuals diagnosed with schizophrenia whose housing quality was assessed.

Clinical rationale:

Studies indicate that patients with schizophrenia are more likely than the general population to have inadequate or unstable housing situations. Unstable housing situations have been associated with elevated psychiatric symptoms and higher rehospitalization rates and may lead to homelessness. Mental health clinicians can play a role in addressing this problem by assessing housing needs, adequacy of current housing, and advocacy and coordination of services.

2.

Specifications

Denominator:

Enrollees who had either one inpatient admission or two outpatient visits with a primary diagnosis of schizophrenia within a 12-month period

Numerator:

The number of individuals in the denominator whose housing quality was assessed, with medical record documentation indicating that a trained professional (e.g., social worker, visiting nurse) saw the quality of the individual’s housing and/or made an effort to modify the individual’s housing situation

Data sources:

Administrative data, medical record

3. Development Developer:

Popkin et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

39%–49%, 377 Utah Medicaid beneficiaries (Popkin et al. 1998)

References and Instruments Drake RE, Wallach MA, Teague GB, et al: Housing instability and homelessness among rural schizophrenic patients. Am J Psychiatry 148:330–336, 1991 Newman SJ: The housing and neighborhood conditions of persons with severe mental illness. Hosp Community Psychiatry 45:338–343, 1994

Assessment Measures

TABLE 9–19.

❚ 247

Housing assessment for individuals with schizophrenia (continued)

Popkin MK, Callies AL, Lurie N, et al: An instrument to evaluate the process of psychiatric care in ambulatory settings. Psychiatr Serv 48:524–527, 1997 Popkin MK, Lurie N, Manning W, et al: Changes in the process of care for Medicaid patients with schizophrenia in Utah’s prepaid mental health plan. Psychiatr Serv 49:518–523, 1998

248

❚

TABLE 9–20.

IMPROVING MENTAL HEALTHCARE

Independent living skills assessment for individuals with schizophrenia

1. Summary

This measure assesses the proportion of individuals in active inpatient or outpatient care for schizophrenia who received an assessment of independent-living skills over a 2-month period.

Clinical rationale:

Independent living is a goal for many individuals with schizophrenia. Assessments of independent-living skills can be used to identify service needs, shape treatment planning, and monitor progress toward independent living.

2. Specifications Denominator:

Enrollees who had either one inpatient admission or two outpatient visits with a primary diagnosis of schizophrenia within a 12-month period

Numerator:

Patients in the denominator who received an assessment of independent-living skills

Data sources:

Administrative data, medical record

3. Development Developer:

Popkin et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

84%–87%, 377 Utah Medicaid beneficiaries (Popkin et al. 1998)

References and Instruments Popkin MK, Callies AL, Lurie N, et al: An instrument to evaluate the process of psychiatric care in ambulatory settings. Psychiatr Serv 48:524–527, 1997 Popkin MK, Lurie N, Manning W, et al: Changes in the process of care for Medicaid patients with schizophrenia in Utah’s prepaid mental health plan. Psychiatr Serv 49:518–523, 1998

Assessment Measures

TABLE 9–21.

❚ 249

Assessment for psychosocial issues of psychiatric patients

1. Summary

This measure assesses the proportion of individuals age 18 and older receiving a psychiatric evaluation that includes a psychosocial/developmental history documented in the medical record.

Clinical rationale:

Clinical practice guidelines recommend that a psychiatric evaluation of a newly presenting patient include an assessment of the individual’s psychosocial and developmental history. Such an assessment typically includes information about developmental milestones, family and social relationships, educational and work history, and major life events, including a history of trauma. This assessment can inform diagnosis and treatment as well as provide information about patient strengths, vulnerabilities, and potential sources of support. There is little research on the adequacy of assessment of psychosocial issues in psychiatric evaluations or its impact on patient outcome.

2. Specifications Denominator:

All individuals age 18 and older who undergo a psychiatric evaluation during a specified period

Numerator:

Individuals in the denominator whose medical record documents a psychosocial/developmental history (components include major life events, history of abuse or trauma, levels of functioning in family and social roles)

Data sources:

Administrative data, medical record

3. Development Developer:

American Psychiatric Association

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

American Psychiatric Association Practice Guidelines

Development:

Under development

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996

250

❚

TABLE 9–22. 1.

Summary

Clinical rationale:

IMPROVING MENTAL HEALTHCARE

Comprehensiveness of inpatient psychosocial assessments This measure assesses the proportion of patients whose medical records include documentation of a comprehensive psychosocial assessment. A thorough psychosocial assessment of inpatients with psychiatric disorders is important for identifying a patient’s experiences, strengths, and deficits in areas such as education, finances, social support, and role functioning. The findings of a psychosocial assessment contribute to clinical decision making, discharge planning, and postdischarge services. There is no research evidence examining the relationship between the comprehensiveness of an inpatient psychosocial assessment and post-discharge outcome.

2. Specifications Denominator:

The total number of individuals admitted to an inpatient psychiatric setting during a specified time period

Numerator:

The number of individuals from the denominator whose medical record contains a psychosocial assessment that meets the following criteria for comprehensiveness: 1) addresses problems and strengths in social role functioning, 2) identifies environmental issues, including financial and other basic needs, 3) considers problems and strengths in the family and the social support systems and cultural factors, 4) spells out the implications for criteria 1– 3 for post-hospital planning, and 5) specifies the social work plan of intervention

Data sources:

Administrative data, medical record

3. Development Developer:

National Association of Social Workers (NASW)

Stakeholders:

Accrediting organizations, clinicians, provider organizations

Measure set:

NASW Clinical Indicators for Social Work

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement

Standards:

95% (NASW Commission on Health and Mental Health 1990)

Assessment Measures

TABLE 9–22.

❚ 251

Comprehensiveness of inpatient psychosocial assessments (continued)

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 National Association of Social Workers (NASW) Commission on Health and Mental Health: NASW Clinical Indicators for Social Work and Psychosocial Services in the Acute Psychiatric Hospital. Washington, DC, National Association of Social Workers, 1990 Vourlekis BS: Quality assurance indicators for monitoring social work in psychiatric acute care hospitals. Hosp Community Psychiatry 42:460–461, 1991

252

❚

TABLE 9–23. 1.

IMPROVING MENTAL HEALTHCARE

Timely inpatient psychosocial assessment

Summary

Clinical rationale:

2.

This measure assesses the proportion of patients whose medical records include documentation of a comprehensive psychosocial assessment within 5 days of hospital admission. Psychosocial assessment of inpatients with psychiatric disorders evaluates an individual’s experiences, strengths, and deficits in areas such as education, finances, social support, and role functioning. The findings contribute to clinical decision-making processes necessary for inpatient care, discharge planning, and post-discharge services. There is no research evidence evaluating the relationship between the timeliness of an inpatient psychosocial assessment and post-discharge outcome.

Specifications

Denominator:

The total number of individuals admitted to an inpatient psychiatric facility during a specified time period

Numerator:

Individuals from the denominator who have a comprehensive psychosocial assessment documented in the medical record within 5 days of hospital admission (assessment should evaluate problems and strengths in social role functioning, financial and other basic needs, social support systems, and cultural issues. Identified problems should be accompanied by proposed interventions and implications for discharge planning.)

Data sources:

Administrative data, medical record

3. Development Developer:

National Association of Social Workers (NASW)

Stakeholders:

Accrediting organizations, clinicians, provider organizations

Measure set:

NASW Clinical Indicators for Social Work

Development:

Incomplete

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement

Standards:

95% (NASW Commission on Health and Mental Health 1990)

Assessment Measures

TABLE 9–23.

❚ 253

Timely inpatient psychosocial assessment (continued)

References and Instruments American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 National Association of Social Workers (NASW) Commission on Health and Mental Health: NASW Clinical Indicators for Social Work and Psychosocial Services in the Acute Psychiatric Hospital. Washington, DC, National Association of Social Workers, 1990 Vourlekis BS: Quality assurance indicators for monitoring social work in psychiatric acute care hospitals. Hosp Community Psychiatry 42:460–461, 1991

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C H A P T E R

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Treatment Measures

255

256

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TABLE 10–1.

IMPROVING MENTAL HEALTHCARE

Family involvement in attention-deficit/ hyperactivity disorder (ADHD)

1. Summary

This measure assesses the proportion of individuals under age 18 with ADHD whose family members are actively involved in assessment and treatment.

Clinical rationale:

Family members or guardians have an important role in the psychiatric treatment of children. Families are an important source of information about the presentation and course of psychiatric problems and are important collaborators in treatment. In addition, families can benefit from education and support. Family-based interventions have been shown to be effective for a variety of child and adolescent disorders; however, the impact of unstructured, general family involvement on outcome has not been studied.

2. Specifications Denominator:

The number of individuals under age 18 in a health plan receiving treatment for a diagnosis of ADHD in a 3-month period

Numerator:

Individuals from the denominator with medical-record documentation of active involvement of family members or primary caretakers in the patient’s assessment and treatment, unless contraindicated

Data sources:

Administrative data, medical record

3.

Development

Developer:

ValueOptions

Stakeholders:

Consumers, clinicians, managed care organizations, delivery system managers

Measure set:

ValueOptions Corporate Quality Indicators

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Standards:

80% (ValueOptions 2000)

Treatment Measures

TABLE 10–1.

❚ 257

Family involvement in attention-deficit/ hyperactivity disorder (ADHD) (continued)

References and Instruments Anastopoulos AD, Barkley RA, Shelton TL: Family based treatment: psychosocial intervention for children and adolescents with attention-deficit/hyperactivity disorder, in Psychosocial Treatments for Child and Adolescent Disorders: Empirically Based Strategies for Clinical Practice. Edited by Hibbs E, Jensen PS. Washington, DC, American Psychological Association, 1996, pp 267–284 Dulcan M: Practice parameters for the assessment and treatment of children, adolescents, and adults with attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry 36(suppl):85S–121S, 1997 Estrada AU, Pinsof WM: The effectiveness of family therapies for selected behavioral disorders of childhood. J Marit Fam Ther 21:403–440, 1995 ValueOptions: Corporate Quality Management, Quality Indicator Methodology Manual. Norfolk, VA, ValueOptions, 2000

258

❚

TABLE 10–2.

IMPROVING MENTAL HEALTHCARE

Stimulant medication treatment for attentiondeficit/hyperactivity disorder (ADHD)

1. Summary

This measure assesses the proportion of children with a diagnosis of ADHD who receive a trial of stimulant medication at appropriate dosage and duration.

Clinical rationale:

ADHD is a common psychiatric condition with an estimated prevalence between 3% and 6% among school-aged children in the United States. Evidence-based treatment options for ADHD include medication, environmental and behavioral modification, and interventions addressing skill deficits or psychological issues. Studies have shown that stimulant medication is relatively safe and efficacious for short-term treatment of inattentiveness, impulsivity, and hyperactivity. Smaller effects were seen for short-term learning and achievement. Research on longer-term outcomes are inconclusive. Patient and family preferences play an important role in selection among treatment options for ADHD.

2.

Specifications

Denominator:

The total number of children enrolled in a health plan with a service-related diagnosis of ADHD, moderate or severe subtype, over a specified period

Numerator:

Those children from the denominator who received a trial on stimulant medication with appropriate dosage and duration during a specified time period

Data sources:

Administrative data, medical record

3. Development Developer:

American Psychiatric Association (APA)

Stakeholders:

Accrediting organizations, clinicians, researchers, provider organizations

Measure set:

APA Quality Indicators for Children

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

75% (American Psychiatric Association 2000)

Treatment Measures

TABLE 10–2.

❚ 259

Stimulant medication treatment for attentiondeficit/hyperactivity disorder (ADHD) (continued)

References and Instruments American Psychiatric Association Task Force on Quality Indicators for Children: Workbook of Quality Indicators for Children. Washington, DC, American Psychiatric Association, 2000 Dulcan M: Practice parameters for the assessment and treatment of children, adolescents, and adults with attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry 36(suppl):85S–121S, 1997 Goldman LS, Genel M, Bezman RJ, et al: Diagnosis and treatment of attentiondeficit/hyperactivity disorder. JAMA 279:1100–1107, 1998 Greenhill LL, Halperin JM, Abikoff H: Stimulant medications. J Am Acad Child Adolesc Psychiatry 38:503–512, 1999 Kaplan HI, Sadock BJ (eds): Comprehensive Textbook of Psychiatry VI, Vol 2. Baltimore, MD, Williams and Wilkins, 1995

260

❚

TABLE 10–3.

IMPROVING MENTAL HEALTHCARE

Blood level monitoring with mood stabilizers

1. Summary

This measure examines the proportion of patients with a primary or secondary diagnosis of bipolar disorder who received blood level monitoring at least once during a 12month period.

Clinical rationale:

Lithium, valproic acid (Depakote), and carbamazepine (Tegretol) are used to provide mood stabilization for bipolar disorder and other conditions. Randomized controlled trials have shown these medications to be most effective within a range of concentrations in the blood, generally 0.8–1.4 mmol/L for lithium and 45–125 µg/L for valproic acid. Higher blood levels can cause side effects that impair patient functioning and drug compliance. Levels lower than the recommended range are less effective. Practice guidelines recommend ongoing monitoring of drug levels and dosage adjustment to maintain a drug level within these ranges. There is less empirical evidence in regard to the frequency of monitoring needed. Guidelines generally recommend blood level monitoring every 3–6 months for lithium and every 6–12 months for valproic acid and carbamazepine.

2. Specifications Denominator:

The number of members enrolled in a health plan, age 18–64, with two or more service-based claims for bipolar disorder and at least one claim for lithium, valproic acid, or carbamazepine in at least three out of four quarters (the same drug in each quarter) of a 12-month period, excluding those individuals who were hospitalized for 30 or more days during the same 12-month period

Numerator:

Patients included in the denominator who have received serum drug level monitoring for a mood stabilizer at least once during a 12-month period

Data sources:

Administrative data, laboratory data, pharmacy data

3. Development Developer:

Marcus et al. 1999

Stakeholders:

Clinicians, researchers

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Treatment Measures

TABLE 10–3.

❚ 261

Blood level monitoring with mood stabilizers (continued)

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

63.5% lithium, 57.6% valproic acid, 57.8% carbamazepine, 718 Medicaid patients (Marcus et al. 1999)

References and Instruments American Psychiatric Association: Practice guideline for the treatment of patients with bipolar disorder. Am J Psychiatry 151(suppl):1–36, 1994 Bowden CL, Janicak PG, Orsulak P, et al: Relation of serum valproate concentration to response in mania. Am J Psychiatry 153:765–770, 1996 Gelenberg AJ, Kane JM, Keller MB, et al: Comparison of standard and low serum levels of lithium for maintenance treatment of bipolar disorder. N Engl J Med 321:1489–1493, 1989 Marcus S, Olfson M, Pincus H, et al: Therapeutic drug monitoring of mood stabilizers in Medicaid patients with bipolar disorder. Am J Psychiatry 156:1014– 1018, 1999

262

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TABLE 10–4.

IMPROVING MENTAL HEALTHCARE

Inpatient lithium level testing

1. Summary

This measure assesses the proportion of inpatients receiving lithium whose lithium blood levels are above the therapeutic range or have not been documented.

Clinical rationale:

Lithium is an efficacious treatment for acute and maintenance phases of bipolar disorder. Randomized controlled trials and other studies have shown that lithium is most effective within a “therapeutic window” or range of concentrations in the blood of 0.5–1.5 mEq/L. Higher blood levels can cause side effects that reduce drug compliance and impair patient functioning, while levels below the recommended range are associated with lower rates of remission and greater likelihood of relapse.

2. Specifications Denominator:

The total number of inpatients receiving lithium during the course of their hospital stay

Numerator:

Those individuals from the denominator who do not have a documented lithium blood level or whose highest measured level exceeds a specific threshold

Data sources:

Administrative data, medical record, pharmacy data

3.

Development

Developer:

Joint Commission on Accreditation of Healthcare Organizations

Stakeholders:

Accrediting organizations, researchers

Measure set:

National Library of Healthcare Indicators

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

References and Instruments Apter JT: Side effects and toxicity of lithium. J Fam Pract 15:1101–1106, 1982 Gelenberg AJ, Carroll JA, Baudhuin MG, et al: The meaning of lithium levels in maintenance therapy of mood disorders: a review of the literature. J Clin Psychiatry 50(suppl):17–22, 1989 Gelenberg AJ, Kane JM, Keller MB, et al: Comparison of standard and low serum levels of lithium for maintenance treatment of bipolar disorder. N Engl J Med 321:1489–1493, 1989 Gitlin MJ: Lithium-induced renal insufficiency. J Clin Psychopharmacol 13:276–279, 1993

Treatment Measures

TABLE 10–4.

❚ 263

Inpatient lithium level testing (continued)

Joint Commission on Accreditation of Healthcare Organizations: National Library of Healthcare Indicators. Oakbrook Terrace, IL, Joint Commission on Accreditation of Healthcare Organizations, 1997

264

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TABLE 10–5.

IMPROVING MENTAL HEALTHCARE

Side effect monitoring with mood stabilizers

1. Summary

This measure assesses the proportion of patients treated for bipolar disorder with a mood stabilizer who receive appropriate laboratory tests for adverse drug effects at least once during a 12-month period.

Clinical rationale:

Controlled studies have established the effectiveness of mood stabilizers for bipolar disorder and other conditions; however, they have also identified potential for adverse drug effects on specific organ systems. Valproate (Depakote) and carbamazepine (Tegretol) can cause thrombocytopenia, hypothyroidism, and in rare cases hepatitis and pancreatitis. Because of the potential for these effects, practice guidelines recommend annual blood tests to monitor blood cell counts and liver enzyme levels. Lithium can cause polyuria, renal dysfunction, and hypothyroidism, giving rise to recommendations to monitor blood urea nitrogen, creatine, and thyroid function via blood tests every 6–12 months. Monitoring can lead to early detection, changes in dosing or medication, and in some cases clinical intervention. There is little empirical evidence underlying the frequency of testing.

2. Specifications Denominator:

The number of members enrolled in a health plan, ages 18–64, with two or more service-based claims for bipolar disorder and at least one claim for lithium, valproic acid, or carbamazepine in at least three out of four quarters (the same drug in each quarter) of a 12-month period, excluding those individuals who were hospitalized for 30 or more days during the same 12-month period

Numerator:

Patients from the denominator who have undergone complete blood count (valproate/carbamazepine), liver (valproate/carbamazepine), thyroid, and renal function testing (lithium) at least once in the 12-month period

Data sources:

Administrative data, laboratory data, pharmacy data

3.

Development

Developer:

Marcus et al. 1999

Stakeholders:

Clinicians, researchers

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Treatment Measures

TABLE 10–5. Selected results:

❚ 265

Side effect monitoring with mood stabilizers (continued) Thyroid function: 45.9%; renal function: 4.2%; complete blood count: 56.4%; liver function: 46.7% among valproate users and 44.9% among carbamazepine users (Marcus et al. 1999)

References and Instruments American Psychiatric Association: Practice guideline for the treatment of patients with bipolar disorder. Am J Psychiatry 151(suppl):1–36, 1994 Baldessarini RJ: Chemotherapy in Psychiatry, Revised Edition. Cambridge, MA, Harvard University Press, 1985 Marcus S, Olfson M, Pincus H, et al: Therapeutic drug monitoring of mood stabilizers in Medicaid patients with bipolar disorder. Am J Psychiatry 156:1014– 1018, 1999

266

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TABLE 10–6. 1.

Summary

Clinical rationale:

IMPROVING MENTAL HEALTHCARE

Use of mood stabilizers for bipolar disorder This measure assesses the proportion of individuals ages 18 and older diagnosed with bipolar disorder and experiencing an acute manic episode who receive lithium, valproic acid, or carbamazepine. Bipolar disorder, which is manifested by episodes of mania and depression, can have a deleterious impact on a patient’s personal, social, and occupational functioning. Randomized controlled studies show that the mood stabilizers lithium, valproate, and carbamazepine are effective in treating acute symptoms and decreasing the likelihood of relapse after remission. Untreated bipolar disorder is common, with substantial rates of noncompliance with treatment recommendations. The contribution of clinician practices to the underuse of mood stabilizers for this population is not well understood.

2. Specifications Denominator:

All members of a plan, ages 18 and older, diagnosed with bipolar disorder, acute manic episode, during a specified period

Numerator:

Plan members from the denominator who receive lithium, valproic acid, or carbamazepine during a specified interval

Data sources:

Administrative data, pharmacy data

3. Development Developer:

American Psychiatric Association (APA)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

APA Task Force on Quality Indicators

Development:

Under development

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

90% (American Psychiatric Association 1999)

References and Instruments American Psychiatric Association Workgroup on Bipolar Disorder: Practice Guideline for Treatment of Patients With Bipolar Disorder. Washington, DC, American Psychiatric Association, 1996 American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1999

Treatment Measures

TABLE 10–6.

❚ 267

Use of mood stabilizers for bipolar disorder (continued)

Blanco C, Laje G, Olfson M, et al: Trends in the treatment of bipolar disorder by outpatient psychiatrists. Am J Psychiatry 159:1005–1010, 2002 Davis JM, Janicak PG, Hogan DM: Mood stabilizers in the prevention of recurrent affective disorders: a meta-analysis. Acta Psychiatr Scand 100:406–417, 1999 The Expert Consensus Panel for Bipolar Disorder: Treatment of bipolar disorder. J Clin Psychiatry 57(suppl):2–87, 1996

268

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TABLE 10–7.

IMPROVING MENTAL HEALTHCARE

Adequacy of antidepressant dosage for depressed elderly

1. Summary

This measure assesses the proportion of depressed elderly inpatients discharged who receive an antidepressant medication below the recommended minimum dosage for this age group.

Clinical rationale:

Epidemiologic studies have found depression to occur in approximately 15% of community residents over age 65. Depression is associated with poor personal and social functioning as well as increased rates of medical morbidity and suicide. Randomized controlled studies have shown that antidepressant drugs administered within a therapeutic range can effectively treat depression among elderly patients. In general, lower dosages are recommended for elderly patients, who typically metabolize medications more slowly and can be more sensitive to side effects. Subtherapeutic dosages have been observed in studies of the quality of depression care.

2. Specifications Denominator:

The total number of patients ages 65 or older who are discharged from a hospital with a diagnosis of depression (unipolar or unspecified) and receive antidepressant medication

Numerator:

Those patients from the denominator who are prescribed a daily dose of antidepressant medication below the dosage recommended for elderly patients (< 50 mg for nortriptyline and nomifensine, <20 mg for protriptyline, <75 mg for doxepin, amitriptyline, amoxapine, desipramine, trazodone, imipramine, maprotiline, and trimipramine)

Data sources:

Administrative data, medical record

3. Development Developer:

Wells et al. 1994

Stakeholders:

Clinicians, researchers

Measure set:

RAND Prospective Payment Study

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Reliability testing:

Positive

Type:

Interrater reliability results available

Treatment Measures

TABLE 10–7.

❚ 269

Adequacy of antidepressant dosage for depressed elderly (continued)

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

32.5%, 2,746 elderly patients in 297 acute-care general medical hospitals (Wells et al. 1994)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, race, Medicaid status, and illness severity at admission

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Gram LF: Inadequate dosing and pharmacokinetic variability as confounding factors in assessment of efficacy of antidepressants. Clin Neuropharmacol 13(suppl):S35–S44, 1990 Streim JE, Oslin DW, Katz IR, et al: Drug treatment of depression in frail elderly nursing home residents. Am J Geriatr Psychiatry 8:150–159, 2000 Wells K, Norquist G, Benjamin B, et al: Quality of antidepressant medications prescribed at discharge to depressed elderly patients in general medical hospitals before and after prospective payment system. Gen Hosp Psychiatry 16:4–15, 1994 Wells K, Katon W, Rogers B, et al: Use of minor tranquilizers and antidepressant medications by depressed outpatients: results from the Medical Outcomes Study. Am J Psychiatry 151:694–700, 1994

270

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TABLE 10–8.

IMPROVING MENTAL HEALTHCARE

Adequacy of antidepressant dosage

1. Summary

This measure assesses the proportion of patients newly treated for depression with an antidepressant medication who received an adequate dosage.

Clinical rationale:

Depressive disorders can impair personal, social, and family functioning, decrease work productivity, and increase the risk of suicide. Major depression can be treated effectively with antidepressant medications, but research suggests a minimum dosage is required for these medications to be effective. Studies have shown that a substantial proportion of patients receive subtherapeutic dosages in clinical practice.

2. Specifications Denominator:

The number of primary care patients between the ages of 18 and 75 who are newly prescribed an antidepressant (i.e., no previous antidepressant prescriptions for 120 days) for a diagnosis of major depression

Numerator:

Those patients from the denominator who received an adequate antidepressant dosage for at least 4 consecutive weeks during a specified time period (age 18–60: 100 mg of imipramine, amitryptyline, doxepin, desipramine, trazodone, amoxapine, maprotiline, or trimipramine; 75 mg of nortriptyline; 30 mg of protriptyline; or 20 mg of fluoxetine. Age over 60: 75 mg of imipramine, amitryptyline, doxepin, desipramine, trazodone, amoxapine, maprotiline, or trimipramine; 50 mg of nortriptyline; 20 mg of proptriptyline; or 10 mg of fluoxetine.)

Data sources:

Administrative data, medical record, pharmacy data

3. Development Developer:

Katon et al. 1992

Stakeholders:

Clinicians, researchers

Measure set:

Antidepressant Treatment in Primary Care

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

Reliability testing:

Positive

Type: Validity testing: Type:

Interrater reliability results available Positive Comparison with the results of other methods or measures, gold standard validity testing

Treatment Measures

TABLE 10–8.

❚ 271

Adequacy of antidepressant dosage (continued)

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

27.9%–37.1%, 119 primary care patients (Katon et al. 1992)

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age, sex, education, marital status, employment, income level

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Katon W, von Korff M, Lin E, et al: Adequacy and duration of antidepressant treatment in primary care. Med Care 30:67–76, 1992 Simon G, Lin EHB, Katon W, et al: Outcomes of “inadequate” treatment in primary care. J Gen Intern Med 10:663–670, 1995 Wells K, Katon W, Rogers B, et al: Use of minor tranquilizers and antidepressant medications by depressed outpatients: results from the Medical Outcomes Study. Am J Psychiatry 151:694–700, 1994

272

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TABLE 10–9.

IMPROVING MENTAL HEALTHCARE

Adequacy of antidepressant dosing and duration

1. Summary

This measure assesses the proportion of primary care patients with major depression who receive antidepressant medication at the recommended dosage and duration for acute-phase treatment.

Clinical rationale:

Depression among primary care patients is undetected or undertreated in a substantial proportion of cases. Inadequate pharmacotherapy includes subthreshold antidepressant drug dosages and insufficient treatment durations. Research shows that individuals with major depression who receive medication treatment concordant with Agency for Healthcare Research and Quality (AHRQ) guidelines for dosage and duration are more likely to achieve remission than those who do not.

2. Specifications Denominator:

All patients seen in primary care during a specified period who had major depression based on a structured assessment administered independent of the clinical visit

Numerator:

Patients from the denominator who are treated with an antidepressant medication within the range recommended by AHRQ practice guidelines at least 75% of the days for at least 8 weeks

Data sources:

Medical record, pharmacy data

3. Development Developer:

Rost et al. 1995

Stakeholders:

Researchers

Measure set:

Major depression in rural family practice

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

Reliability testing:

Positive

Type:

Interrater reliability results available

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

28.9%, rural primary care patients (Rost et al. 1995)

Case-mix adjustment:

Yes

Type:

Multivariate

Treatment Measures

TABLE 10–9.

❚ 273

Adequacy of antidepressant dosing and duration (continued)

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Rost K, Williams C, Wherry J, et al: The process and outcomes of care for major depression in rural family practice settings. J Rural Health 11:114–121, 1995 Schulberg HC, Block MR, Madonia MJ, et al: The “usual care” of major depression in primary care practice. Arch Fam Med 6:334–339, 1997 Wells K, Katon W, Rogers B, et al: Use of minor tranquilizers and antidepressant medications by depressed outpatients: results from the Medical Outcomes Study. Am J Psychiatry 151:694–700, 1994

274

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IMPROVING MENTAL HEALTHCARE

TABLE 10–10. Adequacy of antidepressant drug dosing 1.

Summary

Clinical rationale:

This measure assesses the proportion of patients ages 18 and older with a diagnosis of major depression, moderate to severe, who are receiving antidepressant medication within the recommended therapeutic dosage range. Major depressive disorder affects 3.7%–10.3% of adult Americans over a 12-month period. Depression can impair personal, social, occupational, and family functioning; lower quality of life; and increase the risk of suicide. Antidepressant medications provide effective treatment for the condition, but research has shown these agents to be most effective within a therapeutic range of dosages. Lower dosages may lead to inadequate treatment response, whereas higher dosages may produce side effects without greater efficacy. Studies have shown that many patients receive subtherapeutic dosages in treatment.

2. Specifications Denominator:

The number of patients ages 18 and older with a diagnosis of major depression (moderate or severe) during a specified period

Numerator:

Patients included in the denominator who receive an appropriate dosage (i.e., within therapeutic range) of antidepressant medication

Data sources:

Administrative data, pharmacy data

3. Development Developer:

American Psychiatric Association (APA)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

APA Task Force on Quality Indicators

Development:

Under development

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Selected results:

61% (Wells et al. 1994)

Standards:

75% (American Psychiatric Association 1999)

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993

Treatment Measures

❚ 275

TABLE 10–10. Adequacy of antidepressant drug dosing (continued) American Psychiatric Association Work Group on Major Depressive Disorder: Practice Guideline for Major Depressive Disorder in Adults. Washington, DC, American Psychiatric Association, 1996 American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1999 Wells K, Katon W, Rogers B, et al: Use of minor tranquilizers and antidepressant medications by depressed outpatients: results from the Medical Outcomes Study. Am J Psychiatry 151:694–700, 1994

276

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–11. Antidepressant initiation shortly before discharge 1. Summary

This measure assesses the proportion of elderly inpatients discharged with depression and a prescribed antidepressant who were started on an antidepressant within 48 hours before discharge.

Clinical rationale:

Depression is the most frequent diagnosis among hospitalized elderly individuals, with an estimated prevalence among inpatients of 6%–12%. The condition is associated with poor personal, social, and family functioning and increased rates of medical morbidity but is often undetected or inadequately treated. Randomized controlled trials show antidepressant medications to be effective for this population. Some published treatment recommendations advise that antidepressants not be started shortly before hospital discharge. Elderly patients can be particularly sensitive to medication side effects, and monitoring can indicate whether adjustment is needed. One study found that falls among elderly patients were increased after discharge from inpatient medical care and significantly associated with tricyclic antidepressant treatment use. The influence of newer antidepressants, with improved side effect profiles, on post-hospital adverse events and the need for inpatient monitoring has not been studied.

2. Specifications Denominator:

The number of patients ages 65 or older who are discharged from a hospital with a primary diagnosis of depression (unipolar or unspecified) and prescribed antidepressant medication

Numerator:

Those patients from the denominator who began the antidepressant medication within 48 hours before discharge

Data sources:

Administrative data, medical record

3. Development Developer:

Wells et al. 1994

Stakeholders:

Clinicians, researchers

Measure set:

RAND Prospective Payment Study

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Reliability testing:

Positive

Type:

Interrater reliability results available

Treatment Measures

❚ 277

TABLE 10–11. Antidepressant initiation shortly before discharge (continued) Validity testing: Type:

Positive Comparison with the results of other methods or measures

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

6.9%, 2,746 elderly (Wells et al. 1994)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, race, Medicaid status, and illness severity at admission

References and Instruments Katz MM, Koslow SH, Frazier A: Onset of antidepressant activity: reexamining the structure of depression and multiple actions of drugs. Depress Anxiety 4:257–267, 1996–1997 Mahoney JE, Palta M, Johnson J, et al: Temporal association between hospitalization and rate of falls after discharge. Arch Intern Med 160:2788–2795, 2000 Pollok BG: Adverse reactions of antidepressants in elderly patients. J Clin Psychiatry 60(suppl):4–8, 1999 Wells K, Norquist G, Benjamin B, et al: Quality of antidepressant medications prescribed at discharge to depressed elderly patients in general medical hospitals before and after prospective payment system. Gen Hosp Psychiatry 16:4–15, 1994

278

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IMPROVING MENTAL HEALTHCARE

TABLE 10–12. Sedating antidepressants in the elderly 1. Summary

This measure assesses the proportion of elderly inpatients with a primary diagnosis of depression who are prescribed a sedating antidepressant medication at discharge.

Clinical rationale:

Although elderly individuals can be effectively treated with antidepressant medications, they are at greater risk of adverse drug reactions due to the physiological changes associated with the aging process. In particular, antidepressants with strong anticholinergic effects (e.g., imipramine, amitriptyline, and doxepin) are not recommended for ongoing use in the elderly because they can cause orthostatic hypotension, sedation, and confusion. Use of these agents has been associated with high rates of adverse effects, including falls, among elderly patients.

2. Specifications Denominator:

The number of inpatients age 65 or older discharged with a diagnosis of depression (unipolar or unspecified) who are prescribed antidepressant medication

Numerator:

Those patients from the denominator who are treated with doxepin, amitriptyline, maprotiline, or trimipramine

Data sources:

Administrative data, medical record

3. Development Developer:

Wells et al. 1994

Stakeholders:

Clinicians, researchers

Measure set:

RAND Prospective Payment Study

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Reliability testing:

Positive

Type: Validity testing: Type:

Interrater reliability results available Mixed or fair Comparison with the results of other methods or measures

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

43.4%, 2,746 elderly patients in 297 acute-care general medical hospitals (Wells et al. 1994)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, race, Medicaid status, and illness severity at admission

Treatment Measures

❚ 279

TABLE 10–12. Sedating antidepressants in the elderly (continued) References and Instruments American Psychiatric Association Work Group on Major Depressive Disorder: Practice Guideline for Major Depressive Disorder in Adults. Washington, DC, American Psychiatric Association, 1996 Dunner DL, Cohn JB, Walshe T III, et al: Two combined multicenter double-blind studies of paroxetine and doxepin in geriatric patients with major depression. J Clin Psychiatry 53(suppl):57–60, 1992 Lebowitz BD, Pearson JL, Schneider LS, et al: Diagnosis and treatment in late life: consensus statement update. JAMA 278:1186–1190, 1997 Mahoney JE, Palta M, Johnson J, et al: Temporal association between hospitalization and rate of falls after discharge. Arch Intern Med 160:2788–2795, 2000 Wells K, Norquist G, Benjamin B, et al: Quality of antidepressant medications prescribed at discharge to depressed elderly patients in general medical hospitals before and after prospective payment system. Gen Hosp Psychiatry 16:4–15, 1994

280

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IMPROVING MENTAL HEALTHCARE

TABLE 10–13. Continuation of depression treatment 1.

Summary

Clinical rationale:

This measure assesses the proportion of patients initiating treatment for major depression who subsequently received at least 2 months of antidepressant medication or eight mental health specialty visits. Although major depression can be effectively treated with antidepressant medication or psychotherapy, many patients discontinue treatment prematurely, resulting in failure to achieve remission or relapse. Studies have found that patients continuing medication for 4–9 months after remission are less likely to relapse than those who do not. Studies of psychotherapy have found remission to occur after an average of 8–12 visits. A well-designed crosssectional study found a strong association between patient continuation of antidepressants and clinician–patient communication about treatment goals and side effects.

2. Specifications Denominator:

Number of patients with an outpatient visit for a new primary diagnosis of major depression (i.e., no diagnosis in prior 12 months) who receive either an antidepressant prescription or at least two mental health clinic visits in the subsequent 30 days

Numerator:

Patients from the denominator who either 1) filled prescriptions for 60 days or more of an antidepressant medication within 90 days of the index encounter, or 2) had at least eight mental health specialty visits within 6 months of the index encounter

Data sources:

Administrative data, pharmacy data

3. Development Developer:

Veterans Health Administration/Department of Defense (VHA/DOD)

Stakeholders:

Public sector payers and purchasers, employer purchasers, clinicians, delivery system managers, researchers

Measure set:

VHA/DOD Performance Measures for the Management of Major Depressive Disorder in Adults

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Treatment Measures

❚ 281

TABLE 10–13. Continuation of depression treatment (continued) Case-mix adjustment: Type:

Yes Multivariate: age; sex; history of major depressive disorder, psychosis, substance abuse, lithium or antipsychotic use; number of visits in primary care; antidepressant used in greatest quantity; number of different antidepressants

References and Instruments Agency for Health Care Policy and Research. Depression in Primary Care. Depression Guideline Panel: Vol 2. Treatment of Major Depression. Washington, DC: US Department of Health and Human Services, 1993. Robinson LA, Berman JS, Neimeyer RA: Psychotherapy for the treatment of depression: a comprehensive review of controlled outcome research. Psychol Bull 108:30–49, 1990 Thase M, Greenhouse J, Frank E, et al: Treatment of major depression with psychotherapy or psychotherapy-pharmacotherapy combinations. Arch Gen Psychiatry 54:1009–1015, 1997 Veterans Health Administration/Department of Defense: VHA/DOD Performance Measures for the Management of Major Depressive Disorder in Adults, Version 2.0. Washington, DC, Veterans Health Administration/Department of Defense, 2000

282

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IMPROVING MENTAL HEALTHCARE

TABLE 10–14. Depressed elderly patients discharged on antidepressants 1. Summary

This measure assesses the proportion of hospitalized depressed elderly patients who are prescribed an antidepressant medication at discharge.

Clinical rationale:

Depression is the most frequent diagnosis among hospitalized elderly individuals, with an estimated prevalence among inpatients of 6%–12%. The condition is associated with poor personal, social, and family functioning and increased rates of medical morbidity but is often undetected or inadequately treated. The National Institute of Mental Health Consensus Conference report, Diagnosis and Treatment of Depression in Late Life, recommended on the basis of randomized controlled trials that “depressed elderly people should be treated vigorously with sufficient doses of antidepressants and for a sufficient length of time to maximize the likelihood of recovery” (National Institutes of Health 1991, p. 19).

2. Specifications Denominator:

The number of inpatients age 65 or older discharged with a primary diagnosis of depression (unipolar or unspecified)

Numerator:

The number of patients from the denominator who are prescribed an antidepressant medication at discharge

Data sources:

Administrative data, medical record

3.

Development

Developer:

Wells et al. 1994

Stakeholders:

Clinicians, researchers

Measure set:

RAND Prospective Payment Study

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

Reliability testing:

Positive

Type: Validity testing: Type:

Interrater reliability results available Positive Comparison with the results of other methods or measures

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

65.3%, 2,746 elderly (Wells et al. 1994)

Treatment Measures

❚ 283

TABLE 10–14. Depressed elderly patients discharged on antidepressants (continued) Case-mix adjustment: Type:

Yes Multivariate: age, sex, race, Medicaid status, and illness severity at admission

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 American Psychiatric Association Work Group on Major Depressive Disorder: Practice Guideline for Major Depressive Disorder in Adults. Washington, DC, American Psychiatric Association, 1996 Katon W, von Korff M, Lin E, et al: Adequacy and duration of antidepressant treatment in primary care. Med Care 30:67–76, 1992 National Institutes of Health: Diagnosis and treatment of depression in late life. NIH Consensus Statement Presented at the NIH Consensus Development Conference, Bethesda, MD, November 1991 Wells K, Norquist G, Benjamin B, et al: Quality of antidepressant medications prescribed at discharge to depressed elderly patients in general medical hospitals before and after prospective payment system. Gen Hosp Psychiatry 16:4–15, 1994

284

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IMPROVING MENTAL HEALTHCARE

TABLE 10–15. Depression counseling at index visit 1. Summary

This measure assesses the proportion of individuals age 18 and older with depression who received 3 minutes or more of counseling from their physician.

Clinical rationale:

Despite their high prevalence and associated impairment, depressive disorders are often undetected and untreated. Controlled trials have found that specific psychotherapies lead to better outcomes for individuals with depression. Relatively few data exist on the provision of psychotherapy (evidence-based or otherwise) to depressed patients nationwide. The Medical Outcomes Study found that while nearly all depressed patients treated by mental health specialists received brief counseling for at least 3 minutes, fewer than half of depressed patients in the general medical sector received counseling.

2. Specifications Denominator:

Patients ages 18 and older enrolled in a health plan who were screened and confirmed to be depressed, independently of their physician’s judgment, and attended an index visit with their physician during a specified point in time

Numerator:

Those patients in the denominator with whom the physician reported counseling for 3 minutes or more about the depression

Data sources:

Administrative data, clinician survey/instrument, patient survey/instrument

3. Development Developer:

Wells et al. 1992

Stakeholders:

Clinicians, researchers

Measure set:

RAND Depression Medical Outcomes Study

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Reliability testing:

Positive

Type:

Internal consistency results available

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

93.2% for psychiatrists, 32%–98% for nonpsychiatrist clinicians, among 2,545 adults (Meredith et al. 1994)

Treatment Measures

❚ 285

TABLE 10–15. Depression counseling at index visit (continued) References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 1: Detection and Diagnosis. Washington, DC, U.S. Department of Health and Human Services, 1993 Glied S: Too little time? The recognition and treatment of mental health problems in primary care. Health Serv Res 33:891–910, 1998 Meredith L, Wells K, Camp P: Clinician specialty and treatment styles for depressed outpatients with and without medical comorbidities. Arch Fam Med 3:1065–1072, 1994 Meredith LS, Wells KB, Kaplan SH, et al: Counseling typically provided for depression: role of clinician specialty and payment system. Arch Gen Psychiatry 53:905–912, 1996 Robins L, Helzer J, Cottler L, et al: NIMH Diagnostic Interview Schedule, Version III Revised (DIS-III-R). Bethesda, MD, National Institute of Mental Health, 1989 Wells K, Burnam M, Hays D, et al: The course of depression in adult outpatients: results from the Medical Outcomes Study. Arch Gen Psychiatry 49:788–794, 1992

286

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–16. Antidepressant medication management: effective acute-phase treatment 1. Summary

This measure assesses the proportion of individuals started on an antidepressant for major depression who remain on the medication for at least 12 weeks.

Clinical rationale:

Depressive disorders can impair personal, social, and family functioning, decrease work productivity, and increase the risk of suicide. Randomized clinical trials show antidepressants to be efficacious for major depression; however, remission requires continuous treatment throughout a 12-week acute treatment phase. A substantial proportion of patients discontinue antidepressants prematurely—in one study, 28% within the first 4 weeks. Research suggests that clinicians can play an important role in influencing patient adherence to treatment by providing education, addressing concerns, and evaluating and treating side effects.

2. Specifications Denominator:

Members ages 18 and older as of the 120th day of the measurement year who were diagnosed with a new episode of depression and treated with antidepressant medication

Numerator:

Those members from the denominator with an 84-day (12week acute treatment phase) treatment with antidepressant medication

Data sources:

Administrative data, pharmacy data

3. Development Developer:

National Committee for Quality Assurance

Stakeholders:

Accrediting organizations, public sector payers and purchasers, employer purchasers, consumers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Health Plan Employer Data and Information Set

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

5. Use Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Selected results:

18.8%, 4,052 adult patients (Melfi et al. 1998) 22.7%–43.6%, adults from two health plans (Kerr et al. 2000) 58.8%, members of commercial health plans (National Committee for Quality Assurance 1999)

Treatment Measures

❚ 287

TABLE 10–16. Antidepressant medication management: effective acute-phase treatment (continued) Benchmarks:

46.1%, beneficiaries from State Medicaid Research Files for six states, 1994–1995 (Hermann et al. 2002)

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Bull SA, Hu XH, Hunkeler EM, et al: Discontinuation of use and switching of antidepressants: influence of patien-physician communication. JAMA 288:1403– 1409, 2002 Hermann RC, Chan J, Chiu WT, et al: Interpreting Findings From Quality Measurement Initiatives in Mental Health and Substance Abuse: Use of Prior Results and Statistical Benchmarks. Report for the U.S. Substance Abuse and Mental Health Services Administration, Center for Quality Assessment and Improvement in Mental Health. Washington, DC, Substance Abuse and Mental Health Services Administration, 2002 Kerr E, McGlynn E, Van Vorst K, et al: Measuring antidepressant prescribing practice in a health care system using administrative data: implications for quality measurement and improvement. Jt Comm J Qual Improv 26:203–216, 2000 Melfi C, Chawla A, Croghan T, et al: The effects of adherence to antidepressant treatment guidelines on relapse and recurrence of depression. Arch Gen Psychiatry 55:1128–1132, 1998 National Committee for Quality Assurance: NCQA Quality Compass. Washington, DC, National Committee for Quality Assurance, 1999 National Committee for Quality Assurance: Health Plan Employer Data and Information Set (HEDIS 2003). Washington, DC, National Committee for Quality Assurance, 2002

288

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–17. Duration of drug treatment for acute depression (first refill) 1. Summary

This measure assesses the proportion of individuals treated for depression who had a refill of their antidepressant within 6 weeks after the initial prescription.

Clinical rationale:

Depressive disorders can impair personal, social, and family functioning, decrease work productivity, and increase the risk of suicide. Randomized clinical trials show antidepressants to be efficacious for major depression; however, remission requires continuous treatment throughout a 12-week acute treatment phase. A substantial proportion of patients discontinue antidepressants prematurely–in one study, 28% within the first 4 weeks. Clinicians can play an important role in influencing patient adherence to treatment by providing education, addressing concerns, and evaluating and treating side effects.

2. Specifications Denominator:

Patients between the ages of 18 and 80 with an outpatient visit and a primary diagnosis of major depression who receive an initial antidepressant prescription (no prior antidepressant within the last 120 days)

Numerator:

The number of patients from the denominator who had a refill of their antidepressant within 6 weeks of the initial prescription

Data sources:

Administrative data, pharmacy data

3. Development Developer:

Katon et al. 2000

Stakeholders:

Clinicians, consumers, delivery system managers, researchers

Measure set:

Psychotropic Drug Use in Primary Care

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level A. Good research-based evidence

Validity testing:

Positive

Type:

Comparison with the results of other methods or measures, gold standard validity testing

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

40%–91.7%, 1,599 primary care patients (Katon et al. 2000)

Treatment Measures

❚ 289

TABLE 10–17. Duration of drug treatment for acute depression (first refill) (continued) Case-mix adjustment: Type:

Yes Multivariate: age, sex, medical comorbidity, illness severity, history of prior episode

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Katon W, Ruter C, Lin E, et al: Are there detectable differences in quality of care or outcome of depression across primary care providers? Med Care 38:552–561, 2000 Lin EH, Von Korff M, Katon W, et al: The role of the primary care physician in patients’ adherence to antidepressant therapy. Med Care 33:67–74, 1995

290

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–18. Duration of drug treatment for continuationphase depression (three prescriptions) 1. Summary

This measure assesses the proportion of patients newly prescribed antidepressants for a depressive disorder who filled three or more prescriptions in the proceeding year.

Clinical rationale:

Research has shown that the continuation of antidepressant medication for major depression for 4–9 months after acute symptom remission can reduce the rate of relapse. However, studies show that a substantial proportion of patients stop taking medication by the third month of treatment. Research suggests that clinicians can influence treatment continuation through patient and family education and active follow-up.

2.

Specifications

Denominator:

The number of primary care patients between the ages of 18 and 75 who are newly prescribed an antidepressant (i.e., no previous antidepressant prescriptions for 120 days) for a diagnosis of major depression

Numerator:

Those patients from the denominator who filled three or more prescriptions for antidepressants within 1 year after the index prescription

Data sources:

Administrative data, medical record, pharmacy data

3.

Development

Developer:

Katon et al. 1992

Stakeholders:

Clinicians, researchers

Measure set:

Antidepressant Treatment in Primary Care

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Reliability testing:

Positive

Type: 5.

Interrater reliability results available

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

22.7%–34.8%, 119 patients (Katon et al. 1992)

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age, sex, education, marital status, employment, income level

Treatment Measures

❚ 291

TABLE 10–18. Duration of drug treatment for continuationphase depression (three prescriptions) (continued) References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Bull SA, Hu XH, Hunkeler EM, et al: Discontinuation of use and switching of antidepressants: influence of patient-physician communication. JAMA 288:1403– 1409, 2002 Katon W, von Korff M, Lin E, et al: Adequacy and duration of antidepressant treatment in primary care. Med Care 30:67–76, 1992 Lin EH, Von Korff M, Katon W, et al: The role of the primary care physician in patients’ adherence to antidepressant therapy. Med Care 33:67–74, 1995 Melfi C, Chawla A, Croghan T, et al: The effects of adherence to antidepressant treatment guidelines on relapse and recurrence of depression. Arch Gen Psychiatry 55:1128–1132, 1998

292

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–19. Antidepressant medication management: effective continuation-phase treatment 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of individuals started on an antidepressant for major depression who remain on the medication for at least 6 months. Depressive disorders can impair personal, social, and family functioning, decrease work productivity, and increase the risk of suicide. Randomized clinical trials show antidepressants to be efficacious for treating major depression and preventing relapse. However, antidepressants must be continued for 4–9 months after initiation to minimize the likelihood of relapse. Research suggests that clinicians can play an important role in influencing patient adherence to treatment by providing education, addressing concerns, and evaluating and treating side effects.

Specifications

Denominator:

Members ages 18 years and older as of the 120th day of the measurement year who were diagnosed with a new episode of depression and treated with antidepressant medication

Numerator:

Those members from the denominator with a 180-day treatment with antidepressant medication

Data sources:

Administrative data, pharmacy data

3.

Development

Developer:

National Committee for Quality Assurance

Stakeholders:

Accrediting organizations, public sector payers and purchasers, employer purchasers, consumers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Health Plan Employer Data and Information Set

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level A. Good research-based evidence

Validity testing:

Positive

Type: 5.

Comparison with the results of other methods or measures, gold standard validity testing

Use

Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Selected results:

43%, California health plans (CalPERS Health Plan 2001); 42.2%, commercial health plans (NCQA 1999)

Treatment Measures

❚ 293

TABLE 10–19. Antidepressant medication management: effective continuation-phase treatment (continued) Benchmarks:

42.1%, beneficiaries from State Medicaid Research Files for six states, 1994–1995 (Hermann et al. 2002)

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Bull SA, Hu XH, Hunkeler EM, et al: Discontinuation of use and switching of antidepressants: influence of patient-physician communication. JAMA 288:1403– 1409, 2002 CalPERS Health Plan: Health Plan Quality Results: Blue Shield, Kaiser, Pacificare. Sacramento, CA, CalPERS Health Plan, 2001 Hermann RC, Chan J, Chiu WT, et al: Interpreting Findings From Quality Measurement Initiatives in Mental Health and Substance Abuse: Use of Prior Results and Statistical Benchmarks. Report for the U.S. Substance Abuse and Mental Health Services Administration, Center for Quality Assessment and Improvement in Mental Health. Washington, DC, Substance Abuse and Mental Health Services Administration, 2002 Melfi C, Chawla A, Croghan T, et al: The effects of adherence to antidepressant treatment guidelines on relapse and recurrence of depression. Arch Gen Psychiatry 55:1128–1132, 1998 National Committee for Quality Assurance (NCQA): NCQA Quality Compass. Washington, DC, National Committee for Quality Assurance, 1999 National Committee for Quality Assurance (NCQA): Health Plan Employer Data and Information Set (HEDIS 2003). Washington, DC, National Committee for Quality Assurance, 2002

294

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–20. Follow-up visits in antidepressant treatment 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of patients who receive a new antidepressant medication for depression and have a follow-up visit within 3 and 6 weeks. Although antidepressants typically take 4–8 weeks to be effective, a substantial proportion of depressed patients discontinue them during the first month of treatment. A follow-up visit shortly after initiating an antidepressant allows clinicians to provide patients with further education and encouragement, assess for side effects, and make adjustments to treatment. The U.S. Agency for Healthcare Research and Quality’s practice guidelines on treatment of depression in primary care recommend clinical visits every 1–2 weeks during the first 8 weeks of treatment. Recent research suggests that follow-up contact in conjunction with other practice enhancements is associated with improved outcome, but a follow-up visit alone is not.

Specifications

Denominator:

Patients between the ages of 18 and 80 with an outpatient visit and a primary diagnosis of major depression who receive an initial antidepressant prescription (no prior antidepressant within the last 120 days)

Numerator:

The number of patients from the denominator who have a medication management visit within 3 or 6 weeks of the index visit

Data sources:

Administrative data, pharmacy data

3.

Development

Developer:

Katon et al. 2000

Stakeholders:

Clinicians, consumers, delivery system managers, researchers

Measure set:

Psychotropic Drug Use in Primary Care

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Validity testing:

Negative

Type:

Comparison with the results of other methods or measures, gold standard validity testing

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Treatment Measures

❚ 295

TABLE 10–20. Follow-up visits in antidepressant treatment (continued) Selected results:

3 weeks: 0%–66%, 6 weeks: 20%–92.8%, 63 family physicians treating 1,599 patients (Katon et al. 2000)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, medical comorbidity, illness severity, history of prior episode

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Katon W, Von Korff M, Lin E, et al: Collaborative management to achieve treatment guidelines: impact on depression in primary care. JAMA 273:1026–1031, 1995 Katon W, Ruter C, Lin E, et al: Are there detectable differences in quality of care or outcome of depression across primary care providers? Med Care 38:552–561, 2000 Lin EH, Von Korff M, Katon W, et al: The role of the primary care physician in patients’ adherence to antidepressant therapy. Med Care 33:67–74, 1995

296

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–21. Antidepressant medication management: optimal practitioner contacts 1.

Summary

Clinical rationale:

This measure assesses the proportion of patients treated with antidepressant medication for depression who have at least three follow-up visits during the 12-week acute-phase treatment period. Randomized clinical trials have shown that 12 weeks of continuous treatment with antidepressants are needed, on average, to bring about remission of major depression. However, a substantial proportion of patients discontinue antidepressants prematurely—in one study, 28% within the first 4 weeks. Clinical experience suggests that follow-up visits after drug initiation can play an important role in influencing patient adherence by providing education, addressing concerns, and evaluating and treating side effects. Little research has examined the effectiveness of differences in frequency of follow-up visits, although Schulberg et al. (1995) found that a majority in one sample achieved significant improvement after an average of 6.9 visits (range 3–14) over 8 weeks. Agency for Healthcare Research and Quality practice guidelines for major depression recommend four to eight visits during the acute phase of treatment.

2. Specifications Denominator:

Members ages 18 and older as of the 120th day of the measurement year who were diagnosed with a new episode of depression and treated with antidepressant medication

Numerator:

Those members from the denominator with three or more outpatient follow-up visits or day/night treatment with a primary care or mental health practitioner (at least one of which is a prescribing practitioner) within 84 days after new diagnosis of depression (Follow-up visits must be for mental health and are expected to be “face to face.”)

Data sources:

Administrative data, pharmacy data

3.

Development

Developer:

National Committee for Quality Assurance

Stakeholders:

Accrediting organizations, public sector payers and purchasers, employer purchasers, consumers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Health Plan Employer Data and Information Set

Development:

Fully operationalized

Treatment Measures

❚ 297

TABLE 10–21. Antidepressant medication management: optimal practitioner contacts (continued) 4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Selected results:

21.3%, commercial health plans (NCQA 1999) 57%, California health plans (CalPERS Health Plan 2001) 32%, 16 New York commercial health plans, 2000 (New York State Health Accountability Foundation 2001)

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 CalPERS Health Plan: Health Plan Quality Results: Blue Shield, Kaiser, Pacificare. Sacramento, CA, CalPERS Health Plan, 2001 Kerr E, McGlynn E, Van Vorst K, et al: Measuring antidepressant prescribing practice in a health care system using administrative data: implications for quality measurement and improvement. Jt Comm J Qual Improv 26:203–216, 2000 National Committee for Quality Assurance (NCQA): NCQA Quality Compass. Washington, DC, National Committee for Quality Assurance, 1999 National Committee for Quality Assurance (NCQA): Health Plan Employer Data and Information Set (HEDIS 2003). Washington, DC, National Committee for Quality Assurance, 2002 New York State Health Accountability Foundation: New York State HMO Report Card 2001. Available at http://www.nyshaf.org/dox/hmorc/pdf/ 2001HMOReportCard.pdf. Accessed August 23, 2002 Schulberg HC, Block MR, Madonia M, et al: Applicability of clinical pharmacotherapy guidelines for major depression in primary care settings. Arch Fam Med 4:106–112, 1995

298

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IMPROVING MENTAL HEALTHCARE

TABLE 10–22. Initiation of depression treatment 1. Summary

This measure assesses the proportion of patients with major depression who receive an initial prescription for antidepressant medication or at least three psychotherapy visits.

Clinical rationale:

Controlled studies have established that antidepressant medications and certain types of psychotherapy are effective treatments for major depression. However, many primary care patients with depression go undetected and/or do not receive evidence-based treatments.

2. Specifications Denominator:

All patients seen in primary care during a specified period who had major depression based on a structured assessment administered independent of the clinical visit

Numerator:

Patients in the denominator who filled at least one antidepressant prescription or had at least three psychotherapy visits during the 5-month period after diagnosis

Data sources:

Medical record, patient survey/instrument

3. Development Developer:

Rost et al. 1995

Stakeholders:

Researchers

Measure set:

Major depression in rural family practice

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

68.4%, rural primary care patients (Rost et al. 1995)

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Delgado PL: Approaches to the enhancement of patient adherence to antidepressant medication treatment. J Clin Psychiatry 61(suppl):6–9, 2000 Lin EH, Von Korff M, Katon W, et al: The role of the primary care physician in patients’ adherence to antidepressant therapy. Med Care 33:67–74, 1995 Rost KM, Burnan MA, Smith GR: Development of screeners for depressive disorders and substance disorder history. Med Care 31:189–200, 1993

Treatment Measures

❚ 299

TABLE 10–22. Initiation of depression treatment (continued) Rost K, Williams C, Wherry J, et al: The process and outcomes of care for major depression in rural family practice settings. J Rural Health 11:114–121, 1995

300

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–23. Doctor visits in inpatient care for depression 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of elderly individuals hospitalized with a diagnosis of depression whose medical record contains documentation of daily doctor visits. Depression is the most frequent diagnosis among hospitalized elderly individuals, with an estimated prevalence among inpatients of 6%–12%. Because an inpatient level of care is typically limited to patients with significant impairment requiring active treatment, daily assessment by a doctor is generally indicated. There is no research evidence examining the association between the frequency of inpatient clinician visits and outcome for this population.

Specifications

Denominator:

Patients ages 65 and older discharged from a hospital with a primary diagnosis of depression (unipolar or unspecified) during a specified period

Numerator:

The subset of patients in the denominator with doctor (M.D. or Ph.D.) visits documented in the medical record in each of the first three or last two hospital days

Data sources:

Administrative data, medical record

3. Development Developer:

Wells et al. 1994

Stakeholders:

Clinicians, researchers

Measure set:

RAND Depressed Elderly

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Reliability testing:

Positive

Type:

Interrater reliability results available

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

86%, 2,746 elderly in 297 acute-care general medical hospitals (Wells et al. 1993)

Case mix adjustment:

Yes

Type:

Multivariate: age, sex, race, Medicaid status, and illness severity at admission

Treatment Measures

❚ 301

TABLE 10–23. Doctor visits in inpatient care for depression (continued) References and Instruments Norquist G, Wells KB, Rogers WH, et al: Quality of care for depressed elderly patients hospitalized in the specialty psychiatric units or general medical wards. Arch Gen Psychiatry 52:695–702, 1995 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993 Wells KB, Rogers WH, Davis LM, et al: Quality of care for depressed elderly prepost prospective payment system: differences in response across treatment settings. Med Care 32:257–276, 1994

302

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IMPROVING MENTAL HEALTHCARE

TABLE 10–24. Inpatient rehabilitative therapy for depressed elderly 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of elderly patients admitted to a hospital with a diagnosis of depression whose medical record contains documentation of rehabilitation, recreation, or occupational therapy. Depression is the most frequent diagnosis among hospitalized elderly individuals, with an estimated prevalence among inpatients of 6%–12%. Because depression can impair social and physical functioning, inpatient programs may provide rehabilitation programs, organized recreation, and/or occupational therapy to encourage physical activity, social connections, and skills enhancement. There is little empirical research showing an association between these inpatient programs and patient outcome in the contemporary context of time-limited inpatient stays.

Specifications

Denominator:

Patients ages 65 and older discharged from a hospital with a primary diagnosis of depression (unipolar or unspecified) during a specified period

Numerator:

The subset of patients in the denominator with rehabilitation, recreation, or occupational therapy sessions documented in the medical record for the first three or last two hospital days

Data sources:

Administrative data, medical record

3.

Development

Developer:

Norquist et al. 1995

Stakeholders:

Clinicians, researchers

Measure set:

RAND Depressed Elderly

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Reliability testing:

Positive

Type: 5.

Interrater reliability results available

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

13%, medical ward, 45%, psychiatric unit, 2,746 elderly in 297 acute-care general medical hospitals (Norquist et al. 1995)

Treatment Measures

❚ 303

TABLE 10–24. Inpatient rehabilitative therapy for depressed elderly (continued) Case-mix adjustment: Type:

Yes Multivariate: age, sex, race, Medicaid status, and illness severity at admission

References and Instruments Kochershberger G, Hielema F, Westlund R: Rehabilitation in the nursing home: how much, why, and with what results. Public Health Rep 109:372–376, 1994 Norquist G, Wells KB, Rogers WH, et al: Quality of care for depressed elderly patients hospitalized in the specialty psychiatric units or general medical wards. Arch Gen Psychiatry 52:695–702, 1995

304

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–25. Patient termination of treatment in depression 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of adults initiating treatment for major depression who discontinued treatment against the advice of their counselor or therapist. Research studies demonstrating the efficacy of antidepressant medication have found that 3–4 months of treatment is needed, on average, for remission of an acute depressive episode, and further treatment is needed to prevent relapse. Similarly, studies of psychotherapies suggest that multiple sessions are needed to produce positive results. However, research has also found that many individuals with major depression terminate treatment prematurely. Although clinicians have limited influence with regard to patient engagement in treatment, strategies including education, outreach, and encouragement can influence patient adherence to treatment recommendations.

Specifications

Denominator:

Adults with a clinician’s diagnosis of major depression whose responses to the Foundation for Accountability (FACCT) Questionnaire 1) confirmed the diagnosis of major depression using the Depression-Arkansas Scale and 2) reported the termination of treatment within 6 months of diagnosis (responded “no” to question 31)

Numerator:

Individuals from the denominator who reported that treatment ended for reasons other than the “counselor/ therapist agreed it was time to end treatment” (item 2 or 3 on question 31a)

Data sources:

Administrative data, patient survey/instrument

3.

Development

Developer:

FACCT

Stakeholders:

Consumers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

FACCT Quality Measures

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Treatment Measures

❚ 305

TABLE 10–25. Patient termination of treatment in depression (continued) References and Instruments Foundation for Accountability: FACCT Quality Measures: Major Depressive Disorder, Measurement Specifications. Portland, OR, Foundation for Accountability, 1997 Last CG, Thase ME, Hersen M, et al: Patterns of attrition for psychosocial and pharmacologic treatments of depression. J Clin Psychiatry 46:361–366, 1985 Melfi C, Chawla A, Croghan T, et al: The effects of adherence to antidepressant treatment guidelines on relapse and recurrence of depression. Arch Gen Psychiatry 55:1128–1132, 1998 Oei TP, Kazmierczak T: Factors associated with dropout in a group cognitive behavior therapy for mood disorders. Behav Res Ther 35:1025–1030, 1997 Pages KP, Russo JE, Wingerson DK, et al: Predictors and outcome of discharge against medical advice from the psychiatric units of a general hospital. Psychiatr Serv 49:1187–1192, 1998 Simons AD, Levine JL, Lustman PJ, et al: Patient attrition in a comparative outcome study of depression: a follow-up report. Affect Disord 6:163–173, 1984

306

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TABLE 10–26. Scheduled follow-up for antidepressant therapy 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of individuals newly prescribed an antidepressant medication who had a scheduled follow-up appointment documented in the medical record at the index visit. Many patients discontinue antidepressants during the first month of treatment, before they are likely to be effective. For those who complete the first 4–6 weeks of treatment, reevaluation is typically indicated for assessment of response and change in dosage or medication if warranted. Research conducted in the general medical sector, not specific to antidepressants, found that patients who are provided scheduled follow-up appointments are more likely to return than patients who were asked to return but not scheduled. Recent research suggests that follow-up contact after treatment initiation for depression is associated with improved outcome when combined with other practice enhancements, but follow-up contact alone has not been shown to be associated with outcome.

Specifications

Denominator:

The number of individuals ages 18 and older enrolled in a health plan who were newly prescribed an antidepressant medication during a specified time period

Numerator:

Those patients from the denominator who had a scheduled appointment for follow-up documented in the medical record at the time of the index visit

Data sources:

Administrative data, medical record, pharmacy data, patient contact/appointment data

3.

Development

Developer:

Wells et al. 1988

Stakeholders:

Clinicians, researchers

Measure set:

Psychotropic Drug Use in Primary Care

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Treatment Measures

❚ 307

TABLE 10–26. Scheduled follow-up for antidepressant therapy (continued) Selected results:

89%, 578 patients across 16 academic internal medicine group practices (Wells et al. 1988) 57%, 100 patients in a Midwestern health plan (Theobald et al. 2000) 43.1%, 109 Hispanic and non-Hispanic white patients (Sleath et al. 2001)

Standards:

90% (Wells et al. 1988)

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age, sex, race, education, insurance, mental health status, physical and role functioning

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Katon W, Ruter C, Lin E, et al: Are there detectable differences in quality of care or outcome of depression across primary care providers? Med Care 38:552–561, 2000 Pinsker J, Phillips RS, Davis RB, et al: Use of follow-up services by patients referred from a walk-in unit: how can patient compliance be improved? Am J Med Qual 10:81–87, 1995 Simon GE, VonKorff M, Rutter C, et al: Randomised trial of monitoring, feedback, and management of care by telephone to improve treatment of depression in primary care. BMJ 320:550–554, 2000 Sleath B, Rubin RH, Huston S: Resident physician management of Hispanic and non-Hispanic white patients on antidepressants. Int J Qual Health Care 13(3):231– 238, 2001 Theobald DE, Kasper M, NickKresl CA, et al: Documentation of indicators for antidepressant treatment and response in an HMO primary care population. J Manag Care Pharm 6:494–498, 2000 Wells KB, Goldberg G, Brook R, et al: Management of patients on psychotropic drugs in primary care clinics. Med Care 26:645–656, 1988

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TABLE 10–27. Somatic treatment for severe depression 1. Summary

This measure assesses the proportion of patients with major depressive disorder (severe) who received an antidepressant medication or electroconvulsive therapy (ECT).

Clinical rationale:

Major depressive disorder is prevalent and disabling, often accompanied by impaired personal, social, occupational, and/or family functioning. Research studies have found that the disorder goes undetected or inadequately treated. Severe depression has been shown to be effectively treated with antidepressant medication and ECT.

2. Specifications Denominator:

Adults with a current diagnosis of major depressive disorder of severe or recurrent subtype (not in remission) during a specified period of time

Numerator:

The number of individuals in the denominator who receive an antidepressant medication or ECT

Data sources:

Administrative data, medical record

3.

Development

Developer:

American Psychiatric Association (APA)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

APA Practice Guidelines for Depression

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

92.3% for patients with moderate or severe major depressive disorder treated by a psychiatrist (West et al. 2000)

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Hermann R, Ettner S, Dorwart R, et al: Diagnoses of patients treated with electroconvulsive therapy: comparing evidence-based standards with reported use. Psychiatr Serv 50:1059–1065, 1999 Wells K, Katon W, Rogers B, et al: Use of minor tranquilizers and antidepressant medications by depressed outpatients: results from the Medical Outcomes Study. Am J Psychiatry 151:694–700, 1994

Treatment Measures

❚ 309

TABLE 10–27. Somatic treatment for severe depression (continued) West J, Leaf P, Zarin D: Health plan characteristics and conformance with key practice guideline psychopharmacologic treatment recommendations for major depression. Ment Health Serv Res 2:223–237, 2000

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TABLE 10–28. Somatic treatment for psychotic depression 1.

Summary

Clinical rationale:

This measure assesses the proportion of patients with a diagnosis of major depression, psychotic subtype, who receive either electroconvulsive therapy (ECT) or an antidepressant and an antipsychotic medication. Psychosis is present among an estimated 16%–54% of patients with major depression. Compared with nonpsychotic depression, major depression with psychotic features is characterized by greater functional impairment, higher rate of recurrence, and longer episodes. The psychotic subtype has a lower rate of response to antidepressant medications alone. Higher response rates are seen with either ECT or combination treatment with antidepressant and antipsychotic medications. Despite these findings from efficacy studies, nearly half of a sample of patients referred for ECT for psychotic depression had been previously treated with an antidepressant drug alone, without an accompanying antipsychotic drug.

2. Specifications Denominator:

Adults with a current diagnosis of major depression, psychotic subtype (DSM-IV code 296.24) during a specified period of time

Numerator:

The number of patients from the denominator who receive either a combination of an antidepressant and an antipsychotic medication or ECT

Data sources:

Administrative data, medical record

3. Development Developer:

American Psychiatric Association (APA)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

APA Practice Guidelines for Depression

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

80.9% among APA Practice Research Network psychiatrists (West et al. 2000)

Treatment Measures

❚ 311

TABLE 10–28. Somatic treatment for psychotic depression (continued) References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Mulsant B, Haskett R, Prudic J, et al: Low use of neuroleptic drugs in the treatment of psychotic major depression. Am J Psychiatry 154:559–561, 1997 Spiker DG, Perel JM, Hanin I, et al: The pharmacological treatment of delusional depression, part II. J Clin Psychopharmacol 6:339–342, 1986 West J, Leaf P, Zarin D: Health plan characteristics and conformance with key practice guideline psychopharmacologic treatment recommendations for major depression. Ment Health Serv Res 2:223–237, 2000

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TABLE 10–29. Treatment changes for nonresponsive depression 1.

Summary

Clinical rationale:

This measure assesses the proportion of patients with major depression treated for 8 weeks without response whose medical record documents a change in their treatment plan. Research studies have shown that antidepressant treatment for major depression will generally show signs of effectiveness within 4–6 weeks after initiation of treatment. Practice guidelines recommend that a patient who shows no or minimal response after 4–8 weeks should be reassessed, and treatment should be adjusted accordingly. Appropriate clinical responses include diagnostic reassessment, increasing drug dosage, adding a supplemental treatment, or changing treatments. Certain types of psychotherapy are also effective for major depression; however, the evidence supporting a threshold period for reassessment is less clear for these modalities.

2. Specifications Denominator:

Patients with a diagnosis of major depression who show no improvement in target symptoms after 8 weeks of the initiation of a treatment intervention

Numerator:

Those patients from the denominator who have documented changes in their treatment plan

Data sources:

Administrative data, medical record

3. Development Developer:

Joint Commission on Accreditation of Healthcare Organizations

Stakeholders:

Accrediting organizations, researchers

Measure set:

National Library of Healthcare Indicators

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level A. Good research-based evidence

Use

Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993

Treatment Measures

❚ 313

TABLE 10–29. Treatment changes for nonresponsive depression (continued) Joint Commission on Accreditation of Healthcare Organizations: National Library of Healthcare Indicators. Oakbrook Terrace, IL, Joint Commission on Accreditation of Healthcare Organizations, 1997 Shapiro DA, Barkham M, Rees A, et al: Effects of treatment duration and severity of depression on the effectiveness of cognitive-behavioral therapy and psychodynamic-interpersonal therapy. J Consult Clin Psychol 62:522–534, 1994

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TABLE 10–30. Treatment for mild depression 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of patients with major depression (mild) who receive an antidepressant medication or psychotherapy. Major depressive disorder affects 3.7%–10.3% of adult Americans over a 12-month period. Depression can impair social, vocational, and other role functioning. Antidepressant medications and certain types of psychotherapy (e.g., cognitive behavioral therapy, interpersonal therapy) have been shown to be efficacious in the treatment of major depressive disorder. Practice guidelines recommend first-line use of either modality for mild subtypes of the disorder. Research studies such as the Medical Outcomes Study indicate that both treatments may be underused among individuals with depression.

Specifications

Denominator:

Patients with a current diagnosis of major depression that is mild (DSM-IV code 296.21) and not chronic during a specified period

Numerator:

Patients in the denominator who received an antidepressant medication or psychotherapy during a specified period

Data sources:

Administrative data, pharmacy data

3.

Development

Developer:

American Psychiatric Association (APA)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

APA Practice Guidelines for Depression

Development:

Incomplete

4. Properties Evidence basis: 5.

AHRQ Level A. Good research-based evidence

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

97.6% among APA Practice Research Network psychiatrists (West et al. 2000)

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996

Treatment Measures

❚ 315

TABLE 10–30. Treatment for mild depression (continued) Meredith LS, Wells KB, Kaplan SH, et al: Counseling typically provided for depression: role of clinician specialty and payment system. Arch Gen Psychiatry 53:905–912, 1996 Wells K, Katon W, Rogers B, et al: Use of minor tranquilizers and antidepressant medications by depressed outpatients: results from the Medical Outcomes Study. Am J Psychiatry 151:694–700, 1994 West J, Leaf P, Zarin D: Health plan characteristics and conformance with key practice guideline psychopharmacologic treatment recommendations for major depression. Ment Health Serv Res 2:223–237, 2000

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TABLE 10–31. Treatment for moderate depression 1. Summary

This measure assesses the proportion of patients with major depressive disorder (moderate; MDD) who receive an antidepressant, psychotherapy, or electroconvulsive therapy (ECT).

Clinical rationale:

MDD is prevalent and disabling, often accompanied by impaired personal, social, occupational, and/or family functioning. Research studies have found that the disorder often goes undetected or inadequately treated. Antidepressant medications, ECT, and certain types of psychotherapy (e.g., cognitive behavioral therapy, interpersonal therapy) have been shown to be efficacious in the treatment of MDD.

2.

Specifications

Denominator:

Adults with a current diagnosis of MDD of moderate subtype during a specified period of time.

Numerator:

The number of individuals in the denominator who receive an antidepressant, psychotherapy, or ECT.

Data sources:

Administrative data, medical record

3.

Development

Developer:

American Psychiatric Association (APA)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

APA Practice Guidelines for Depression

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level A. Good research-based evidence

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

92.3% for patients with moderate or severe MDD treated by a psychiatrist (West et al. 2000)

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 American Psychiatric Association: Practice Guidelines for Psychiatric Evaluation of Adults. Washington, DC, American Psychiatric Association, 1996 Meredith LS, Wells KB, Kaplan SH, et al: Counseling typically provided for depression: role of clinician specialty and payment system. Arch Gen Psychiatry 53:905–912, 1996

Treatment Measures

❚ 317

TABLE 10–31. Treatment for moderate depression (continued) Wells K, Katon W, Rogers B, et al: Use of minor tranquilizers and antidepressant medications by depressed outpatients: results from the Medical Outcomes Study. Am J Psychiatry 151:694–700, 1994 West J, Leaf P, Zarin D: Health plan characteristics and conformance with key practice guideline psychopharmacologic treatment recommendations for major depression. Ment Health Serv Res 2:223–237, 2000

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TABLE 10–32. Treatment initiation for individuals with depressive symptoms 1.

Summary

Clinical rationale:

2.

This measure assesses the number of health plan members reporting depressive symptoms whose documentation shows a mental health clinician visit, psychoeducation class, filled antidepressant prescription, or report of using nonplan mental health services. Depressive disorders can impair personal, social, and family functioning, decrease work productivity, and increase the risk of suicide. Research studies have found that medication and psychotherapy are both effective for the treatment of depression, and clinical practice guidelines recommend treatment with one of these interventions or with electroconvulsive therapy. Nonetheless, studies have also shown that many individuals who have depressive symptoms at the time of a clinical visit do not receive treatment. This measure looks for evidence of whether treatment was initiated.

Specifications

Denominator:

Adults ages 18 and older enrolled in a health maintenance organization (HMO) within a specified time period with depression as indicated by a score of greater than 1.1 on the Hopkins Symptom Checklist Depression Scale

Numerator:

Patients from the denominator who experienced one of the following: 1) filled an antidepressant, 2) had a mental health clinician visit (either in HMO or paid for by HMO), 3) took a depression psychoeducation class, or 4) reported in a survey use of other mental health services for depression

Data sources:

Administrative data, patient survey/instrument, pharmacy data

3.

Development

Developer:

Brown et al. 2000

Stakeholders:

Clinicians, delivery system managers, researchers

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

46.5%–55.0%, 928 patients (Brown et al. 2000)

Treatment Measures

❚ 319

TABLE 10–32. Treatment initiation for individuals with depressive symptoms (continued) References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 Brown J, Shye D, McFarland B, et al: Controlled trials of CQI and academic detailing to implement a clinical practice guideline for depression. Jt Comm J Qual Improv 26:39–54, 2000 Meredith LS, Wells KB, Kaplan SH, et al: Counseling typically provided for depression: role of clinician specialty and payment system. Arch Gen Psychiatry 53:905–912, 1996 Wells K, Katon W, Rogers B, et al: Use of minor tranquilizers and antidepressant medications by depressed outpatients: results from the Medical Outcomes Study. Am J Psychiatry 151:694–700, 1994

320

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TABLE 10–33. Treatment plans for antidepressant use 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of adults newly prescribed an antidepressant medication by their primary care clinician who have an adequate treatment plan documented in their medical record. Quality of care for depression in primary care has been found to vary. Treatment plans can provide for systematic documentation of the target symptoms for treatment and the goals for each intervention. There are no research studies examining the association between use of written treatment plans and clinical outcomes among depressed primary care patients.

Specifications

Denominator:

The number of patients ages 18 and older enrolled in a health plan who are treated by a primary care physician and newly prescribed antidepressants during a specified period

Numerator:

The number of cases from the denominator for which there was an adequate treatment plan documented in the medical record (adequate defined as counseling offered, a stated goal for medication treatment, and criteria for discontinuation of the medication)

Data sources:

Administrative data, medical record, pharmacy data

3.

Development

Developer:

Wells et al. 1988

Stakeholders:

Clinicians, researchers

Measure set:

Psychotropic Drug Use in Primary Care

Development:

Incomplete

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

60%, 578 patients across 16 academic internal medicine group practices (Wells et al. 1988) 51%, 109 Hispanic and non-Hispanic white patients (Sleath et al. 2001)

Standards:

90% (Wells et al. 1988)

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age, sex, race, education, insurance, mental health status, physical and role functioning

Treatment Measures

❚ 321

TABLE 10–33. Treatment plans for antidepressant use (continued) References and Instruments Jaski ME, Schwartzburg JG, Guttman RA, et al: Medication review and documentation in physician office practice. Eff Clin Pract 3:31–34, 2000 Sleath B, Rubin RH, Huston S: Resident physician management of Hispanic and non-Hispanic white patients on antidepressants. Int J Qual Health Care 13:231– 238, 2001 Soreff S, Gulkin T, Pike JG: The evolving clinical chart: how it reflects and influences psychiatric and medical practice and the quality of care. Psychiatr Clin North Am 13:127–133, 1990 Wells KB, Goldberg G, Brook RH, et al: Quality of care for psychotropic drug use in internal medicine group practices. J West Med 145:710–714, 1986 Wells KB, Goldberg G, Brook R, et al: Management of patients on psychotropic drugs in primary care clinics. Med Care 26:645–656, 1988

322

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TABLE 10–34. Untreated depression in nursing homes 1.

Summary

Clinical rationale:

This measure assesses the proportion of nursing home residents who had a diagnosis or symptoms of depression and did not receive an antidepressant medication. Depression is often unrecognized and untreated among elderly patients in nursing homes. A study of 42,901 nursing home residents in five states found that although 11% met criteria for depression, only 55% of this group were receiving antidepressant medication. Untreated depression in elderly individuals is associated with lower functioning and quality of life and an increased risk of suicide.

2. Specifications Denominator:

All nursing home residents evaluated at a given point in time

Numerator:

Residents with a diagnosis or symptoms of depression (including sad mood and at least two of the following functional symptoms: distress, agitation or withdrawal, awake with unpleasant mood, suicidal or recurrent thoughts of death) and not treated with antidepressant medication during the previous 7 days

Data sources:

Minimal Data Set 2.0 Resident Assessment Instrument

3. Development Developer:

Center for Health Systems Research and Analysis

Stakeholders:

Clinicians, researchers

Measure set:

University of Wisconsin–Nursing Home

Development:

Fully operationalized

Quality Indicators 4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement, research study

Selected results:

None

Standards:

Lower (good) threshold, 5.1%; upper (problematic) threshold, 14% (Rantz et al. 2000)

References and Instruments Brown MN, Lapane KL, Luisi AF: The management of depression in older nursing home residents. J Am Geriatr Soc. 50:69–76, 2002 Lebowitz BD, Pearson JL, Schneider LS, et al: Diagnosis and treatment in late life: consensus statement update. JAMA 278:1186–1190, 1997

Treatment Measures

❚ 323

TABLE 10–34. Untreated depression in nursing homes (continued) Morris JN, Hawes C, Fries BE, et al: Designing the national resident assessment instrument for nursing homes. Gerontologist 30:293–307, 1990 Rantz MJ, Petroski GF, Madsen RW, et al: Setting thresholds for quality indicators derived from MDS data for nursing home quality improvement reports: an update. J Qual Improv 26:101–110, 2000 Zimmerman DR, Karon SL, Arling G, et al: Development and testing of nursing home quality indicators. Health Care Financ Rev 16:107–127, 1995

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TABLE 10–35. Visit frequency for depression treatment (four visits) 1. Summary

This measure assesses the proportion of individuals diagnosed with major depressive disorder who have at least four psychotherapy or medication management visits for major depressive disorder within 8 weeks of the initial visit.

Clinical rationale:

Major depression impairs an individual’s mood, functioning, and quality of life. Effective treatments include antidepressant medication and psychotherapy, but both require extended treatment to be effective. Clinical visits are needed for providing psychotherapy or, for medication treatment, to assess drug response, evaluate side effects, adjust medication, and provide ongoing education and support. The Agency for Healthcare Research and Quality clinical practice guidelines for depression recommend weekly visits during the first 6–8 weeks of acute care. Research evidence on the efficacy of short-term psychotherapy supports the need for at least four sessions. Although clinicians have limited influence over patient engagement in treatment, strategies have been proposed to engage and motivate individuals at risk for early dropout.

2. Specifications Denominator:

All plan members receiving an initial diagnosis of major depressive disorder during a specified reporting period

Numerator:

Patients included in the denominator who had at least four psychotherapy or medication management visits for major depressive disorder within 8 weeks of the initial visit

Data sources:

Administrative data

3. Development Developer:

American Managed Behavioral Healthcare Association

Stakeholders:

Accrediting organizations, consumers, researchers

Measure set:

PERMS 2.0

Development:

Incomplete

4. Properties Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Treatment Measures

❚ 325

TABLE 10–35. Visit frequency for depression treatment (four visits) (continued) References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5 (AHCPR Publication No. 93–0551). Rockville, MD, U.S. Department of Health and Human Services, 1993 American Managed Behavioral Healthcare Association: PERMS 2.0: Performance Measures for Managed Behavioral Healthcare Programs. Washington, DC, American Managed Behavioral Healthcare Association, 1998 Delgado PL: Approaches to the enhancement of patient adherence to antidepressant medication treatment. J Clin Psychiatry 61(suppl):6–9, 2000 Jarrett RB: Psychosocial aspects of depression and the role of psychotherapy. J Clin Psychiatry 51(suppl):26–35, 1990 Jarrett RB, Schaffer M, McIntire D, et al: Treatment of atypical depression with cognitive therapy or phenelzine: a double-blind, placebo controlled trial. Arch Gen Psychiatry 56:431–437, 1999 Schulberg HC, Block MR, Madonia MJ, et al: Treating major depression in primary care practice: eight month clinical outcomes. Arch Gen Psychiatry 53:913–919, 1996

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TABLE 10–36. Antidepressant dosages for depression with schizophrenia 1. Summary

This measure assesses the proportion of individuals with schizophrenia who receive an antidepressant dosage below the level recommended by evidence-based guidelines.

Clinical rationale:

Approximately 25% of individuals with schizophrenia exhibit symptoms constituting a depressive syndrome over an extended period of observation. Compared with schizophrenia alone, the presence of co-occurring depression has been associated with worse functioning, increased relapse rates, and a greater likelihood of suicide. Despite research evidence supporting the effectiveness of antidepressant medications at standard dosages, evidence suggests that depression is often underrecognized and undertreated in this population.

2. Specifications Denominator:

Enrollees who had either one inpatient admission or two outpatient visits with a primary diagnosis of schizophrenia within a 12-month period

Numerator:

Individuals in the denominator who received an antidepressant dosage below guideline-recommended thresholds for more than 4 weeks of the 12-month period (amitriptyline 150 mg, amoxapine 200 mg, bupropion 225 mg, clomipramine 125 mg, desipramine 150 mg, doxepin 150 mg, fluoxetine 20 mg, imipramine 150 mg, maprotiline 150 mg, nortriptyline 75 mg, protriptyline 30 mg, trazodone 200 mg, trimipramine 150 mg)

Data sources:

Administrative data, medical record

3. Development Developer:

Popkin et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

15%–19%, 377 Utah Medicaid beneficiaries (Popkin et al. 1998)

Treatment Measures

❚ 327

TABLE 10–36. Antidepressant dosages for depression with schizophrenia (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Levinson DF, Umapathy C, Musthaq M: Treatment of schizoaffective disorder and schizophrenia with mood symptoms. Am J Psychiatry 156:1138–1148, 1999 Plasky P: Antidepressant usage in schizophrenia. Schizophr Bull 17:649–657, 1991 Popkin MK, Callies AL, Lurie N, et al: An instrument to evaluate the process of psychiatric care in ambulatory settings. Psychiatr Serv 48:524–527, 1997 Popkin MK, Lurie N, Manning W, et al: Changes in the process of care for Medicaid patients with schizophrenia in Utah’s prepaid mental health plan. Psychiatr Serv 49:518–523, 1998 Siris SG: Depression in schizophrenia: perspective in the era of “atypical” antipsychotic agents. Am J Psychiatry 157:1379–1389, 2000

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TABLE 10–37. Antipsychotic drug dosing for inpatients with schizophrenia 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of inpatients with acutephase schizophrenia who are receiving a daily dosage of an antipsychotic medication within the recommended dosage range at the time of discharge. Antipsychotic medications have been shown to be efficacious in the treatment of acute psychotic exacerbations of schizophrenia and in reducing the likelihood of relapse. Randomized controlled trials have demonstrated the efficacy of these agents within a dosage range between 300 and 1,000 chlorpromazine equivalents. Below this range the likelihood of poor response is increased. Higher dosages on average lead to increased side effects without additional therapeutic benefit.

Specifications

Denominator:

All inpatients ages 18 and older hospitalized with a primary diagnosis of schizophrenia during a specified period and receiving an antipsychotic medication at discharge

Numerator:

The subset of patients in the denominator who were prescribed an antipsychotic medication dosage in the range of 300–1,000 chlorpromazine equivalents per day at the time of discharge

Data sources:

Administrative data, medical record

3. Development Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia Patient Outcomes Research Team

Users:

American Psychiatric Association

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level A. Good research-based evidence

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

62.4%, 719 individuals in two states (Lehman and Steinwachs 1998b) 73.6%, 192 Veterans Affairs (VA) inpatients, 83.2%, 96 nonVA inpatients (Rosenheck et al. 2000) 52%, 936 veterans in 14 facilities (Valenstein et al. 2001) 63.6%, 34,925 VA patients (Leslie and Rosenheck 2001)

Treatment Measures

❚ 329

TABLE 10–37. Antipsychotic drug dosing for inpatients with schizophrenia (continued) References and Instruments Dixon L, Lehman A, Levine J: Conventional antipsychotic medications for schizophrenia. Schizophr Bull 21:567–577, 1995 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Leslie D, Rosenheck R: Use of pharmacy data to assess quality of pharmacotherapy for schizophrenia in a national health care system: individual and facility predictors. Med Care 39:923–933, 2001 Owen R, Thrush C, Kirchner J, et al: Performance measurement for schizophrenia: adherence to guidelines for antipsychotic dose. Int J Qual Health Care 12:475– 482, 2000 Rosenheck R, Desai R, Steinwachs D, et al: Benchmarking treatment of schizophrenia: a comparison of service delivery by the national government and by state and local providers. J Nerv Ment Dis 188:209–216, 2000 Valenstein M, Copeland L, Owen R, et al: Delays in adopting evidence-based dosages of conventional antipsychotics. Psychiatr Serv 52:1242–1244, 2001

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TABLE 10–38. Maintenance antipsychotic drug dosing for schizophrenia 1. Summary

This measure assesses the proportion of patients with schizophrenia who receive a maintenance dosage of antipsychotic medication of 300–600 chlorpromazine equivalents per day.

Clinical rationale:

Practice guidelines recommend that individuals with schizophrenia receive maintenance treatment after the remission of an acute exacerbation. Controlled trials have shown that individuals with schizophrenia who have experienced an acute psychotic episode within the prior 12 months are less likely to relapse if they receive an antipsychotic medication. Studies have found that maintenance treatment is most effective within a dosage range of 300–600 chlorpromazine equivalents per day. Dosages lower than 300 chlorpromazine equivalents increase the likelihood of relapse, whereas doses higher than 600 equivalents are associated with higher rates of side effects and, on average, do not lead to better clinical outcomes.

2. Specifications Denominator:

All individuals ages 18 and older with a diagnosis of schizophrenia who receive an antipsychotic medication on an outpatient basis at a specified point in time

Numerator:

Those individuals from the denominator receiving an antipsychotic medication of between 300 and 600 chlorpromazine equivalents per day

Data sources:

Administrative data, medical record

3. Development Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia Patient Outcomes Research Team

Users:

American Psychiatric Association

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level A. Good research-based evidence

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

29.1%, 440 outpatients (Lehman and Steinwachs 1998b) 35.7%, 274 Veterans Affairs (VA) outpatients 33.9%, 184 non-VA outpatients (Rosenheck et al. 2000) 27.9%, 344 patients in two states (Buchanan et al. 2002)

Treatment Measures

❚ 331

TABLE 10–38. Maintenance antipsychotic drug dosing for schizophrenia (continued) References and Instruments Baldessarini RJ, Cohen BM, Teicher MH: Significance of neuroleptic dose and plasma level in the pharmacological treatment of psychoses. Arch Gen Psychiatry 45:79–81, 1988 Buchanan RW, Kreyenbuhl J, Zito JM, et al: The Schizophrenia PORT pharmacological treatment recommendations: conformance and implications for symptoms and functional outcome. Schizophr Bull 28:63–73, 2002 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Dixon L, Lehman A, Levine J: Conventional antipsychotic medications for schizophrenia. Schizophr Bull 21:567–577, 1995 Rosenheck R, Desai R, Steinwachs D, et al: Benchmarking treatment of schizophrenia: a comparison of service delivery by the national government and by state and local providers. J Nerv Ment Dis 188:209–216, 2000 Van Putten T, Marder SR, Mintz J: A controlled dose comparison of haloperidol in newly admitted schizophrenia patients. Arch Gen Psychiatry 47:754–758, 1990

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TABLE 10–39. Subtherapeutic antipsychotic dosages for schizophrenia 1.

Summary

Clinical rationale:

This measure assesses the proportion of individuals prescribed an antipsychotic medication for schizophrenia who receive a dosage less than 150 chlorpromazine equivalents. Antipsychotic medications have been shown to be efficacious in the treatment of acute psychotic exacerbations of schizophrenia and in reducing the likelihood of relapse. Randomized controlled trials have demonstrated the efficacy of these agents within a dosage range of 300–1,000 chlorpromazine equivalents. Below this range the likelihood of poor response is increased. Higher dosages on average lead to increased side effects without additional therapeutic benefit.

2. Specifications Denominator:

Enrollees prescribed an antipsychotic medication who had either one inpatient admission or two outpatient visits with a primary diagnosis of schizophrenia over a 12-month period

Numerator:

Patients from the denominator who received a dosage less than 150 chlorpromazine equivalents for more than 4 weeks

Data sources:

Administrative data, medical record

3. Development Developer:

Popkin et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level A. Good research-based evidence

Validity testing:

Positive

Type:

Comparison with the results of other methods or measures, gold standard validity testing

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

17%–26%, 377 Utah Medicaid beneficiaries (Popkin et al. 1998)

Treatment Measures

❚ 333

TABLE 10–39. Subtherapeutic antipsychotic dosages for schizophrenia (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Dixon L, Lehman A, Levine J: Conventional antipsychotic medications for schizophrenia. Schizophr Bull 21:567–577, 1995 Owen R, Thrush C, Kirchner J, et al: Performance measurement for schizophrenia: adherence to guidelines for antipsychotic dose. Int J Qual Health Care 12:475– 482, 2000 Popkin MK, Callies AL, Lurie N, et al: An instrument to evaluate the process of psychiatric care in ambulatory settings. Psychiatr Serv 48:524–527, 1997 Popkin MK, Lurie N, Manning W, et al: Changes in the process of care for Medicaid patients with schizophrenia in Utah’s prepaid mental health plan. Psychiatr Serv 49:518–523, 1998

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TABLE 10–40. Antipsychotic drug use for inpatients with schizophrenia 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of individuals hospitalized for a primary diagnosis of schizophrenia who were prescribed an antipsychotic medication at the time of discharge. Practice guidelines for the treatment of schizophrenia recommend the use of antipsychotic medication to treat the symptoms of an acute psychotic exacerbation. Numerous randomized controlled trials have shown that treatment of positive symptoms of schizophrenia (e.g., hallucinations, delusions, and thought disorganization) with antipsychotic medications is superior to placebo treatment.

Specifications

Denominator:

Inpatients ages 18 and older discharged with a primary diagnosis of schizophrenia during a specified period

Numerator:

Those individuals from the denominator who were prescribed an antipsychotic medication at the time of discharge

Data sources:

Administrative data, medical record

3.

Development

Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia Patient Outcomes Research Team

Users:

American Psychiatric Association

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level A. Good research-based evidence

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

89.2%, 279 inpatients (Lehman and Steinwachs 1998b) 77% (Chen et al. 2000) 97.8%, 224 inpatients from two states (Buchanan et al. 2002)

References and Instruments Buchanan RW, Kreyenbuhl J, Zito JM, et al: The Schizophrenia PORT pharmacological treatment recommendations: conformance and implications for symptoms and functional outcome. Schizophr Bull 28:63–73, 2002 Chen R, Nadkarni P, Levin F, et al: Using a computer database to monitor compliance with pharmacologic guidelines for schizophrenia. Psychiatr Serv 51:791–794, 2000

Treatment Measures

❚ 335

TABLE 10–40. Antipsychotic drug use for inpatients with schizophrenia (continued) Dixon L, Lehman A, Levine J: Conventional antipsychotic medications for schizophrenia. Schizophr Bull 21:567–577, 1995 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b

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TABLE 10–41. Depot antipsychotic medication for schizophrenia 1. Summary

This measure assesses the proportion of individuals treated for schizophrenia who report noncompliance with medications and receive depot antipsychotic medication.

Clinical rationale:

Noncompliance with antipsychotic medication is common and increases the likelihood of relapse and hospitalization of patients with schizophrenia. Practice guidelines, including those from the Schizophrenia Patient Outcomes Research Team (PORT), recommend that individuals with relapse secondary to noncompliance be treated with depot antipsychotic drugs, long-acting agents requiring intramuscular administration one or two times per month. Research comparing oral and depot formulations shows better compliance with depot formulations but no clear advantage in relapse rates.

2. Specifications Denominator:

Patients ages 18 and older with a current diagnosis of schizophrenia and a current prescription for antipsychotic medications who report noncompliance with their medication regimen

Numerator:

Patients in the denominator who receive depot antipsychotic medication

Data sources:

Administrative data, medical record, patient survey/ instrument

3. Development Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia PORT

Users:

American Psychiatric Association

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

13.3%–50%, inpatients (Lehman and Steinwachs 1998b) 24.8%–35%, outpatients (Lehman and Steinwachs 1998b)

Treatment Measures

❚ 337

TABLE 10–41. Depot antipsychotic medication for schizophrenia (continued) References and Instruments Adams CE, Eisenbruch M: Depot fluphenazine for schizophrenia. Cochrane Database Syst Rev (2):CD000307, 2000 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Quraishi S, David A: Depot haloperidol decanoate for schizophrenia. Cochrane Database Syst Rev (2):CD001361, 2000 Quraishi S, David A: Depot perphenazine decanoate and enanthate for schizophrenia. Cochrane Database Syst Rev (2):CD001717, 2000

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TABLE 10–42. Family involvement in schizophrenia treatment 1. Summary

This measure assesses the proportion of consumers treated for schizophrenia or schizoaffective disorder and in close contact with family members whose medical record contains documentation of family involvement in treatment during the past year.

Clinical rationale:

Randomized controlled trials have shown that interventions directed at family members of individuals with schizophrenia can improve outcomes for both patients and families. These interventions include educating families about schizophrenia, providing support, and training families in problem solving and intervening during crisis situations. Less is known about the association between lessintensive family involvement in treatment and patient outcomes.

2. Specifications Denominator:

The number of consumers between the ages of 18 and 65 in treatment for at least 3 months with a diagnosis of schizophrenia or schizoaffective disorder (during that time having at least one visit with a psychiatrist and no more than 21 days in the hospital) who either live with family members or have contact with them two or more times per week

Numerator:

Consumers from the denominator whose medical record contains documentation of a family member’s recent involvement in treatment (e.g., family meeting or phone contact with clinician) during the 1-year period

Data sources:

Administrative data, medical record, patient survey/ instrument

3. Development Developer:

Young et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

43%, 153 patients at two public mental health clinics (Young et al. 1998)

Treatment Measures

❚ 339

TABLE 10–42. Family involvement in schizophrenia treatment (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Dixon LB, Lehman AF: Family interventions for schizophrenia. Schizophr Bull 21:631–643, 1995 Dixon L, McFarlane WR, Lefley H, et al: Evidence-based practices for services to families of people with psychiatric disabilities. Psychiatr Serv 52:903–910, 2001 Hogarty GE, Anderson CM, Reiss DJ, et al: Family psychoeducation, social skills training, and maintenance chemotherapy in the aftercare treatment of schizophrenia, II: two-year effects of a controlled study on relapse and adjustment. Arch Gen Psychiatry 48:340–347, 1991 Young A, Sullivan G, Burnam A, et al: Measuring the quality of outpatient treatment for schizophrenia. Arch Gen Psychiatry 55:611–617, 1998

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TABLE 10–43. Family treatment for schizophrenia 1. Summary

This measure assesses the proportion of individuals treated for schizophrenia whose families have received therapy, education, or a support program.

Clinical rationale:

Randomized controlled trials have shown that interventions directed at family members of individuals with schizophrenia can improve outcomes for both patients and families. These interventions include educating families about schizophrenia, providing support, and training families in problem solving. Less is known about the association between less-intensive family intervention and outcomes.

2. Specifications Denominator:

All patients ages 18 and older in a plan who are in active treatment for schizophrenia and have ongoing contact with their families

Numerator:

Individuals in the denominator whose medical record documents provision of “family therapy or support” in the treatment plan or report in response to a survey that a family member has received information about schizophrenia or attended an educational or support program

Data sources:

Administrative data, medical record, patient survey/ instrument

3. Development Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia Patient Outcomes Research Team

Users:

American Psychiatric Association

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

37.2% outpatients, 40.8% inpatients (Lehman and Steinwachs 1998b) 31.6% Veterans Affairs (VA) inpatients, 41.2% non-VA inpatients, 22.2% VA outpatients, 29.8% non-VA outpatients (Rosenheck et al. 2000)

Treatment Measures

❚ 341

TABLE 10–43. Family treatment for schizophrenia (continued) References and Instruments Dixon L, Lyles A, Scott J, et al: Services to families of adults with schizophrenia: from treatment recommendations to dissemination. Psychiatr Serv 50:233–238, 1999 Dixon L, Adams C, Lucksted A: Update on family psychoeducation for schizophrenia. Schizophr Bull 26:5–20, 2000 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Rosenheck R, Desai R, Steinwachs D, et al: Benchmarking treatment of schizophrenia: a comparison of service delivery by the national government and by state and local providers. J Nerv Ment Dis 188:209–216, 2000

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TABLE 10–44. Maintenance antipsychotic drug duration for schizophrenia 1. Summary

This measure assesses the proportion of adults with a primary diagnosis of schizophrenia discharged after an inpatient stay who continued to receive antipsychotic medication for 12 months following discharge.

Clinical rationale:

Practice guidelines recommend maintenance treatment with an antipsychotic medication for individuals with schizophrenia following treatment of an acute psychotic exacerbation. Controlled trials have shown that patients who receive antipsychotic medication for 1 year after an acute psychiatric episode experience a lower likelihood of relapse compared with patients treated with a placebo.

2. Specifications Denominator:

Individuals ages 18 and older with a primary diagnosis of schizophrenia discharged during a specified time following an inpatient stay who received an antipsychotic medication on discharge

Numerator:

Those individuals from the denominator who continued to receive an antipsychotic medication for the 12-month period following discharge

Data sources:

Administrative data, medical record

3.

Development

Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia Patient Outcomes Research Team

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level A. Good research-based evidence

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

96.1%, 358 outpatients in two states (Buchanan et al., 2002)

References and Instruments Buchanan RW, Kreyenbuhl J, Zito JM, et al: The schizophrenia PORT pharmacological treatment recommendations: conformance and implications for symptoms and functional outcome. Schizophr Bull 28:63– 73, 2002

Treatment Measures

❚ 343

TABLE 10–44. Maintenance antipsychotic drug duration for schizophrenia (continued) Dixon L, Lehman A, Levine J: Conventional antipsychotic medications for schizophrenia. Schizophr Bull 21:567–577, 1995 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Robinson D, Woerner MG, Alvir JM, et al: Predictors of relapse following response from a first episode of schizophrenia or schizoaffective disorder. Arch Gen Psychiatry 56:241–247, 1999

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TABLE 10–45. Educating individuals with schizophrenia about medications 1. Summary

This measure assesses the proportion of individuals in outpatient treatment for schizophrenia who receive education about their prescribed medications and side effects.

Clinical rationale:

Educating patients about the benefits and side effects of prescribed medications is a basic and essential component of clinical practice. Individuals with schizophrenia have rates of nonadherence to prescribed medications exceeding 40%. Although education alone has not been found to improve adherence, education is one component of multimodal interventions that have improved adherence and clinical outcomes.

2. Specifications Denominator:

Enrollees who had either one inpatient admission or two outpatient visits with a primary diagnosis of schizophrenia within a 12-month period

Numerator:

Patients from the denominator whose medical record documented that the patient received education about his or her prescribed medications and side effects

Data sources:

Administrative data, medical record

3.

Development

Developer:

Popkin et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Incomplete

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

63%–77%, 377 Utah Medicaid beneficiaries (Popkin et al. 1998)

References and Instruments Azrin NH, Teichner G: Evaluation of an instructional program for improving medication compliance for chronically mentally ill outpatients. Behav Res Ther 36:849–861, 1998 Hornung WP, Klingberg S, Feldmann R, et al: Collaboration with drug treatment by schizophrenic patients with and without psychoeducational training: results of a 1year follow-up. Acta Psychiatr Scand 97:213–219, 1998

Treatment Measures

❚ 345

TABLE 10–45. Educating individuals with schizophrenia about medications (continued) Kemp R, Kirov G, Everitt B, et al: Randomised controlled trial of compliance therapy: 18-month follow-up. Br J Psychiatry 172:413–419, 1998 Popkin MK, Callies AL, Lurie N, et al: An instrument to evaluate the process of psychiatric care in ambulatory settings. Psychiatr Serv 48:524–527, 1997 Popkin MK, Lurie N, Manning W, et al: Changes in the process of care for Medicaid patients with schizophrenia in Utah’s prepaid mental health plan. Psychiatr Serv 49:518–523, 1998

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TABLE 10–46. Medication treatment of comorbid anxiety in schizophrenia 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of individuals with diagnoses of schizophrenia and an anxiety disorder who are prescribed either a benzodiazepine or propanolol. Persistent symptoms of anxiety may be seen in individuals with schizophrenia. Research studies support the efficacy of benzodiazepines for treatment of schizophrenia, although response is typically modest and seen in only a subset of patients. Studies of propanolol are less extensive and conclusive. Practice guidelines, including those from the Schizophrenia Patient Outcomes Research Team (PORT), recommend a trial of one these agents for anxiety that persists despite use of an antipsychotic medication for schizophrenia.

Specifications

Denominator:

All patients ages 18 and older with a current diagnosis of schizophrenia who report a current diagnosis of anxiety disorder or who have a current chart diagnosis of comorbid anxiety disorder at a specified point in time

Numerator:

Patients in the denominator whose medical record documents prescription of either a benzodiazepine or propranolol

Data sources:

Administrative data, medical record, patient survey/ instrument

3.

Development

Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia PORT

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

33.3% inpatients, 41.3% outpatients (Lehman and Steinwachs 1998b) 47.5% Veterans Affairs (VA) inpatients, 65.4% non-VA inpatients, 36.4% VA outpatient, 46.4% non-VA outpatient (Rosenheck et al. 2000)

Treatment Measures

❚ 347

TABLE 10–46. Medication treatment of comorbid anxiety in schizophrenia (continued) References and Instruments Johns CA, Thompson JW: Adjunctive treatments in schizophrenia: pharmacotherapies and electroconvulsive therapy. Schizophr Bull 21:607–619, 1995 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Rosenheck R, Desai R, Steinwachs D, et al: Benchmarking treatment of schizophrenia: a comparison of service delivery by the national government and by state and local providers. J Nerv Ment Dis 188:209–216, 2000 Wolkowitz OM, Pickar D: Benzodiazepines in the treatment of schizophrenia: a review and reappraisal. Am J Psychiatry 148:714–726, 1991

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IMPROVING MENTAL HEALTHCARE

TABLE 10–47. Medication treatment of comorbid depression in schizophrenia 1. Summary

This measure assesses the proportion of individuals with schizophrenia and concurrent depression who are prescribed an antidepressant medication.

Clinical rationale:

Depressive symptoms or syndromes are frequently seen among individuals with schizophrenia. Research studies show that depression can be efficaciously treated with an antidepressant medication in this population, and practice guidelines recommend their use. However, many such patients are not treated.

2.

Specifications

Denominator:

All individuals ages 18 and older with a current diagnosis of schizophrenia who score within the upper quartile of the Symptom Checklist–90 or report a current diagnosis of depression or who have a current chart diagnosis of depression at a specified point in time

Numerator:

Patients in the denominator who are prescribed an antidepressant

Data sources:

Administrative data, medical record, patient survey/ instrument

3. Development Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia Patient Outcomes Research Team

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

33.8% inpatients, 45.7% outpatients (Lehman and Steinwachs 1998b) 25.1% Veterans Affairs (VA) inpatients, 32.1% non-VA inpatients, 33.6% VA outpatients, 34.6% non-VA outpatients (Rosenheck et al. 2000)

References and Instruments Johns CA, Thompson JW: Adjunctive treatments in schizophrenia: pharmacotherapies and electroconvulsive therapy. Schizophr Bull 21:607–619, 1995

Treatment Measures

❚ 349

TABLE 10–47. Medication treatment of comorbid depression in schizophrenia (continued) Kramer MS, Vogel WH, DiJohnson C, et al: Antidepressants in “depressed” schizophrenic inpatients: a controlled trial. Arch Gen Psychiatry 46:922–928, 1989 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Plasky P: Antidepressant usage in schizophrenia. Schizophr Bull 17:649–657, 1991 Rosenheck R, Desai R, Steinwachs D, et al: Benchmarking treatment of schizophrenia: a comparison of service delivery by the national government and by state and local providers. J Nerv Ment Dis 188:209–216, 2000 Siris SG: Diagnosis of secondary depression in schizophrenia: implications for DSMIV. Schizophr Bull 17:75–98, 1991

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TABLE 10–48. Assertive community treatment (ACT) program utilization for individuals with schizophrenia 1. Summary

This measure assesses the proportion of individuals with schizophrenia with high inpatient and/or emergency department utilization who are enrolled in an ACT program.

Clinical rationale:

ACT programs provide intensive community-based care to individuals with severe and persistent mental illness, including case management services, outreach, and multidisciplinary coordination. Controlled trials comparing ACT with other treatment modalities have found that ACT significantly contributes to maintaining the continuity of mental health services, reduces inpatient admissions and emergency department visits, and increases the likelihood of independent living and patient satisfaction. Among individuals with dual diagnoses, ACT has been shown to improve some measures of substance abuse and quality of life but did not result in higher remission rates. ACT services are resource intensive; their cost-effectiveness is enhanced by targeting enrollment. Consumer advocates have expressed concern that ACT programs are underused.

2.

Specifications

Denominator:

Number of adult patients in a plan who have two or more inpatient stays or four emergency department crisis visits with a diagnosis of schizophrenia in the prior 12-month period

Numerator:

Number of patients in the denominator who are enrolled in an ACT program

Data sources:

Administrative data, medical record

3. Development Developer:

American Psychiatric Association (APA)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

APA Task Force on Quality Indicators

Development:

Under development

4.

Properties

Evidence basis: 5.

AHRQ Level A. Good research-based evidence

Use

Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

Greater than 50% (American Psychiatric Association 1999)

Treatment Measures

❚ 351

TABLE 10–48. Assertive community treatment (ACT) program utilization for individuals with schizophrenia (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1999 Burns BJ, Santos AB: Assertive community treatment: an update of randomized trials. Psychiatr Serv 46:669–675, 1995 Lehman AF, Dixon LB, Kernan E, et al: A randomized trial of assertive community treatment for homeless persons with severe mental illness. Arch Gen Psychiatry 54:1038–1043, 1997 Marshall M, Lockwood A: Assertive community treatment for people with severe mental disorders. Cochrane Database Syst Rev (2):CD001089, 2000

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TABLE 10–49. Polypharmacy in schizophrenia 1.

Summary

Clinical rationale:

This measure assesses the proportion of individuals treated for schizophrenia who are simultaneously prescribed four or more psychotropic drugs. Recent data suggest that polypharmacy (i.e., receiving multiple medications) among individuals with schizophrenia is common. Interpretation of this finding is controversial. Some argue that polypharmacy is suggestive of indiscriminant diagnostic and prescribing practices. Although many patients with schizophrenia may fail to respond sufficiently to an initial trial of an antipsychotic drug, practice guidelines typically recommend sequential medication trials. On the other hand, some evidence supports augmentation strategies for treatment-resistant psychosis, and practice guidelines also recommend adjunctive pharmacotherapy for anxiety and depressive disorders that can co-occur with schizophrenia. Prescription of multiple medications requires caution because of the potential for drug interactions and side effects. No research studies have examined the relationship between the number of psychotropic medications prescribed and clinical outcomes in schizophrenia.

2. Specifications Denominator:

Medicaid beneficiaries who had either one inpatient admission or two outpatient visits with a primary diagnosis of schizophrenia during a 12-month period

Numerator:

Patients from the denominator prescribed four or more psychotropic drugs (antipsychotics, antidepressants, anxiolytics, mood stabilizers, or antiparkinsonian agents) simultaneously for at least 1 month during the 12-month period

Data sources:

Administrative data, medical record

3. Development Developer:

Popkin et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

8%–13%, 377 Utah Medicaid beneficiaries (Popkin et al. 1998)

Treatment Measures

❚ 353

TABLE 10–49. Polypharmacy in schizophrenia (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Covell NH, Jackson CT, Evans AC, et al: Antipsychotic prescribing practices in Connecticut’s public mental health system: rates of changing medications and prescribing styles. Schizophr Bull 28:17–29, 2002 Popkin MK, Callies AL, Lurie N, et al: An instrument to evaluate the process of psychiatric care in ambulatory settings. Psychiatr Serv 48:524–527, 1997 Popkin MK, Lurie N, Manning W, et al: Changes in the process of care for Medicaid patients with schizophrenia in Utah’s prepaid mental health plan. Psychiatr Serv 49:518–523, 1998 Stahl SM: Antipsychotic polypharmacy, part 1: therapeutic option or dirty little secret? J Clin Psychiatry 60:425–426, 1999 Weissman EM: Antipsychotic prescribing practices in the Veterans Healthcare Administration–New York metropolitan region. Schizophr Bull 28:31–42, 2002

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TABLE 10–50. Psychotherapy treatment for schizophrenia 1. Summary

This measure assesses the proportion of individuals diagnosed with schizophrenia who receive psychotherapy that is problem focused.

Clinical rationale:

Evidence is gradually emerging on the efficacy of specific psychotherapies for schizophrenia. Controlled trials have found that 1) psychodynamic therapy has not been shown to be effective in several studies; 2) personal therapy, a modality that combines psychoeducational and supportive principles with an emphasis on affective regulation, has been shown to lead to improvement in several desirable outcomes; 3) social skills training has been shown to decrease relapse rates and improve adjustment; and 4) cognitive remediation has led to improvement in attention and symptoms. Other approaches, including group and supportive therapy, have not been well studied. Although administrative databases and medical records may document the provision of psychotherapy, they typically contain little indication of the type or content of psychotherapy provided.

2. Specifications Denominator:

All individuals ages 18 and older in active treatment for schizophrenia during a specified interval

Numerator:

All individuals from the denominator 1) whose treatment plan includes individual or group psychotherapy, and 2) who reported that the therapy focused on one or more of the following problems: difficult feelings or thoughts; getting along with others; understanding a diagnosis, illness, or medications; housing or employment

Data sources:

Administrative data, medical record

3. Development Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia Patient Outcomes Research Team

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Treatment Measures

❚ 355

TABLE 10–50. Psychotherapy treatment for schizophrenia (continued) Selected results:

96.5% inpatients prescribed either individual or group therapy at discharge, 64.7% inpatients receiving help for at least one life problem, 45.0% outpatients receiving group or individual therapy, 76.7% outpatients receiving help for at least one life problem (Lehman and Steinwachs 1998b) 35.8% Veterans Affairs (VA) inpatients, 51.2% non-VA inpatients, 51.1% VA outpatients, 52.7% non-VA outpatients (Rosenheck et al. 2000)

References and Instruments Hogarty GE, Kornblith SJ, Greenwald D, et al: Three-year trials of personal therapy among schizophrenic patients living with or independent of family, I: description of study and effects on relapse rates. Am J Psychiatry 154:1504–1513, 1997 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Mojtabai R, Nicholson RA, Carpenter BN: Role of psychosocial treatments in management of schizophrenia: a meta-analytic review of controlled outcome studies. Schizophr Bull 24:569–587, 1998 Rosenheck R, Desai R, Steinwachs D, et al: Benchmarking treatment of schizophrenia: a comparison of service delivery by the national government and by state and local providers. J Nerv Ment Dis 188:209–216, 2000

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TABLE 10–51. Rationale for outlier dosages for schizophrenia 1. Summary

This measure assesses the proportion of individuals with schizophrenia receiving an antipsychotic medication that is outside the recommended dosage range whose medical record provides a clinical rationale for dosage.

Clinical rationale:

Randomized clinical trials have found that acute positive symptoms of schizophrenia are most likely to respond to a daily antipsychotic dosage between 300 and 1,000 chlorpromazine equivalents. Guidelines from the American Psychiatric Association and the Schizophrenia Patient Outcomes Research Team generally recommend use of dosages within this range. The likelihood of poor response increases below the dosage range, whereas higher dosages on average lead to increased side effects with little added therapeutic benefit. Nonetheless, outlier dosages may be needed for individual patients, given variability of patient response, tolerance of side effects, patient preference, and response to previous dosages. In these cases, practice guidelines recommend that the treating clinician document the rationale in the medical record.

2. Specifications Denominator:

All individuals ages 18 and older with a diagnosis of schizophrenia who are receiving antipsychotic medication at a dosage that is outside the recommended range (300–1,000 chlorpromazine equivalents) at a specified point in time

Numerator:

Individuals in the denominator whose medical record of the preceding 6 months provides documentation for the dosage used

Data sources:

Administrative data, medical record, pharmacy data

3.

Development

Developer:

Center for Quality Assessment and Improvement in Mental Health

Stakeholders:

Clinicians, delivery system managers, researchers

Measure set:

Massachusetts Schizophrenia Quality of Care Study

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Research study

Treatment Measures

❚ 357

TABLE 10–51. Rationale for outlier dosages for schizophrenia (continued) References and Instruments American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1998 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Walkup JT, McAlpine DD, Olfson M, et al: Patients with schizophrenia at risk for excessive antipsychotic dosing. J Clin Psychiatry 61:344–348, 2000

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TABLE 10–52. Availability of medication management and psychotherapy for patients with schizophrenia 1. Summary

This measure assesses the proportion of individuals who are seen at least four times by a psychiatrist during a 1-year period.

Clinical rationale:

Antipsychotic medications are effective in the treatment of acute exacerbations of schizophrenia. Because symptoms can fluctuate over time and because these medications can have adverse side effects, clinical practice guidelines recommend regular monitoring of patients. There has been little research to assess what constitutes adequate or optimal frequency of monitoring. The 1996 Expert Consensus Guideline for Treatment of Schizophrenia recommended monthly visits, at a minimum, for stable outpatients with schizophrenia and more frequent contact for patients with unstable symptoms or functioning. This measure is part of a set of measures proposed for testing and has not been adopted by the developing organization.

2. Specifications Denominator:

All members ages 18 and older enrolled in a health plan with a diagnosis of schizophrenia

Numerator:

Those members from the denominator who had at least four medication management or psychotherapy visits with a psychiatrist during a 12-month period

Data sources:

Administrative data

3. Development Developer:

National Committee for Quality Assurance

Stakeholders:

Accrediting organizations, public sector payers and purchasers, employer purchasers, consumers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Health Plan Employer Data and Information Set 3.0 Testing Set

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Treatment Measures

❚ 359

TABLE 10–52. Availability of medication management and psychotherapy for patients with schizophrenia (continued) References and Instruments Dixon L, Lehman A, Levine J: Conventional antipsychotic medications for schizophrenia. Schizophr Bull 21:567–577, 1995 Expert Consensus Guideline Series: treatment of schizophrenia. J Clin Psychiatry 57:1–59, 1996 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998 National Committee for Quality Assurance: HEDIS 3.0: Test Measures. Washington, DC, National Committee for Quality Assurance, 1999 Robinson D, Woerner MG, Alvir JM, et al: Predictors of relapse following response from a first episode of schizophrenia or schizoaffective disorder. Arch Gen Psychiatry 56:241–247, 1999

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TABLE 10–53. Treatment of akathisia and extrapyramidal symptoms (EPS) in schizophrenia 1. Summary

This measure assesses the proportion of individuals with schizophrenia and significant akathisia or EPS who received an appropriate medication treatment or a decreased antipsychotic dosage or were offered a trial of an atypical antipsychotic agent.

Clinical rationale:

Akathisia and EPS are side effects of antipsychotic medications. Effective clinical responses to these conditions include reduction of the antipsychotic dosage, switching to an atypical agent, or adding a drug that can alleviate the symptoms. Benzodiazepines and beta-blockers have been shown to reduce akathisia, whereas anticholinergic and antiparkinson agents can effectively treat EPS.

2. Specifications Denominator:

The number of consumers ages 18–65 in treatment for at least 3 months with a diagnosis of schizophrenia or schizoaffective disorder (during that time having at least 1 visit with a psychiatrist and no more than 21 days in the hospital) who have significant akathisia or EPS (based on survey responses)

Numerator:

Consumers from the denominator who have one of the following: reduction in antipsychotic dose; switch to a different antipsychotic; addition of a beta-blocker, benzodiazepine, or anticholinergic or antiparkinson agent; or who were offered an atypical antipsychotic

Data sources:

Administrative data, medical record, patient survey/ instrument

3. Development Developer:

Young et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level A. Good research-based evidence

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Endicott J, Spitzer RL, Fleiss JL, et al: The Global Assessment Scale: a procedure for measuring overall severity of psychiatry disturbance. Arch Gen Psychiatry 33:766–771, 1976

Treatment Measures

❚ 361

TABLE 10–53. Treatment of akathisia and extrapyramidal symptoms (EPS) in schizophrenia (continued) Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998 Tonda ME, Guthrie SK: Treatment of acute neuroleptic-induced movement disorders. Pharmacotherapy 14:543–560, 1994 Young A, Sullivan G, Burnam A, et al: Measuring the quality of outpatient treatment for schizophrenia. Arch Gen Psychiatry 55:611–617, 1998

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IMPROVING MENTAL HEALTHCARE

TABLE 10–54. Treatment of drug-related extrapyramidal symptoms (EPS) in schizophrenia 1. Summary

This measure assesses the proportion of patients on an antipsychotic medication who report EPS and are treated with an antiparkinson agent.

Clinical rationale:

Surveys suggest that 50%–75% of individuals who are treated with conventional antipsychotic medications develop some form of EPS—akathasia, dystonia, or parkinsonism. These side effects are distressing to patients and can adversely affect compliance with the medication. Research has established that antiparkinson drugs can treat EPS effectively. The prophylactic use of these agents is more controversial, and guidelines recommend the decision be made on a case-by-case basis.

2. Specifications Denominator:

All patients ages 18 and older with a diagnosis of schizophrenia who receive antipsychotic medication and report on a survey that they experienced EPS

Numerator:

Patients in the denominator who have received a prescription for an antiparkinson medication

Data sources:

Administrative data, medical record, patient survey/ instrument

3. Development Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia Patient Outcomes Research Team

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

53.9% inpatients, 46.1% outpatients (Lehman and Steinwachs 1998b) 69.2% Veterans Affairs (VA) inpatients, 72.7% non-VA inpatients, 56.4% VA outpatients, 56.9% non-VA outpatients (Rosenheck et al. 2000)

Treatment Measures

❚ 363

TABLE 10–54. Treatment of drug-related extrapyramidal symptoms (EPS) in schizophrenia (continued) References and Instruments Assessment of EPS and tardive dyskinesia in clinical trials: collaborative working group on clinical trial evaluations. J Clin Psychiatry 59(suppl):23–27, 1998 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Rifkin A, Siris S: Drug treatment of acute schizophrenia, in Psychopharmacology: The Third Generation of Progress. Edited by Meltzer HY. New York, Raven Press, 1987, pp 1095–1101 Rosenheck R, Desai R, Steinwachs D, et al: Benchmarking treatment of schizophrenia: a comparison of service delivery by the national government and by state and local providers. J Nerv Ment Dis 188:209–216, 2000

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TABLE 10–55. Treatment of residual symptoms in schizophrenia 1. Summary

This measure assesses the proportion of outpatients with residual psychotic symptoms of schizophrenia who had a change in antipsychotic dosage or drug in the past 3 months or were offered clozapine.

Clinical rationale:

Antipsychotic medications are often only partially effective in treating positive symptoms of schizophrenia. Research studies show that residual psychotic symptoms may respond to an increased dosage of the current antipsychotic, a trial of a different antipsychotic agent, or a trial of clozapine.

2. Specifications Denominator:

The number of consumers ages 18–65 with a diagnosis of schizophrenia or schizoaffective disorder in treatment for at least 3 months (during that time having at least one visit with a psychiatrist and no more than 21 days in the hospital) who have significant psychotic symptoms based on the Brief Psychiatric Rating Scale

Numerator:

Consumers from the denominator who had a change in antipsychotic drug or dosage or were offered treatment with clozapine during the 3-month period

Data sources:

Administrative data, medical record, patient survey/ instrument

3.

Development

Developer:

Young et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level A. Good research-based evidence

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

30%, 56 patients at two public mental health clinics (Young et al. 1998)

References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Dixon L, Lehman A, Levine J: Conventional antipsychotic medications for schizophrenia. Schizophr Bull 21:567–577, 1995 Overall JE, Gorham DR: The Brief Psychiatric Rating Scale. Psychol Rep 10:799– 812, 1962

Treatment Measures

❚ 365

TABLE 10–55. Treatment of residual symptoms in schizophrenia (continued) Rosenheck R, Cramer J, Xu W, et al: A comparison of clozapine and haloperidol in hospitalized patients with refractory schizophrenia: Department of Veterans Affairs Cooperative Study Group on Clozapine in Refractory Schizophrenia. N Engl J Med 337:809–815, 1997 Young A, Sullivan G, Burnam A, et al: Measuring the quality of outpatient treatment for schizophrenia. Arch Gen Psychiatry 55:611–617, 1998

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TABLE 10–56. Treatment of tardive dyskinesia (TD) in schizophrenia 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of individuals with schizophrenia and significant TD who received a decreased antipsychotic dosage or were offered a trial of an atypical antipsychotic agent. Antipsychotic medications can cause TD, which is characterized by abnormal repetitive, involuntary neuromuscular movements typically affecting oral/facial regions of the body. Although research evidence does not support neuroleptic cessation for the treatment of TD, some studies show a association between lower dosages of traditional antipsychotic drugs and reductions in TD. In addition, atypical agents such as clozapine, risperidone, olanzapine, or quetiapine may be less likely to cause TD.

Specifications

Denominator:

All consumers ages 18–65 with a diagnosis of schizophrenia or schizoaffective disorder who have been in treatment for at least 3 months, spent no more than 21 days in the hospital during the previous 3 months, have had at least one visit with a psychiatrist during the 3-month period, and have significant TD as indicated by the Abnormal Involuntary Movement Scale

Numerator:

Those consumers from the denominator who had a reduction in antipsychotic dosage during the 3-month period or were offered treatment with clozapine

Data sources:

Administrative data, medical record, patient survey/ instrument, clinician-administered instrument

3. Development Developer:

Young et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Treatment Measures

❚ 367

TABLE 10–56. Treatment of tardive dyskinesia (TD) in schizophrenia (continued) References and Instruments American Psychiatric Association: Tardive Dyskinesia: A Task Force Report of the American Psychiatric Association. Washington, DC, American Psychiatric Press, 1992 American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Guy W (ed): Abnormal Involuntary Movements Scale (AIMS) ECDEU Assessment Manual for Psychopharmacology (Publication ADM 76–338). Washington, DC, U.S. Department of Health, Education, and Welfare, 1976 McGrath JJ, Soares KVS: Neuroleptic reduction and/or cessation and neuroleptics as specific treatments for tardive dyskinesia. Cochrane Database Syst Rev (2):CD000459, 2000 Young A, Sullivan G, Burnam A, et al: Measuring the quality of outpatient treatment for schizophrenia. Arch Gen Psychiatry 55:611–617, 1998

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TABLE 10–57. Use of atypical antipsychotic drugs for schizophrenia 1. Summary

This measure assesses the proportion of patients ages 18 and older with a diagnosis of schizophrenia receiving atypical medications (clozapine, risperidone, olanzapine, quetiapine, ziprasidone) during a specified period.

Clinical rationale:

The atypical antipsychotic medications clozapine, olanzapine, risperidone, quetiapine, and ziprasidone present the mental health care system with trade-offs between benefits and costs. Studies have shown clozapine to have superior efficacy and lower extrapyramidal symptoms compared with traditional antipsychotics, although clozapine’s risk of agranulocytosis requires routine blood monitoring. Most studies have found the other atypical agents to have a superior side effect profile than traditional antipsychotics and comparable efficacy. One exception is a recent randomized controlled study that compared individuals with stable, chronic schizophrenia treated with risperidone with those treated with the traditional antipsychotic haloperidol. The study found that risperidone-treated patients were less likely to experience a relapse within a 1-year period. The cost of atypical antipsychotics is several times greater than the traditional agents. Some public- and private-sector payers have placed restrictions on use of the atypical agents through utilization review and formulary restrictions, and consumer advocates have expressed concern regarding access to these agents.

2.

Specifications

Denominator:

All persons served by a state mental health authority, ages 18 and older, with a diagnosis of schizophrenia at a specified point in time

Numerator:

The number of unduplicated persons from the denominator who received atypical medications (clozapine, olanzapine, risperidone, quetiapine, ziprasidone) during a specified period

Data sources:

Administrative data, pharmacy data

3.

Development

Developer:

National Association of State Mental Health Program Directors (NASMHPD)

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

NASMHPD Performance Measures for Mental Health Systems

Treatment Measures

❚ 369

TABLE 10–57. Use of atypical antipsychotic drugs for schizophrenia (continued) Users:

NASMHPD, Virginia Department of Mental Health, Wisconsin Department of Mental Health

Development:

Incomplete

4. Properties Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Leucht S, Pitschel-Walz G, Abraham D, et al: Efficacy and extrapyramidal sideeffects of the new antipsychotics olanzapine, quetiapine, risperidone, and sertindole compared to conventional antipsychotics and placebo: a meta-analysis of randomized controlled trials. Schizophr Res 35:51–68, 1999 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: NRI Performance Measurement System: National Public Rates, 2002. Available at: http://www.rdmc.org/ nripms. Accessed June 25, 2005. Reid W, Pham V, Rago W: Clozapine use by state programs: public mental health systems respond to a new medication. Hosp Community Psychiatry 44:739–743, 1993 Wahlbeck K, Cheine M, Essali M, et al: Clozapine versus typical neuroleptic medication for schizophrenia. Cochrane Database Syst Rev (2):CD000059, 2000

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TABLE 10–58. Use of atypical antipsychotics for schizophrenia 1. Summary

This measure assesses the proportion of adults with schizophrenia who receive an atypical antipsychotic medication other than clozapine within a specified time period.

Clinical rationale:

The atypical antipsychotic medications olanzapine, risperidone, quetiapine, and ziprasidone present the mental health care system with trade-offs between costs and benefits. Most studies have found the atypical agents, whose cost is several times greater than traditional antipsychotics, to have comparable efficacy with a superior side effect profile. However, a recent randomized controlled study compared individuals with stable, chronic schizophrenia treated with risperidone with those treated with the traditional antipsychotic haloperidol and found that risperidone-treated patients were less likely to experience a relapse within a 1-year period. Some public- and privatesector payers have placed restrictions on the utilization of atypical antipsychotics, and consumer advocates have expressed concern regarding access to these agents.

2. Specifications Denominator:

The unduplicated number of adults (over the age of 18) with a diagnosis of schizophrenia utilizing mental health services within a specified time period

Numerator:

The number of adults in the denominator who received at least one dose of the atypical antipsychotics (risperidone, olanzapine, quetiapine, ziprasidone) during the specified time period

Data sources:

Administrative data, pharmacy data

3. Development Developer:

American Psychiatric Association (APA)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

APA Task Force on Quality Indicators

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

20%–40% (American Psychiatric Association 1999)

Treatment Measures

❚ 371

TABLE 10–58. Use of atypical antipsychotics for schizophrenia (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1999 Csernansky JG, Mahmoud R, Brenner R: A comparison of risperidone and haloperidol for the prevention of relapse in patients with schizophrenia: The Risperidone-USA-79 Study Group. N Engl J Med 346:16–22, 2002 Frankenburg FR: Choices in antipsychotic therapy in schizophrenia. Harv Rev Psychiatry 6:241–249, 1999 Leucht S, Pitschel-Walz G, Abraham D, et al: Efficacy and extrapyramidal sideeffects of the new antipsychotics olanzapine, quetiapine, risperidone, and sertindole compared to conventional antipsychotics and placebo: a meta-analysis of randomized controlled trials. Schizophr Res 35:51–68, 1999

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TABLE 10–59. Vocational rehabilitation for schizophrenia 1. Summary

This measure assesses the proportion of individuals with schizophrenia who are candidates for vocational services and receive these services.

Clinical rationale:

Securing employment is a goal for many individuals with schizophrenia. There are several models for providing assistance, including education and training, job finding, sheltered employment, and supported employment. Research findings are mixed but have found that individual placement and support, in which employment specialists help patients to obtain competitive jobs and provide ongoing support, and enhanced vocational rehabilitation, in which stepwise vocational services are delivered by rehabilitation agencies, are associated with attaining and sustaining paid employment but have been less successful in retaining individuals in competitive employment or improving outcomes outside of employment. Studies examining predictors of successful use of vocational services suggest these services should be made available to individuals with schizophrenia who identify employment as a goal, have a history of competitive employment, have a minimal history of psychiatric hospitalization, or have been assessed as having good work skills.

2.

Specifications

Denominator:

Individuals ages 18 and older in active treatment for schizophrenia who at a specified point in time 1) report in a survey that they are currently employed and have a prior work history or are actively looking for a job, or 2) are currently employed

Numerator:

Those individuals in the denominator 1) who report participating in a program to help them find a job or for whom vocational rehabilitation is prescribed in their treatment plan, or 2) who report receiving assistance from an employment specialist

Data sources:

Administrative data, medical record, patient survey/ instrument

3. Development Developer:

Lehman and Steinwachs 1998a

Stakeholders:

Clinicians, researchers

Measure set:

Schizophrenia Patient Outcomes Research Team

Development:

Incomplete

Treatment Measures

❚ 373

TABLE 10–59. Vocational rehabilitation for schizophrenia (continued) 4. Properties Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

30.4% inpatients, 22.5% outpatients (Lehman and Steinwachs 1998b) 16.8% Veterans Affairs (VA) inpatients, 21.9% non-VA outpatients, 10.7% VA outpatients, 26.4% non-VA outpatients (Rosenheck et al. 2000)

References and Instruments Drake RE, McHugo GJ, Bebout RR, et al: A randomized clinical trial of supported employment for inner-city patients with severe mental disorders. Arch Gen Psychiatry 56:627–633, 1999 Lehman AF: Vocational rehabilitation in schizophrenia. Schizophr Bull 21:645–656, 1995 Lehman A, Steinwachs D: At issue: translating research into practice. The Schizophrenia Patient Outcomes Research Team (PORT) treatment recommendations. Schizophr Bull 24:1–10, 1998a Lehman A, Steinwachs D: Patterns of usual care for schizophrenia: initial results from the Schizophrenia Patient Outcomes Research Team (PORT) client survey. Schizophr Bull 24:11–20, 1998b Lehman AF, Goldberg R, Dixon LB, et al: Improving employment outcomes for persons with severe mental illnesses. Arch Gen Psychiatry 59:165–172, 2002 Rosenheck R, Desai R, Steinwachs D, et al: Benchmarking treatment of schizophrenia: a comparison of service delivery by the national government and by state and local providers. J Nerv Ment Dis 188:209–216, 2000

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TABLE 10–60. Retention rate for chemical dependency treatment 1. Summary

This measure assesses the proportion of patients in a residential or outpatient chemical dependency treatment program who completed the program or remained in treatment for at least 3 months.

Clinical rationale:

Many individuals with substance use disorders leave treatment prematurely. Although confounded by other patient characteristics, research suggests that patients who leave prior to completing a prescribed treatment course have a greater likelihood of relapse and lower levels of functioning than those who complete the course. In particular, individuals who remain in treatment for 3 months or longer experience greater reductions in substance abuse than individuals who remain in treatment for shorter durations. Although clinicians have limited influence with regard to patient engagement in treatment, strategies have been proposed to engage and motivate individuals at risk for early dropout.

2. Specifications Denominator:

Total number of clients discharged from an outpatient or residential chemical dependency treatment program during a specified period who either completed the program or had a length of stay of 1 month or longer

Numerator:

Number of clients in the denominator who either completed the program (i.e., their reason for discharge was “all or most treatment goals met” on PAS-45, item 18) or had participated in the program for 3 months or longer at time of discharge

Data sources:

Proprietary client data system

Alternate versions:

Length of treatment: 6 months, 1 year

3. Development Developer:

New York State Office of Alcoholism and Substance Abuse Services (NYS-OASAS)

Stakeholders:

Public sector payers and purchasers, clinicians

Measure set:

NYS-OASAS Integrated Program Monitoring and Evaluation System Measures

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

❚ 375

Treatment Measures

TABLE 10–60. Retention rate for chemical dependency treatment (continued) 5.

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Standards:

Version

User

3 month: 55%–80%

NYS-OASAS 2000

6 month: 40%–65%

NYS-OASAS 2000

1 year: 25%–50%

NYS-OASAS 2000

References and Instruments Hser YI, Grella CE, Hubbard RL, et al: An evaluation of drug treatments for adolescents in four US cities. Arch Gen Psychiatry 58:689–695, 2001 Hubbard RL, Craddock SG, Lynn PM, et al: Overview of 1-year follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychol Addict Behav 11:261–278, 1997 New York State Office of Alcoholism and Substance Abuse Services (NYS-OASAS): IPMES/Workscope Objective Attainment System: FY2000 and 2000–2001. Albany, NY, New York State Office of Alcoholism and Substance Abuse Services, 2000 New York State Office of Alcoholism and Substance Abuse Services (NYS-OASAS): PAS-45: Client Discharge Reporting Form. 2005. Available at: http:// oasasapps.oasas.state.ny.us/. Accessed on June 30, 2005. Simpson DD: Treatment for drug abuse: follow-up outcomes and length of time spent. Arch Gen Psychiatry 38:875–880, 1981 Simpson DD, Joe GW, Rowan-Szal GA, et al: Drug abuse treatment process components that improve retention. J Subst Abuse Treat 14:565–572, 1997

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TABLE 10–61. Completion of treatment for substance abuse 1. Summary

This measure assesses the proportion of patients discharged from a substance abuse treatment program whose records indicate that they have successfully completed treatment.

Clinical rationale:

Many individuals with substance abuse disorders terminate treatment prematurely. Although limited by confounding with other patient characteristics, research suggests that patients who leave prior to completing a course of treatment have a greater likelihood of relapse and lower functioning than patients who complete the course of treatment. Although clinicians have limited influence with regard to patient engagement in treatment, strategies have been proposed to engage and motivate individuals at risk for early dropout.

2. Specifications Denominator:

All adult patients ages 18 and older discharged from a statefunded substance abuse treatment program during a specified interval, excluding those who were reassessed as inappropriate for the program, were discharged due to loss of program funding, or died

Numerator:

Patients from the denominator whose records contain a discharge note indicating they met at least 75% of 1) their planned duration of stay (documented on the treatment plan) and 2) the behavioral objectives identified in their treatment plan

Data sources:

Medical record, proprietary client data system

Alternate versions:

Population: Child/Adolescent (< age 18)

3. Development Developer:

Texas Commission on Alcohol and Drug Abuse (TCADA)

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, researchers

Measure set:

TCADA Quality Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

❚ 377

Treatment Measures

TABLE 10–61. Completion of treatment for substance abuse (continued) 5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results: Version

Conformance

Standard

User

Outpatient

43%–51%

50%

TCADA 1999

Residential

67%–72%

70%

TCADA 1999

Outpatient

40%–59%

50%

TCADA 1999

Residential

38%–63%

60%

TCADA 1999

Adult

Child/Adolescent

References and Instruments Dalrymple AJ, Fata M: Cross-validating factors associated with discharges against medical advice. Can J Psychiatry 38:285–289, 1993 Jainchill N, Hawke J, De Leon G, et al: Adolescents in therapeutic communities: one-year post-treatment outcomes. J Psychoactive Drugs 32:81–94, 2000 Moos RH, King MJ: Participation in community residential treatment and substance abuse patients’ outcomes at discharge. J Subst Abuse Treat 14:71–80, 1997 Pages KP, Russo JE, Wingerson DK, et al: Predictors and outcome of discharge against medical advice from the psychiatric units of a general hospital. Psychiatr Serv 49:1187–1192, 1998 Texas Commission on Alcohol And Drug Abuse (TCADA): Definition source: 40 Tex.Admin.Code Section 144.552. Data TCADA Behavioral Health Integrated System. Austin, TX, Texas Commission on Alcohol And Drug Abuse, 1999

378

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–62. Family involvement in substance abuse treatment 1. Summary

This measure assesses the proportion of individuals treated for substance use disorders whose family members also received services.

Clinical rationale:

Family members of individuals with substance use disorders may be adversely affected by disorder-related phenomena including lost wages, domestic violence, depression, and poor role modeling. Children of such individuals have been shown to be at higher risk for substance use disorders themselves. Studies have shown that providing risk assessment, support, parent training, and treatment to family members can strengthen family functioning.

2. Specifications Denominator:

The total number of members ages 18 and older enrolled in a health plan who report using alcohol or other drug treatment services

Numerator:

The number of respondents from the denominator who report that their family members and/or significant others received preventive interventions

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Washington Circle Group (WCG)

Stakeholders:

Accrediting organizations, public sector payers and purchasers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

WCG Core Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

References and Instruments Catalano RF, Gainey RR, Fleming CB, et al: An experimental intervention with families of substance abusers: one-year follow-up of the Focus on Families project. Addiction 94:241–254, 1999

Treatment Measures

❚ 379

TABLE 10–62. Family involvement in substance abuse treatment (continued) McCorry F, Garnick D, Bartlett J, et al: Improving Performance Measurement for Alcohol and Other Drug Services: Report of the Washington Circle Group. Rockville, MD, Washington Circle Group and the Center for Substance Abuse Treatment, 2000 Moos RH, Mertens JR, Brennan PL: Program characteristics and readmission among older substance abuse patients: comparisons with middle-aged and younger patients. J Ment Health Adm 22:332–345, 1995 Ruma PR, Burke RV, Thompson RW: Group parent training: is it effective for children of all ages? Behav Ther 27:159–169, 1996

380

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–63. Maintenance pharmacotherapy for substance abuse 1. Summary

This measure assesses the proportion of patients with a diagnosis of opioid or alcohol dependence who receive treatment for longer than 30 days with at least one of the following pharmacological agents: methadone, buprenorphine, naltrexone, or disulfiram.

Clinical rationale:

Research evidence indicates that psychopharmacologic agents are helpful adjuncts in maintaining abstinence from opioids and alcohol in individuals with substance-related disorders, although outcomes vary depending on the particular medication. Substances such as methadone, buprenorphine, naltrexone, and disulfiram either block effects associated with the abused agent or cause the abused substance to be less tolerable. Although there are few data on utilization of most of these drugs, several are believed to be underused.

2. Specifications Denominator:

Patients who receive a service-related diagnosis of opioid or alcohol dependence during a specified period

Numerator:

Those patients in the denominator who receive at least 30 days of treatment with one or more appropriate medications (methadone, buprenorphine, or naltrexone for opiate dependence; naltrexone or disulfiram for alcohol dependence) during a specified interval

Data sources:

Administrative data, pharmacy data

3. Development Developer:

American Psychiatric Association (APA)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

APA Task Force on Quality Indicators

Development:

Under development

4.

Properties

Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

20% (American Psychiatric Association 1999)

Treatment Measures

❚ 381

TABLE 10–63. Maintenance pharmacotherapy for substance abuse (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Substance Use Disorders: Alcohol, Cocaine, Opioids. Washington, DC, American Psychiatric Association, 1996 American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1999 Fuller RK, Roth HP: Disulfuram for the treatment of alcoholism: an evaluation of 128 men. Ann Intern Med 90:901–904, 1979 Garbutt JC, West SL, Carey TS, et al: Pharmacological treatment of alcohol dependence: a review of the evidence. JAMA 281:1318–1325, 1999 Johnson RE, Jaffe JH, Fudula PJ: A controlled trial of buprenorphine treatment for opioid dependence. JAMA 267:2750–2755, 1992 Strain EC, Bigelow GE, Liebson IA, et al: Moderate vs. high-dose methadone in the treatment of opioid dependence: a randomized trial. JAMA 281:1000–1005, 1999 Volpicelli JR, Rhines KC, Rhines JS, et al: Naltrexone and alcohol dependence: role of subject compliance. Arch Gen Psychiatry 54:737–742, 1997

382

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–64. Patient experience of alcohol counseling 1. Summary

This measure assesses patient ratings of the helpfulness and importance of clinicians’ information/advice about reducing alcohol use.

Clinical rationale:

Brief interventions by primary care clinicians have been found to reduce alcohol abuse in randomized controlled trials. Interventions include motivational counseling, advice, education and contracting information, and use of drinking diaries. Research also suggests that the quality of communication may influence patient satisfaction.

2. Specifications Denominator:

Number of noninstitutionalized individuals ages 18 year or older with continuous plan enrollment and at least one provider contact in the past 12 months who reported that their clinician gave them information/advice about reducing alcohol use (question 6, item b) and who responded to two or more of the four items on question 7 of the Foundation for Accountability (FACCT) survey

Numerator:

Sum of numeric responses on FACCT survey questions: 7a+7b +7c+7d: 7a) Way in which the information was provided (0 [very poor]–5 [excellent]) 7b) Sensitivity and understanding of the clinician (0 [very poor]–5 [excellent]) 7c) Importance of advice (0 [not at all important]–4 [very important]) 7d) Helpfulness of advice (0 [not at all helpful]–4 [very helpful])

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

FACCT

Stakeholders:

Consumers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

FACCT Alcohol Misuse

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Treatment Measures

❚ 383

TABLE 10–64. Patient experience of alcohol counseling (continued) References and Instruments Fleming MF, Barry KL, Manwell LB, et al: Brief physician advice for problem alcohol drinkers: a randomized controlled trial in community-based primary care practices. JAMA 277:1039–1045, 1997 Foundation for Accountability: FACCT Quality Measures Guide (Alcohol Misuse), Version 1.0. Portland, OR, Foundation for Accountability, 1998 Friedman PD, McCullough D, Chin MH, et al: Screening and intervention for alcohol problems: a national survey of primary care physicians and psychiatrists. J Gen Intern Med 15:84–91, 2000 Stewart M, Brown JB, Boon H, et al: Evidence on patient-doctor communication. Cancer Prev Control 3:25–30, 1999 Wilk AI, Jensen NM, Havighurst TC: Meta-analysis of randomized control trials addressing brief interventions in heavy alcohol drinkers. J Gen Intern Med 12:274– 283, 1997

384

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–65. Program completion for chemical dependency treatment 1. Summary

This measure assesses the proportion of patients receiving inpatient chemical dependency rehabilitation services who completed the program.

Clinical rationale:

Many individuals with substance use disorders leave treatment prematurely. Although limited by confounding with other patient characteristics, research suggests that patients who leave prior to completing a prescribed treatment course have a greater likelihood of relapse and lower levels of functioning than those who complete the course. In particular, individuals who remain in treatment for 3 months or longer experience greater reductions in substance abuse than individuals who remain in treatment for shorter duration. Although clinicians have limited influence with regard to patient engagement in treatment, strategies have been proposed to engage and motivate individuals at risk for early dropout.

2. Specifications Denominator:

Total number of clients who were discharged from a chemical dependency rehabilitation program during a specified period

Numerator:

Number of clients in the denominator who completed the program (i.e., their reason for discharge was “all or most treatment goals met” on PAS-45, item 18)

Data sources:

Proprietary client data system

3. Development Developer:

New York State Office of Alcoholism and Substance Abuse Services (NYS-OASAS)

Stakeholders:

Public sector payers and purchasers, clinicians

Measure set:

NYS-OASAS Integrated Program Monitoring and Evaluation System Measures

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Standards:

25%–75% (NYS-OASAS 2000)

Treatment Measures

❚ 385

TABLE 10–65. Program completion for chemical dependency treatment (continued) References and Instruments Hubbard RL, Craddock SG, Lynn PM, et al: Overview of 1-year follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychol Addict Behav 11:261–278, 1997 New York State Office of Alcoholism and Substance Abuse Services (NYS-OASAS): IPMES/Workscope Objective Attainment System: FY2000 and 2000–2001. Albany, NY, New York State Office of Alcoholism and Substance Abuse Services, 2000 New York State Office of Alcoholism and Substance Abuse Services (NYS-OASAS): PAS-45: Client Discharge Reporting Form. 2005. Available at: http:// oasasapps.oasas.state.ny.us/. Accessed on June 30, 2005. Simpson DD: Treatment for drug abuse: follow-up outcomes and length of time spent. Arch Gen Psychiatry 38:875–880, 1981 Simpson DD, Joe GW, Rowan-Szal GA, et al: Drug abuse treatment process components that improve retention. J Subst Abuse Treat 14:565–572, 1997

386

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–66. Antipsychotic treatment for childhood psychosis 1. Summary

This measure assesses the proportion of children with a diagnosis of a psychotic disorder who receive a trial of an antipsychotic medication with an appropriate dosage and duration.

Clinical rationale:

Practice parameters developed by the American Academy of Child and Adolescent Psychiatry recommend the use of antipsychotic medication for the treatment of childhood schizophrenia and psychotic conditions. Rigorously controlled research in this area is still in its early stage of development. Some experts recommend that children receive antipsychotic medication in the dosage range of 0.5–9.0 mg/kg/day in chlorpromazine equivalents for approximately 6 weeks before drug response can be determined.

2. Specifications Denominator:

The total number of children enrolled in health plan with a service-related diagnosis of a psychotic disorder over a specified period

Numerator:

Those children from the denominator who receive a trial on antipsychotic medication with appropriate dosage and duration

Data sources:

Administrative data, medical record, pharmacy data

3. Development Developer:

American Psychiatric Association (APA)

Stakeholders:

Accrediting organizations, clinicians, researchers, provider organizations

Measure set:

APA Quality Indicators for Children

Development:

Incomplete

4. Properties Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

90% (American Psychiatric Association 2000)

Treatment Measures

❚ 387

TABLE 10–66. Antipsychotic treatment for childhood psychosis (continued) References and Instruments American Psychiatric Association Task Force on Quality Indicators for Children: Workbook of Quality Indicators for Children. Washington, DC, American Psychiatric Association, 2000 Baldessarini R, Teicher M: Dosing of antipsychotic agents in pediatric populations. J Child Adolescent Psychopharmacol 5:1–4, 1995 Campbell M, Rapoport JL, Simpson GM: Antipsychotics in children and adolescents. J Am Acad Child Adolesc Psychiatry 38:537–545, 1999 Findling RL, Grcevich SJ, Lopez I, et al: Antipsychotic medications in children and adolescents. J Clin Psychiatry 57(suppl):19–23, 1996 McClellan J, Werry J: Practice parameters for the assessment and treatment of children and adolescents with schizophrenia. J Am Acad Child Adolesc Psychiatry 36(suppl):117S–193S, 1997

388

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–67. Use of psychotherapy for borderline personality disorder (BPD) 1. Summary

This measure assesses the proportion of individuals with a DSM-IV diagnosis of BPD who have received psychotherapy in a specified time period.

Clinical rationale:

BPD is characterized by emotional reactivity, interpersonal difficulties, low self-esteem, and impulsive self-destructive behavior. A randomized controlled study showed that dialectical behavioral therapy reduced patients’ parasuicidal behavior and rehospitalization. Case-based and observational studies provide some support for the efficacy of other types of psychotherapy. Little is known about service utilization patterns of individuals diagnosed with this condition or their association with outcome.

2.

Specifications

Denominator:

The number of patients with a DSM-IV diagnosis of BPD (DSM-IV code 301.83) in a specified year

Numerator:

Those patients in the denominator who have received psychotherapy during the specified year

Data sources:

Administrative data

3. Development Developer:

American Psychiatric Association (APA)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

APA Task Force on Quality Indicators

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

75% (American Psychiatric Association 1999)

References and Instruments American Psychiatric Association: Report of the American Psychiatric Association Task Force on Quality Indicators. Washington, DC, American Psychiatric Association, 1999 Beatson JA: Long-term psychotherapy in borderline and narcissistic disorders: when is it necessary? Aust N Z J Psychiatry 29:591–597, 1995 Linehan MM: Cognitive-Behavioral Treatment of Borderline Personality Disorder. New York, Guilford, 1993

Treatment Measures

❚ 389

TABLE 10–67. Use of psychotherapy for borderline personality disorder (BPD) (continued) Linehan MM, Armstrong HE, Suarez A, et al: Cognitive-behavioral treatment of chronically parasuicidal borderline patients. Arch Gen Psychiatry 48:1060–1064, 1991

390

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–68. Supported employment for individuals with severe and persistent mental illness (SPMI) 1.

Summary

Clinical rationale:

This measure assesses the proportion of persons with severe mental illness who participated in a supported employment program. Securing employment is a goal for many individuals with SPMI. There are numerous types of vocational rehabilitative interventions, including education and training, job finding, sheltered employment, and supported employment. Supported employment models emphasize helping the client obtain competitive jobs and providing them with ongoing support to maintain the position. A recent randomized controlled trial compared a supported employment program with a vocational rehabilitation approach that emphasized stepwise experience, beginning with training and sheltered workshops. Both interventions were associated with improvement in job satisfaction, earnings, and nonvocational outcomes, but the individuals assigned to the supported employment program achieved higher rates of competitive employment.

2. Specifications Denominator:

Total unduplicated number of persons served in the community ages 18 and older with a serious mental illness during a specified period

Numerator:

The number of persons in the denominator who receive supported employment programs during that period

Data sources:

Administrative data, program enrollment data

3. Development Developer:

National Association of State Mental Health Program Directors (NASMHPD)

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

NASMHPD Performance Measures for Mental Health Systems

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level A. Good research-based evidence

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

2% (SAMHSA 1998)

Treatment Measures

❚ 391

TABLE 10–68. Supported employment for individuals with severe and persistent mental illness (SPMI) (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Bond GR, Drake RE, Mueser KT, et al: An update on supported employment for people with severe mental illness. Psychiatr Serv 48:335–346, 1997 Drake RE, McHugo GJ, Bebout RR, et al: A randomized clinical trial of supported employment for inner-city patients with severe mental disorders. Arch Gen Psychiatry 56:627–633, 1999 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: NRI Performance Measurement System: National Public Rates, 2002. Available at: http://www.rdmc.org/ nripms. Accessed June 25, 2005. Substance Abuse and Mental Health Services Administration (SAMHSA): The Five-State Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Rockville, MD, Substance Abuse and Mental Health Services Administration, 1998

392

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–69. Supported housing for individuals with severe and persistent mental illness (SPMI) 1. Summary

This measure assesses the proportion of persons with serious mental illness who receive supported housing services.

Clinical rationale:

Studies suggest that the majority of individuals in the United States with SPMI lack adequate, stable housing. Research emphasizes the importance of housing for these individuals’ quality of life, along with the importance of privacy and autonomy and choice in housing. “Supported housing” is an approach that emphasizes facilitation of individuals living in independent, community-based housing. Support generally includes assistance with finding an apartment, moving, money management, and integrating clinical and support services. Research on supported housing largely consists of demonstration programs, but analyses have found inpatient service use has declined after patient entry into a supported housing program and that, on average, consumers have preferred the supported housing model over traditional residential programs.

2. Specifications Denominator:

Total unduplicated number of persons served in the community ages 18 and older with a serious mental illness during a specified period

Numerator:

The number of persons in the denominator who receive supported housing services during that period

Data sources:

Administrative data, program enrollment data

3.

Development

Developer:

National Association of State Mental Health Program Directors (NASMHPD)

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

NASMHPD Performance Measures for Mental Health Systems

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

3% (SAMHSA 1998)

Treatment Measures

❚ 393

TABLE 10–69. Supported housing for individuals with severe and persistent mental illness (SPMI) (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Carling PJ, Curtis LC: Implementing supported housing: current trends and future directions. New Dir Ment Health Ser 74:79–94, 1997 Kasprow WJ, Rosenheck RA, Frisman L, et al: Referral and housing processes in a long-term supported housing program for homeless veterans. Psychiatr Serv 51:1017–1023, 2000 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: NRI Performance Measurement System: National Public Rates, 2002. Available at: http://www.rdmc.org/ nripms. Accessed June 25, 2005. Substance Abuse and Mental Health Services Administration (SAMHSA): The Five-State Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Rockville, MD, Substance Abuse and Mental Health Services Administration, 1998

394

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–70. Use of atypical antipsychotic drugs for severe and persistent mental illness (SPMI) 1.

Summary

Clinical rationale:

This measure assesses the proportion of adults treated with an antipsychotic drug for an SPMI who receive an atypical agent. The atypical antipsychotic medications clozapine, olanzapine, risperidone, quetiapine, and ziprasidone present the mental health care system with trade-offs between benefits and costs. Studies have shown clozapine to have superior efficacy and lower extrapyramidal symptoms compared with traditional antipsychotics, although clozapine’s risk of agranulocytosis requires routine blood monitoring. Most studies have found the other atypical agents to have a superior side effect profile than traditional antipsychotics. A recent randomized controlled study that compared individuals with stable, chronic schizophrenia treated with risperidone with those treated with the traditional antipsychotic haloperidol found that risperidone-treated patients were less likely to experience a relapse within a 1year period. The cost of atypical antipsychotics is several times greater than the traditional agents. Some public- and private-sector payers have placed restrictions on use of the atypical agents through utilization review and formulary restrictions, and consumer advocates have expressed concern regarding access to these agents.

2. Specifications Denominator:

All persons served by a state mental health authority ages 18 and older with a serious mental illness receiving antipsychotic medication during a specified point in time

Numerator:

The number of unduplicated persons from the denominator receiving atypical medication (clozapine, risperidone, quetiapine, olanzapine, ziprasidone) during a specified period

Data sources:

Administrative data, pharmacy data

3. Development Developer:

National Association of State Mental Health Program Directors (NASMHPD)

Stakeholders:

Public sector payers and purchasers, consumers clinicians, delivery system managers, researchers

Measure set:

NASMHPD Performance Measures for Mental Health Systems

Development:

Incomplete

Treatment Measures

❚ 395

TABLE 10–70. Use of atypical antipsychotic drugs for severe and persistent mental illness (SPMI) (continued) 4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Selected results:

53%, patients from four state hospitals and 26%, patients from a community setting (SAMHSA 1998) 67.7%–87.4%, patients from state psychiatric hospitals, 1999– 2001 (NASMHPD Research Institute 2005) 47%, 599 patients from 13 Veterans Affairs medical centers (Owen et al. 2001)

References and Instruments Csernansky J, Mahmoud R, Brenner R: A comparison of risperidone and haloperidol for the prevention of relapse in patients with schizophrenia. N Engl J Med 346:16–22, 2002 Leucht S, Pitschel-Walz G, Abraham D, et al: Efficacy and extrapyramidal sideeffects of the new antipsychotics olanzapine, quetiapine, risperidone, and sertindole compared to conventional antipsychotics and placebo: a meta-analysis of randomized controlled trials. Schizophr Res 35:51–68, 1999 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: NRI Performance Measurement System: National Public Rates, 2002. Available at: http://www.rdmc.org/nripms. Accessed June 25, 2005. Owen R, Feng W, Thrush C, et al: Variations in prescribing practices for novel antipsychotic medications among Veterans Affairs hospitals. Psychiatr Serv 52:1523–1530, 2001 Substance Abuse and Mental Health Services Administration (SAMHSA): The Five-State Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Rockville, MD, Substance Abuse and Mental Health Services Administration, 1998

396

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–71. Use of assertive community treatment (ACT) programs for individuals with severe and persistent mental illness (SPMI) 1.

Summary

Clinical rationale:

This measure assesses the proportion of persons served in the community with a serious mental illness who are receiving assertive community treatment. ACT programs provide intensive community-based care to individuals with SPMI, including case management services, outreach, and multidisciplinary coordination. Controlled trials comparing ACT with other treatment modalities have found that ACT significantly contributes to maintaining the continuity of mental health services, reduces inpatient admissions and emergency department visits, and increases the likelihood of independent living and patient satisfaction. Among individuals with dual diagnoses, ACT has been shown to improve some measures of substance abuse and quality of life but did not result in higher remission rates. Consumer advocates have expressed concern that ACT programs are underused.

2. Specifications Denominator:

Total unduplicated number of persons served in the community ages 18 and older with a serious mental illness during a specified point in time

Numerator:

Those persons from the denominator who receive ACT during a specified period

Data sources:

Administrative data, program enrollment data

3. Development Developer:

National Association of State Mental Health Program Directors (NASMHPD)

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

NASMHPD Performance Measures for Mental Health Systems

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level A. Good research-based evidence

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Internal quality improvement, health plan/provider choice by consumers, external quality improvement

Selected results:

Median 5%, individuals in three states (SAMHSA 1998)

Treatment Measures

❚ 397

TABLE 10–71. Use of assertive community treatment (ACT) programs for individuals with severe and persistent mental illness (SPMI) (continued) References and Instruments Allness D, Knoedler W: Recommended PACT Standards for New Teams. Washington, DC, National Alliance for the Mentally Ill, 1999 Marshall M, Lockwood A: Assertive community treatment for people with severe mental disorders. Cochrane Database Syst Rev (2):CD001089, 2000 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: NRI Performance Measurement System: National Public Rates, 2002. Available at: http://www.rdmc.org/ nripms. Accessed June 25, 2005. Substance Abuse and Mental Health Services Administration (SAMHSA): The FiveState Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Rockville, MD, Substance Abuse and Mental Health Services Administration, 1998 Teague GB, Bond GR, Drake RE: Program fidelity in assertive community treatment: development and use of a measure. Am J Orthopsychiatry 68:216–232, 1998

398

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–72. Antipsychotic drug dosing in nursing homes 1. Summary

This measure assesses the proportion of nursing home residents receiving antipsychotic drugs who receive an average daily dosage greater than 200 chlorpromazine equivalents.

Clinical rationale:

Although antipsychotic medications are efficacious for treating psychotic symptoms and often recommended for treating behavioral symptoms associated with dementia, their use in nursing homes has come under scrutiny. Use of these agents can lead to adverse effects, including extrapyramidal symptoms, tardive dyskinesia, and cognitive impairment. Research studies have reported substantial variation in use among nursing home residents, including misuse and overuse. In response, a federal nursing home regulation (Omnibus Budget Reconciliation Act of 1987) limited diagnostic indications for antipsychotic drug use in nursing homes, provided dosage guidelines, and established documentation standards.

2. Specifications Denominator:

All nursing home residents treated with antipsychotic drugs at the time of assessment, except those with hallucinations, psychotic disorders (DSM-IV codes 295.00–295.9, 297.00– 298.9), Tourette’s syndrome (DSM-IV code 307.23), or Huntington’s disease (DSM-IV code 333.4)

Numerator:

Residents from denominator with an average daily antipsychotic dosage in excess of 200 chlorpromazine equivalents during the previous 7 days

Data sources:

Administrative data, pharmacy data

3.

Development

Developer:

Llorente et al. 1998

Stakeholders:

Researchers

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

89.6% (Llorente et al. 1998)

Treatment Measures

❚ 399

TABLE 10–72. Antipsychotic drug dosing in nursing homes (continued) References and Instruments Beers M, Ouslander J, Rollingher I, et al: Explicit criteria for determining inappropriate medication use in nursing home residents. Arch Intern Med 151:1825–1832, 1991 Llorente OE, Leyva O, Silverman MA, et al: Use of antipsychotic drugs in nursing homes: current compliance with OBRA regulations. J Am Geriatr Soc 46:198–201, 1998 Morris JN, Hawes C, Fries BE, et al: Designing the national resident assessment instrument for nursing homes. Gerontologist 30:293–307, 1990 Sweet RA, Pollok BG: Neuroleptics in the elderly: guidelines for monitoring. Harv Rev Psychiatry 2:327–335, 1995

400

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–73. Antipsychotic use for nonpsychotic conditions 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of individuals receiving prescriptions for antipsychotic medications who do not have a psychotic disorder. Antipsychotic medications are effective in the treatment of psychotic symptoms associated with schizophrenia, affective disorders, and other conditions. Over the past two decades there has been concern about use of these agents outside evidence-based indications. Antipsychotic drugs, particularly the traditional (non-atypical) agents, have significant rates of disabling neurological side effects, including tardive dyskinesia, extrapyramidal symptoms, and cognitive impairment. Observational studies have documented extensive antipsychotic use in populations such as aggressive children and adolescents, elderly with behavioral dyscontrol, learning-disabled individuals, and individuals with autism or other pervasive developmental disorders. Further research is needed on the efficacy and risks of antipsychotic drug use in these populations and on the risk:benefit ratio of the newer atypical agents. One study found that decreasing use of antipsychotic drugs among elderly nursing home residents was associated with better functioning. This measure is part of a set of measures proposed for testing and has not been adopted by the developing organization.

Specifications

Denominator:

All members enrolled in a plan during a specified period who receive prescriptions for antipsychotic medications

Numerator:

The number of individuals from the denominator who did not have a diagnosis of a DSM-IV Axis I psychotic disorder

Data sources:

Administrative data, pharmacy data

3.

Development

Developer:

American Managed Behavioral Healthcare Association

Stakeholders:

Accrediting organizations, consumers, researchers

Measure set:

PERMS 2.0: Leadership Testing Set

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Treatment Measures

❚ 401

TABLE 10–73. Antipsychotic use for nonpsychotic conditions (continued) References and Instruments Ahmed Z, Fraser W, Kerr MP, et al: Reducing antipsychotic medication in people with a learning disability. Br J Psychiatry 176:42–46, 2000 American Managed Behavioral Healthcare Association: PERMS 2.0: Performance Measures for Managed Behavioral Healthcare Programs. Washington, DC, American Managed Behavioral Healthcare Association, 1998 Avorn J, Soumerai SB, Everitt DE, et al: A randomized trial of a program to reduce the use of psychoactive drugs in nursing homes. N Engl J Med 327:168–173, 1992 Baldessarini RJ: Chemotherapy in Psychiatry, Revised Edition. Cambridge, MA, Harvard University Press, 1985 Hermann R, Yang D, Ettner S, et al: Antipsychotic drug use in office-based physician practice in the United States, 1989–1997. Psychiatr Serv 53:425–430, 2002

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IMPROVING MENTAL HEALTHCARE

TABLE 10–74. Antipsychotic use in nursing homes 1. Summary

This measure assesses the proportion of nursing home residents treated with antipsychotic medications in the absence of a psychotic disorder or related condition.

Clinical rationale:

Although antipsychotic medications are efficacious for treating psychotic symptoms and often recommended for treating behavioral symptoms associated with dementia, their use in nursing homes has come under scrutiny. Use of these agents can lead to adverse effects, including extrapyramidal symptoms, tardive dyskinesia, and cognitive impairment. Research studies have reported substantial variation in use among nursing home residents, including misuse and overuse. In response, a federal nursing home regulation (Omnibus Budget Reconciliation Act of 1987) limited diagnostic indications for antipsychotic drug use in nursing homes, provided dosage guidelines, and established documentation standards.

2. Specifications Denominator:

All nursing home residents assessed at a specified point in time, except those residents with one or more psychotic disorders (DSM-IV codes 295.00–295.9, 297.00–298.9), Tourette’s syndrome (DSM-IV code 307.23), Huntington’s disease (DSM-IV code 333.4), or hallucinations

Numerator:

Residents from the denominator who received an antipsychotic medication during the previous 7 days

Data sources:

Minimal Data Set 2.0 Resident Assessment Instrument

3.

Development

Developer:

Center for Health Systems Research and Analysis

Stakeholders:

Clinicians, researchers

Measure set:

University of Wisconsin–Nursing Home Quality Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement, research study

Selected results:

10.7%–11%, residents from 512 nursing facilities in two states (Karon et al. 1999) 15.3%–18.5%, residents from nursing facilities nationwide, 2000–2001 (Health Care Financing Administration 2002)

Standards:

Within 5.3%–14% (Rantz et al. 2000)

Treatment Measures

❚ 403

TABLE 10–74. Antipsychotic use in nursing homes (continued) Case-mix adjustment: Type:

Yes Stratified

References and Instruments Arling G, Karon SL, Sainfort F, et al: Risk adjustment of nursing home quality indicators. Gerontologist 37:757–766, 1997 Elon R, Pawlson LG: The impact of OBRA on medical practice within nursing facilities. J Am Geriatr Soc 40:958–963, 1992 Health Care Financing Administration: MDS Quality Indicator Report. Available at http://www.hcfa.gov/projects/mdsreports/qi/qi_start.asp. Accessed June 24, 2002 Karon S, Sainfort F, Zimmerman D: Stability of nursing home quality indicators over time. Med Care 37:570–579, 1999 Maixner SM, Mellow AM, Tandon R: The efficacy, safety, and tolerability of antipsychotics in the elderly. J Clin Psychiatry 60:29–41, 1999 Rantz MJ, Petroski GF, Madsen RW, et al: Setting thresholds for quality indicators derived from MDS data for nursing home quality improvement reports: an update. J Qual Improv 26:101–110, 2000 Zimmerman DR, Karon SL, Arling G, et al: Development and testing of nursing home quality indicators. Health Care Financ Rev 16:107–127, 1995

404

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IMPROVING MENTAL HEALTHCARE

TABLE 10–75. Average length of inpatient stay prior to readmission 1. Summary

This measure assesses the average length of psychiatric hospital stay among inpatients subsequently readmitted within 30 days.

Clinical rationale:

Hospital readmission rates are a widely used albeit controversial proxy for relapse or complications following an inpatient stay for a psychiatric disorder. Length of inpatient psychiatric hospitalization has decreased markedly in the United States over the past 15 years. Research studies have found that on average, shorter stays are associated with increased readmission rates. However, evidence supporting readmission rates as a quality indicator is mixed. High readmission rates have led some inpatient facilities to examine numerous factors associated with readmissions, including patient characteristics, length of stay, discharge planning, and linkages with outpatient care.

2.

Specifications

Denominator:

The number of individuals discharged from a psychiatric inpatient service within a specified period of time and readmitted within 30 days

Numerator:

Of those individuals in the denominator, the sum of the total number of days spent in the hospital during the first hospitalization

Data sources:

Administrative data

3. Development Developer:

Nevada Division of Mental Health and Developmental Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, legislative members

Measure set:

Nevada Reform Grant Outcome Measures

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Treatment Measures

❚ 405

TABLE 10–75. Average length of inpatient stay prior to readmission (continued) References and Instruments Appleby L, Luchins DJ, Desai PN, et al: Length of stay and recidivism in schizophrenia: a study of public psychiatric hospital inpatients. Am J Psychiatry 150:72–76, 1993 Lieberman PB, Witala SA, Elliot B, et al: Decreasing length of stay: are there effects on outcomes of psychiatric hospitalization? Am J Psychiatry 155:905–909, 1998 Lyons J, O’Mahoney M, Miller S, et al: Predicting readmission to the psychiatric hospital in a managed care environment: implications for quality indicators. Am J Psychiatry 154:337–340, 1997 Mechanic D, McAlpine DD, Olfson M: Changing patterns of psychiatric inpatient care in the United States, 1988–1994. Arch Gen Psychiatry 55:785–791, 1998 Nevada Department of Human Resources, Division of Mental Health and Developmental Services: Nevada’s Consumer Oriented Outcome Measures. Carson City, NV, Nevada Department of Human Resources, 2000

406

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IMPROVING MENTAL HEALTHCARE

TABLE 10–76. Community tenure 1. Summary

This measure assesses the average number of days in the community between index discharge and hospital readmission.

Clinical rationale:

Severe and persistent mental illness can be marked by periods of exacerbation requiring inpatient care. Community tenure for patients discharged from the hospital—that is, the number of days between discharge and readmission—has been proposed as a measure of the quality of inpatient care, discharge planning, and community-based services received after discharge. There has been little empirical study of community tenure as a quality indicator. Studies of the relationship between hospital readmission rates—a related measure—and other measures of quality have been mixed.

2. Specifications Denominator:

All patients admitted to a hospital and discharged with a primary diagnosis of a psychiatric or substance use disorder during the first 6 months of a specified year

Numerator:

For all patients included in the denominator, the sum of the number of days between each patient’s index discharge and rehospitalization within 180 days (For patients who were not rehospitalized during the follow-up period, the number of days would be zero.)

Data sources:

Administrative data

Alternate versions:

Tenure period: 1-year Diagnostic groups: depression (elderly)

3. Development Developer:

Leslie and Rosenheck 2000

Stakeholders:

Consumers, clinicians, delivery system managers, researchers

Measure set:

Veterans Health Administration Mental Health Program Performance Monitoring System

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

17.0 days, 1 year, depression, elderly (Wells et al. 1993)

Treatment Measures

❚ 407

TABLE 10–76. Community tenure (continued) Case-mix adjustment: Type: Cost data:

Yes Devised specifically: age, sex, race, Medicaid status, illness severity (1 year, depression, elderly) Estimates from reported expenses (1 year)

References and Instruments Ashton CM, Wray NP: A conceptual framework for the study of early readmission as an indicator of quality of care. Soc Sci Med 43:1533–1541, 1996 Leslie D, Rosenheck R: Comparing quality of mental health care for public-sector and privately insured populations. Psychiatr Serv 51:650–655, 2000 Lyons J, O’Mahoney M, Miller S, et al: Predicting readmission to the psychiatric hospital in a managed care environment: implications for quality indicators. Am J Psychiatry. 154:337–340, 1997 Solomon P, Davis J, Gordon B: Discharged state hospital patients’ characteristics and use of aftercare: effect on community tenure. Am J Psychiatry 141:1566–1570, 1984 Wells K, Rogers W, Davis L, et al: Quality of care for hospitalized depressed elderly patients before and after the implementation of Medicare prospective payment system. Am J Psychiatry 150:1799–1805, 1993

408

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IMPROVING MENTAL HEALTHCARE

TABLE 10–77. Consumer participation in treatment decisions 1. Summary

This measure assesses the proportion of consumers using mental health services who reported they actively participated in decisions concerning their treatment.

Clinical rationale:

Consumer advocacy and studies demonstrating poor adherence to clinician treatment recommendations among patients have given rise to an emphasis on collaborative decision making between clinicians and consumers. In a review of the literature, Coulter (1997) concluded, “there is considerable evidence that patients want more information and greater involvement, although knowledge about the circumstances in which shared decision-making should be encouraged, and the effects of doing so, is sparse” (p. 112). There is little evidence on the relationship between collaborative decision making, adherence to mental health treatment recommendations, and clinical outcomes.

2. Specifications Denominator:

Consumers who received a mental health service during a specified period of time and completed a Mental Health Statistics Improvement Program (MHSIP) consumer survey.

Numerator:

Consumers included in the denominator who responded either “strongly agree” or “agree” with the statements “I, not staff, decided my treatment goals” (MHSIP question 19) and “I felt comfortable asking questions about my treatment and medication” (MHSIP question 12)

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

MHSIP

Users:

American College of Mental Health Administration, Tennessee Department of Mental Health

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Treatment Measures

❚ 409

TABLE 10–77. Consumer participation in treatment decisions (continued) 5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

References and Instruments Campbell J: How consumers/survivors are evaluating the quality of psychiatric care. Eval Rev 21:357–363, 1997 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Coulter A: Partnership with patients: pros and cons of shared clinical decisionmaking. J Health Serv Res Policy 2:112–121, 1997 Peters RM: Matching physician practice style to patient informational issues and decision-making preferences: an approach to patient autonomy and medical paternalism issues in clinical practice. Arch Fam Med 3:760–763, 1994 Roth D, Crane-Ross D: Impact of services, met needs, and service empowerment on consumer outcomes. Ment Health Serv Res 4:43–56, 2002

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410

IMPROVING MENTAL HEALTHCARE

TABLE 10–78. Consumer perception of coercion in treatment choices 1.

Summary

Clinical rationale:

This measure assesses the proportion of consumers using mental health services who reported that they felt coerced into treatment options or services. Mental healthcare has long struggled to find an appropriate balance between patient autonomy and maintaining safety. Clinicians often attempt to influence patients with poor judgment to make clinical decisions that they believe will lead to improved outcome. In cases in which a patient’s mental impairment would otherwise lead to harm to him- or herself or others, clinicians may intervene by pursuing involuntary commitment or guardianship. On the other hand, consumer advocates in mental healthcare have long advocated that treatment should be free of coercion and paternalism. There is little research evidence documenting a relationship between coercion or paternalism and clinical outcomes.

2. Specifications Denominator:

Consumers who received a mental health service during a specified period of time and completed a Mental Health Statistics Improvement Program (MHSIP) consumer survey.

Numerator:

Consumers in the denominator responding “strongly agree” or “agree” with the statement “Staff behaved as if I cannot choose what is best for me” (MHSIP question 22) and who indicated they did not feel free to complain (MHSIP question 13)

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

MHSIP

Users:

American College of Mental Health Administration

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Treatment Measures

❚ 411

TABLE 10–78. Consumer perception of coercion in treatment choices (continued) 5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

References and Instruments Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Lidz CW: Coercion in psychiatric care: what have we learned from research? J Am Acad Psychiatr Law 26:631–637, 1998 Lidz CW, Mulvey EP, Hoge SK, et al: The validity of mental patients’ accounts of coercion-related behaviors in the hospital admission process. Law Hum Behav 21:361–376, 1997 Lutzen K: Subtle coercion in psychiatric practice. J Psychiatr Ment Health Nurs 5:101–107, 1998 Nicholson RA, Ekenstam C, Norwood S: Coercion and the outcome of psychiatric hospitalization. Int J Law Psychiatry 19:201–217, 1996

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412

IMPROVING MENTAL HEALTHCARE

TABLE 10–79. Informing consumers about healthcare-related rights 1. Summary

This measure assesses the proportion of consumers who report receiving information about their rights related to mental healthcare.

Clinical rationale:

Obligations of ethical practice and requirements of law require that consumers of mental healthcare be informed about their rights. These rights and their limitations vary across states and localities but cover areas including informed consent, autonomy and liberty, competency, privacy, and access to healthcare and care-related information. Research has shown that many patients value collaborative approaches to treatment. There is a lack of empirical research assessing the relationship between receiving information about rights and clinical outcomes.

2. Specifications Denominator:

Consumers who received a mental health service during a 12-month period of time and completed a Mental Health Statistics Improvement Program (MHSIP) consumer survey

Numerator:

The number of consumers from the denominator who indicated “strongly agree” or “agree” responses to the statement “I was given information about my rights” (MHSIP question 15)

Data sources:

Administrative data, patient survey/instrument

3.

Development

Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, managed care organizations, delivery system managers

Users:

Rhode Island Department of Mental Health, Retardation, and Hospitals

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Treatment Measures

❚ 413

TABLE 10–79. Informing consumers about healthcare-related rights (continued) References and Instruments Bjoerkman T, Hansson L, Svensson B, et al: What is important in psychiatric outpatient care? Quality of care from the patient’s perspective. Int J Qual Health Care 7:355–362, 1995 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Kapp MB: Treatment and refusal rights in mental health: therapeutic justice and clinical accommodation. Am J Orthopsychiatry 64:223–234, 1994 Rhode Island Department of Mental Health, Retardation, and Hospitals: The Rhode Island Health Outcome Evaluation System: A Recovery-Based Statewide Approach to Performance Measurement. Providence, RI, Rhode Island Department of Mental Health, Retardation, and Hospitals, 1999 Trudeau ME: Informed consent: the patient’s right to decide. J Psychosoc Nurs Ment Health Serv 31:9–12, 1993

414

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IMPROVING MENTAL HEALTHCARE

TABLE 10–80. Cultural appropriateness of mental health services 1.

Summary

Clinical rationale:

This measure assesses the proportion of consumer members of racial minority groups who report that members of their racial group are treated with dignity. Research indicates that racial and ethnic minorities underutilize mental health services and that this is mediated by cultural, financial, and access-related factors. Some research suggests that racial and ethnic minorities are more likely to return for treatment beyond the initial session and remain in treatment longer when they receive services matched with their ethnic background. Many believe that culturally appropriate treatment can lead to better clinical outcomes; however, research in this area is at an early stage.

2. Specifications Denominator:

The total number of consumers/clients from different cultural groups who completed the Delaware Consumer/Client Satisfaction Survey at a specified point in time

Numerator:

Those consumers/clients who responded “agree” to question 17e: “The staff treat people of my race with dignity.”

Data sources:

Administrative data, patient survey/instrument

3.

Development

Developer:

Delaware Health and Social Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers, provider organizations

Measure set:

Delaware Performance Indicators

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

External quality improvement

Selected results:

93%, 117 Delaware patients with severe and persistent mental illness (Delaware Health and Social Services, Division of Alcoholism, Drug Abuse and Mental Health 1998)

Cost data:

Estimates from reported expenses

Treatment Measures

❚ 415

TABLE 10–80. Cultural appropriateness of mental health services (continued) References and Instruments Delaware Health and Social Services, Division of Alcoholism, Drug Abuse and Mental Health: Performance Indicators for Managed Long Term Behavioral Health Care, Version 3.0. New Castle, DE, Delaware Health and Social Services, 1999 Gallo JJ, Mariano S, Ford D, et al: Filters on the pathway to mental health care, II: sociodemographic factors. Psychol Med 25:1149–1160, 1995 Takeuchi D, Sue S, Yeh M: Return rates and outcomes from ethnicity-specific mental health programs in Los Angeles. Am J Public Health 85:638–643, 1995 Wallen J: Providing culturally appropriate mental health services for minorities. J Ment Health Adm 19:288–295, 1992

416

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IMPROVING MENTAL HEALTHCARE

TABLE 10–81. Current treatment plan for psychiatric outpatients 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of outpatients treated at an outpatient mental health facility who have an active treatment plan in their medical record—that is, completed by the third visit and renewed within subsequent 90-day intervals. The treatment plan documents the goals of a patient’s mental healthcare, the therapies implemented, and symptoms and problems targeted. Completing a treatment plan can foster collaboration between the patient and treatment team and among co-treaters of multiple disciplines. Payers and accrediting organizations require that an active treatment plan be part of the medical record and be reviewed at regular intervals to ensure the information is current. There is little empirical evidence on the association between the development of a written treatment plan and patient outcomes.

Specifications

Denominator:

All adult patients included in the monthly case count of an outpatient mental health facility, excluding patients in an assertive community treatment program

Numerator:

Patients included in the denominator whose medical record includes an active treatment plan (i.e., written within the past 90 days)

Data sources:

Administrative data, medical record

3. Development Developer:

Baker 1998

Stakeholders:

Clinicians, delivery system managers, provider organizations

Measure set:

Physician Performance Indicator Spreadsheet

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments Baker JG: A performance indicator spreadsheet for physicians in community mental health centers. Psychiatr Serv 49:1293–1298, 1998 Nathenson P, Johnson C: The psychiatric treatment plan. Perspect Psychiatr Care 28:32–35, 1992

Treatment Measures

❚ 417

TABLE 10–81. Current treatment plan for psychiatric outpatients (continued) Soreff S, Gulkin T, Pike JG: The evolving clinical chart: how it reflects and influences psychiatric and medical practice and the quality of care. Psychiatr Clin North Am 13:127–133, 1990

418

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IMPROVING MENTAL HEALTHCARE

TABLE 10–82. Discharge to less restrictive placement 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of children and adolescents who are discharged from a residential program to a less restrictive environment. Treatment settings for children and adolescents vary in terms of their restrictiveness (e.g., intensity of care, conditions of entry and departure, limits placed on movement or choice, and other requirements). Principles of high quality and costeffective care include use of the least restrictive environment given a patient’s clinical status, functioning, and safety. Most systems of care have developed level of care criteria to guide admission and discharge decisions. Handwerk et al. (1998) studied patient placement in several child treatment programs and found a correlation between greater severity of patient behavioral problems and the restrictiveness of their treatment program. Discharge to a less restrictive level of care has been used as a proxy for patient outcome in assessing the effectiveness of inpatient and residential programs.

Specifications

Denominator:

Number of patients ages 18 and younger who resided in a residential program for 30 or more days and were discharged with a subsequent known placement

Numerator:

Of the patients from the denominator, those whose subsequent placement setting was “less restrictive” as defined by the Restrictiveness of Living Environments Scale (ROLES)

Data sources:

Administrative data, medical record, clinician survey/ instrument

3. Development Developer:

Bluegrass Regional Mental Health–Mental Retardation Board

Stakeholders:

Public sector payers and purchasers, clinicians, delivery system managers, researchers

Measure set:

Bluegrass Regional Children’s Review Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Treatment Measures

❚ 419

TABLE 10–82. Discharge to less restrictive placement (continued) 5.

Use

Current status:

In routine use

Used in:

External quality improvement

Selected results:

66%, statewide data (Bluegrass Regional Mental Health– Mental Retardation Board, The Children’s Review Program 2000)

References and Instruments Bluegrass Regional Mental Health–Mental Retardation Board, The Children’s Review Program: Performance Measurement System: Implementation Guide, Version 2.0. Lexington, KY, Bluegrass Regional Mental Health–Mental Retardation Board, 2000 Handwerk ML, Friman PC, Mott MA, et al: The relationship between program restrictiveness and youth behavior problems. Journal of Emotional and Behavioral Disorders 6:170–179, 1998 Hawkins RP, Almeida MC, Fabry B, et al: A scale to measure Restrictiveness of Living Environments (ROLES) for troubled children and youths. Hosp Community Psychiatry 43:54–58, 1992

420

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IMPROVING MENTAL HEALTHCARE

TABLE 10–83. Duration of daily minor tranquilizer use 1. Summary

This measure assesses the proportion of individuals newly prescribed a daily minor tranquilizer whose use of the medication was less than 2 months or, if longer, accompanied by documented justification for continued use.

Clinical rationale:

Minor tranquilizers, including benzodiazepines, are effective treatments for anxiety and sleep disorders as well as other psychiatric and medical conditions. However, long-term use can potentially lead to tolerance, dependence, and physiological withdrawal. Practice guidelines generally recommend use for time-limited periods, although there are clinical situations in which longer use is justifiable.

2. Specifications Denominator:

The number of patients ages 18 and older enrolled in a health plan who were newly prescribed a daily minor tranquilizer during a specified period

Numerator:

Those patients from the denominator whose use of the medication was either less than 2 months or, if longer, accompanied by documented justification for continued use in the medical record

Data sources:

Administrative data, medical record

3.

Development

Developer:

Wells et al. 1988

Stakeholders:

Clinicians, researchers

Measure set:

Psychotropic Drug Use in Primary Care

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

57%, 578 patients across 16 academic internal medicine group practices (Wells et al. 1988)

Standards:

70% (Wells et al. 1988)

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age, sex, race, education, insurance, mental health status, physical and role functioning

Treatment Measures

❚ 421

TABLE 10–83. Duration of daily minor tranquilizer use (continued) References and Instruments Ahston H: Guidelines for the rational use of benzodiazepines: when and what to use. Drugs 48:25–40, 1994 American Psychiatric Association: Task Force Report: Benzodiazepine Dependence, Toxicity, and Abuse. Washington, DC, American Psychiatric Association, 1990 Salzman C: The benzodiazepine controversy: therapeutic effects versus dependence, withdrawal, and toxicity. Harv Rev Psychiatry 4:279–282, 1997 Wells KB, Goldberg G, Brook R, et al: Management of patients on psychotropic drugs in primary care clinics. Med Care 26:645–656, 1988

422

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IMPROVING MENTAL HEALTHCARE

TABLE 10–84. Informed consent for children’s medication treatment 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of children who receive a prescription for a new medication from a child and adolescent psychiatrist and whose medical record contains documentation of informed consent. Obtaining informed consent for medical treatment is a basic component of ethical practice, inscribed into American law by the U.S. Supreme Court as “the right of bodily selfdetermination”. Informed consent for a new medication requires communication about the focus of treatment and the potential risks and benefits associated with the medication. Until children reach the age of legal empowerment, parents or guardians are designated to provide informed consent for them, with the child’s assent whenever appropriate. Documenting informed consent in the medical record is important to establish it occurred, to communicate with other clinicians, and for risk management purposes. There is no empirical evidence on the association between informed consent and patient outcomes.

Specifications

Denominator:

The total number of children who met with a child and adolescent psychiatrist for a specified duration during which they were prescribed a new medication

Numerator:

Those children from the denominator whose medical record includes documentation of informed consent

Data sources:

Administrative data, medical record

3.

Development

Developer:

American Academy of Child and Adolescent Psychiatry (AACAP)

Stakeholders:

Clinicians, researchers, provider organizations

Measure set:

AACAP Performance Indicators

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Treatment Measures

❚ 423

TABLE 10–84. Informed consent for children’s medication treatment (continued) References and Instruments American Academy of Child and Adolescent Psychiatry: Work Group on Community Systems of Care: Best Principles for Measuring Outcomes in Managed Care Medicaid Programs. Washington, DC, American Academy of Child and Adolescent Psychiatry, 1998 Foreman DM: The family rule: a framework for obtaining ethical consent for medical interventions from children. J Med Ethics 25:491–500, 1999 Informed consent, parental permission, and assent in pediatric practice: Committee on Bioethics, American Academy of Pediatrics. Pediatrics 95:314–317, 1995 Schachter D, Kleinman I, Williams JI: Informed consent for antipsychotic medication. Can Fam Pract 45:1502–1508, 1999 Soreff S, Gulkin T, Pike JG: The evolving clinical chart: how it reflects and influences psychiatric and medical practice and the quality of care. Psychiatr Clin North Am 13:127–133, 1990

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424

IMPROVING MENTAL HEALTHCARE

TABLE 10–85. Involuntary admissions for inpatient mental healthcare 1.

Summary

Clinical rationale:

This measure assesses the proportion of psychiatric hospitalization admissions during a specified year that are involuntary. Subject to restrictions specific to each state, patients can be hospitalized without their consent if they present an imminent danger to themselves or others. Decisions to admit patients involuntarily are usually made by an evaluating clinician but are typically time-limited and subject to judicial appeal. Involuntary hospitalization can serve an important protective function. Studies have shown that application of criteria for involuntary admission can vary widely, even under localities subject to uniform regulations. Advocates representing consumers of mental healthcare have expressed concern about the variable application of this process and its restriction of individual rights. There is little empirical study of the association between rates of involuntary admissions and patient outcomes. This measure is part of a set of measures proposed for testing and has not been adopted by the developing organization.

2. Specifications Denominator:

The total number of inpatient mental health hospital admissions in a specified year

Numerator:

Those hospital admissions in the denominator that are involuntary

Data sources:

Administrative data, medical record

3.

Development

Developer:

American Managed Behavioral Healthcare Association

Stakeholders:

Accrediting organizations, consumers, researchers

Measure set:

PERMS 2.0: Leadership Testing Set

Users:

Iowa Department of Mental Health, Oklahoma Department of Mental Health

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

External quality improvement

Selected results:

16% Massachusetts hospitals (Boston Globe 1999) 75%, state hospitals (Ganju and Lutterman 1999)

Treatment Measures

❚ 425

TABLE 10–85. Involuntary admissions for inpatient mental healthcare (continued) References and Instruments American Managed Behavioral Healthcare Association: PERMS 2.0: Performance Measures for Managed Behavioral Healthcare Programs. Washington, DC, American Managed Behavioral Healthcare Association, 1998 Boston Globe editorial staff: Difficult admissions. Boston Globe. Feb 17, 1999, p. A14 Ganju V, Lutterman T: The Five-State Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Behavioral Outcomes and Guidelines Sourcebook, 2000 Edition. New York, Faulkner and Gray, 1999 Globe Spotlight Team: Locked wards open door to booming business. Boston Globe, May 11, 1997 Nicholson RA, Ekenstam C, Norwood S: Coercion and the outcome of psychiatric hospitalization. Int J Law Psychiatry 19:201–217, 1996 Rubin WV, Snapp MB, Panzano PC, et al: Variation in civil commitment processes across jurisdictions: an approach for monitoring and managing change in mental health systems. J Ment Health Adm 23:375–388, 1996

426

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IMPROVING MENTAL HEALTHCARE

TABLE 10–86. Long-acting benzodiazepine use in nursing homes 1. Summary

This measure assesses the proportion of nursing home residents who received a long-acting benzodiazepine.

Clinical rationale:

Research studies suggest that benzodiazepines may be overused among elderly patients in nursing homes. These medications are effective for the treatment of anxiety disorders, agitation, and insomnia; however, they can also produce withdrawal symptoms, impair cognition, and increase the risk of falls and fractures. The Center for Medicare and Medicaid Services has issued guidelines encouraging appropriate use that include avoiding longacting agents, which have been associated with higher rates of adverse events in the elderly. Use of long-acting benzodiazepines is advised only when short-acting agents have failed or when treating acute withdrawal symptoms. This measure is no longer active and cannot be derived from the current version of Medicare’s Minimal Data Set (MDS). Alternative data sources include administrative and pharmacy data.

2. Specifications Denominator:

All nursing home residents assessed at a specified point in time

Numerator:

Residents who received long-acting benzodiazepine medications during the previous 7 days

Data sources:

MDS 2.0 Resident Assessment Instrument

3. Development Developer:

Center for Health Systems Research and Analysis

Stakeholders:

Clinicians, researchers

Measure set:

University of Wisconsin–Nursing Home Quality Indicators

Development:

Incomplete

4. Properties Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

Measure tested, implemented, and discontinued

Used in:

External quality improvement, research study

Selected results:

3%, MDS database 1992–1995 (Clark 1999)

Treatment Measures

❚ 427

TABLE 10–86. Long-acting benzodiazepine use in nursing homes (continued) References and Instruments Center for Health Systems Research and Analysis: Nursing home quality indicator development. University of Wisconsin. Available at: www.chsra.wisc.edu/chsra/ qi/development.htm. June 23, 2005 Clark TR: ASCP background paper on HCFA quality indicator on the use of nine or more medications (ASCP background paper). Alexandria, VA, American Society of Consultant Pharmacists, 1999. Available at http://www.ascp.com/ public/pr/hcfabackgrounder.shtml. Accessed February 24, 2003 Wang PS, Bohn RL, Glynn RJ, et al: Hazardous benzodiazepine regimens in the elderly: effects of half-life, dosage, and duration on risk of hip fracture. Am J Psychiatry 158:892–898, 2001 Zimmerman DR, Karon SL, Arling G, et al: Development and testing of nursing home quality indicators. Health Care Financ Rev 16:107–127, 1995 Zisselman MH, Rovner B, Shmuely Y: Benzodiazepine use in the elderly prior to psychiatric hospitalization. Psychosomatics 37:28–42, 1996

428

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–87. Minor tranquilizer monotherapy 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of individuals newly prescribed a minor tranquilizer medication who receive only one minor tranquilizer medication at a time. Minor tranquilizers, including benzodiazepines, are effective treatments for anxiety and sleep disorders as well as other psychiatric and medical conditions. Side effects are dose related and include sedation, drowsiness, and psychomotor impairment, and more severe adverse effects include dependence and withdrawal syndromes. Some published recommendations advise against simultaneous use of multiple agents. However, specific situations exist in which this might be indicated, for example, using a long-acting agent to prevent withdrawal while discontinuing a shortacting agent.

Specifications

Denominator:

The number of patients ages 18 and older enrolled in a health plan who were newly prescribed a minor tranquilizer during a specified time period

Numerator:

Those patients from the denominator who had only one minor tranquilizer prescribed at a time

Data sources:

Administrative data, pharmacy data

3. Development Developer:

Wells et al. 1988

Stakeholders:

Clinicians, researchers

Measure set:

Psychotropic Drug Use in Primary Care

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

86%, 578 patients across 16 academic internal medicine group practices (Wells et al. 1988)

Standards:

80% (Wells et al. 1988)

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age, sex, race, education, insurance, mental health status, physical and role functioning

Treatment Measures

❚ 429

TABLE 10–87. Minor tranquilizer monotherapy (continued) References and Instruments American Psychiatric Association: Task Force Report: Benzodiazepine Dependence, Toxicity, and Abuse. Washington, DC, American Psychiatric Association, 1990 Kaplan HL, Sadock BJ: Pocket Handbook of Psychiatric Drug Treatment. Baltimore, MD, Williams & Wilkins, 1993 Wells KB, Goldberg G, Brook R, et al: Management of patients on psychotropic drugs in primary care clinics. Med Care 26:645–656, 1988

❚

430

IMPROVING MENTAL HEALTHCARE

TABLE 10–88. Patient participation in treatment planning 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of consumers who report that they were involved in the treatment planning process. Receiving information about treatment options and the opportunity to participate in clinical decision making are fundamental patient rights. Research has shown that this right is highly valued by many recipients of mental health services. One study found that patients who were provided a choice among treatment options were more likely to remain in treatment and express satisfaction with services. There was no difference in clinical outcomes between this group and a group that did not receive a choice.

Specifications

Denominator:

Consumers who received a mental health service during a 12-month period of time and completed a Mental Health Statistics Improvement Program (MHSIP) consumer survey

Numerator:

The number of patients responding either “strongly agree” or “agree” to both of the following survey items: “I felt comfortable asking questions about my treatment and medication” (MHSIP question 12) and “I, not staff, decided my treatment goals” (MHSIP question 19)

Data sources:

Administrative data, patient survey/instrument

3.

Development

Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, managed care organizations, delivery system managers

Users:

Rhode Island Department of Mental Health, Retardation, and Hospitals

Development:

Incomplete

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Treatment Measures

❚ 431

TABLE 10–88. Patient participation in treatment planning (continued) References and Instruments Bjoerkman T, Hansson L, Svensson B, et al: What is important in psychiatric outpatient care? Quality of care from the patient’s perspective. Int J Qual Health Care 7:355–362, 1995 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Hansson L, Bjorkman T, Berglund I: What is important in psychiatric inpatient care? Quality of care from the patient’s perspective. Qual Assur Health Care 5:41–47, 1993 Rhode Island Department of Mental Health, Retardation, and Hospitals: The Rhode Island Health Outcome Evaluation System: A Recovery-Based Statewide Approach to Performance Measurement. Providence, RI, Rhode Island Department of Mental Health, Retardation, and Hospitals, 1999 Rokke PD, Tomhave JA, Jocic Z: The role of client choice and target selection in self-management therapy for depression in older adults. Psychol Aging 14:155–169, 1999

432

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–89. Congruence of clinical visit with treatment plan goals 1.

Summary

Clinical rationale:

This measure assesses the proportion of consumers whose clinical visit addressed the goals established in their treatment plans. The treatment plan documents the goals of a patient’s care, the therapies under way, and symptoms and problems being targeted. Development of a treatment plan should reflect input from the patient, primary clinician, and others involved in the individual’s treatment. There has been little research evaluating the extent to which ongoing treatment corresponds with the intended interventions and goals documented in the treatment plan or the association between such conformance and patient outcomes. This measure has been audited but is not formally measured by the developing organization.

2. Specifications Denominator:

The number of consumers who met with a clinician within a 6-month period for a primary diagnosis of a severe and persistent mental illness

Numerator:

The number of individuals from the denominator for whom the medical record documents that the visit addressed the goals described in the consumer’s treatment plan

Data sources:

Administrative data, medical record

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

98% (Performance Measures Workgroup 1999)

Treatment Measures

❚ 433

TABLE 10–89. Congruence of clinical visit with treatment plan goals (continued) References and Instruments Haywood TW, Kravitz HM, Grossman LS, et al: Predicting the “revolving door” phenomenon among patients with schizophrenic, schizoaffective, and affective disorders. Am J Psychiatry 152:856–861, 1995 Nathenson P, Johnson C: The psychiatric treatment plan. Perspect Psychiatr Care 28:32–35, 1992 Owen RR, Fischer EP, Booth BM, et al: Medication noncompliance and substance abuse among patients with schizophrenia. Psychiatr Serv 47:853–858, 1996 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999 Soreff S, Gulkin T, Pike JG: The evolving clinical chart: how it reflects and influences psychiatric and medical practice and the quality of care. Psychiatr Clin North Am 13:127–133, 1990

434

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–90. Polypharmacy in elderly patients 1.

Summary

Clinical rationale:

2.

This measure assesses the proportion of individuals ages 65 and older who are prescribed two or more psychotropic medications during a 12-month period. Recent data on polypharmacy (i.e., an individual patient receiving multiple medications) among the elderly are sparse, but with higher rates of physical morbidity in this age group and the proliferation of psychotropic medications and indications for use, the practice is common and in some cases can raise clinical concerns. Physiological and psychological changes associated with aging result in slower drug metabolism for many elderly patients. Lower dosages, judicious addition of medications, and agents with shorter half-lives are typically advised. This measure is part of a set of measures proposed for testing and has not been adopted by the developing organization.

Specifications

Denominator:

All plan members ages 65 and older who filled prescriptions for psychotropic agents during a specified 12-month period

Numerator:

Plan members from the denominator who were concurrently prescribed two or more psychotropic medications (i.e., anxiolytic, hypnotic, antipsychotic, and thymolytic medications)

Data sources:

Administrative data, pharmacy data

3.

Development

Developer:

American Managed Behavioral Healthcare Association

Stakeholders:

Accrediting organizations, consumers, researchers

Measure set:

PERMS 2.0: Leadership Testing Set

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

References and Instruments American Managed Behavioral Healthcare Association: PERMS 2.0: Performance Measures for Managed Behavioral Healthcare Programs. Washington, DC, American Managed Behavioral Healthcare Association, 1998 Jacqmin-Gadda H, Fourrier A, Commenges D, et al: Risk factors for fractures in the elderly. Epidemiology 9:417–423, 1998

Treatment Measures

❚ 435

TABLE 10–90. Polypharmacy in elderly patients (continued) Katona CL: Psychotropics and drug interactions in the elderly patient. Int J Geriatr Psychiatry 16(suppl):S86–S90, 2001 Spore D, Mor V, Hiris J, et al: Psychotropic drug use among older residents of board and care facilities. J Am Geriatr Soc 43:1403–1409, 1995 Spore DL, Mor V, Larrat P, et al: Inappropriate drug prescriptions for elderly residents of board and care facilities. Am J Public Health 87:404–409, 1997

436

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–91. Benzodiazepine use in nursing homes 1.

Summary

Clinical rationale:

This measure assesses the proportion of nursing home residents who received antianxiety/hypnotic medications. Sedative/hypnotic medications include benzodiazepines, barbiturates, and other agents such as buspirone and chloral hydrate. Benzodiazepine use has received the most attention in nursing homes in recent years; research studies suggest that these agents may be overused among elderly patients in this setting. These medications are effective for the treatment of anxiety disorders, agitation, and insomnia; however, they can also produce withdrawal symptoms, impair cognition, and increase the risk of falls and fractures. The Center for Medicare and Medicaid Services has issued guidelines aimed at reducing use of these agents by requiring environmental interventions, limiting frequency of use, and requiring trials of reduced dosages. Little is known about what would be an “appropriate” utilization rate of benzodiazepines among nursing home residents or how such a rate should be adjusted for population characteristics, but comparative data may be useful to identify high-use facilities and prompt further assessment.

2. Specifications Denominator:

All nursing home residents assessed at a specified point in time, except those residents with hallucinations, one or more psychotic disorders (DSM-IV codes 295.00–295.9, 297.00– 298.9), Tourette’s syndrome (DSM-IV code 307.23), or Huntington’s disease (DSM-IV code 333.4).

Numerator:

Residents in the denominator who received during the previous 7 days 1) any antianxiety/hypnotic medications or 2) two or more doses of any antianxiety/hypnotic medications

Data sources:

Minimal Data Set 2.0 Resident Assessment Instrument

3. Development Developer:

Center for Health Systems Research and Analysis

Stakeholders:

Clinicians, researchers

Measure set:

University of Wisconsin–Nursing Home Quality Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement, research study

Treatment Measures

❚ 437

TABLE 10–91. Benzodiazepine use in nursing homes (continued) Standards:

Any dose: lower (good) threshold, 5.4%; upper (problematic) threshold, 16.6% (Rantz et al. 2000) Two or more doses: lower (good) threshold, 0.9%; upper (problematic) threshold, 3.6% (Rantz et al. 2000)

References and Instruments American Psychiatric Association. Task Force Report: Benzodiazepine Dependence, Toxicity, and Abuse. Washington, DC, American Psychiatric Association, 1990 Gurvich T, Cunningham JA: Appropriate use of psychotropic drugs in nursing homes. Am Fam Physician 61:1437–1446, 2000 Rantz MJ, Petroski GF, Madsen RW, et al: Setting thresholds for quality indicators derived from MDS data for nursing home quality improvement reports: an update. J Qual Improv 26:101–110, 2000 Wang PS, Bohn RL, Glynn RJ, et al: Hazardous benzodiazepine regimens in the elderly: effects of half-life, dosage, and duration on risk of hip fracture. Am J Psychiatry 158:892–898, 2001 Zimmerman DR, Karon SL, Arling G, et al: Development and testing of nursing home quality indicators. Health Care Financ Rev 16:107–127, 1995 Zisselman MH, Rovner B, Shmuely Y: Benzodiazepine use in the elderly prior to psychiatric hospitalization. Psychosomatics 37:28–42, 1996

438

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–92. Scheduled follow-up for minor tranquilizer therapy 1. Summary

This measure assesses the proportion of individuals newly prescribed a minor tranquilizer medication who have a follow-up appointment scheduled at the time of the first visit and documented in the medical record.

Clinical rationale:

Minor tranquilizers, including benzodiazepines, are effective treatments for anxiety and sleep disorders as well as other psychiatric and medical conditions. Side effects of these agents include sedation, drowsiness, and psychomotor impairment, and more severe adverse effects include dependence and withdrawal syndromes. Follow-up care is an important component in monitoring the effects of these agents to address potential adverse effects, assess treatment response, and consider alternative treatments. Research in the general medical sector, not specific to minor tranquilizers, has found that patients who are provided scheduled follow-up appointments are considerably more likely to return than patients who were asked to return but not scheduled. However, scheduled visits have not been found to be associated with better outcomes.

2. Specifications Denominator:

The number of individuals ages 18 and older enrolled in a health plan who were newly prescribed a minor tranquilizer during a specified time period

Numerator:

Those patients from the denominator who had a scheduled follow-up appointment documented in the medical record at the time of the index visit

Data sources:

Administrative data, medical record, pharmacy data, patient contact/appointment data

3.

Development

Developer:

Wells et al. 1988

Stakeholders:

Clinicians, researchers

Measure set:

Psychotropic Drug Use in Primary Care

Development:

Incomplete

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

100%, 578 patients across 16 academic internal medicine group practices (Wells et al. 1988)

Treatment Measures

❚ 439

TABLE 10–92. Scheduled follow-up for minor tranquilizer therapy (continued) Standards:

70% (Wells et al. 1988)

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age, sex, race, education, insurance, mental health status, physical and role functioning

References and Instruments American Psychiatric Association: Task Force Report: Benzodiazepine Dependence, Toxicity, and Abuse. Washington, DC, American Psychiatric Association, 1990 Pinsker J, Phillips RS, Davis RB, et al: Use of follow-up services by patients referred from a walk-in unit: how can patient compliance be improved? Am J Med Qual 10:81–87, 1995 Wells KB, Goldberg G, Brook RH, et al: Quality of care for psychotropic drug use in internal medicine group practices. J West Med 145:710–714, 1986 Wells KB, Goldberg G, Brook R, et al: Management of patients on psychotropic drugs in primary care clinics. Med Care 26:645–656, 1988

❚

440

IMPROVING MENTAL HEALTHCARE

TABLE 10–93. Staff attention to recovery potential 1.

Summary

Clinical rationale:

This measure assesses the proportion of surveyed individuals with severe mental illness who reported that clinical staff believe they could grow, change, and recover. Individuals and groups representing consumers of mental health services have advocated that mental health systems treating individuals with severe mental illness embrace a model that emphasizes recovery. Components of a recovery model include emphasis on consumer functioning, social connectedness, and pursuit of a “satisfying, hopeful, and contributing life, even with limitations caused by the illness.” Some advocate that consumers should also be given greater control over decisions shaping their lives. Elements of the recovery model are beginning to be incorporated into some public mental healthcare systems. There has been little study to date on the relationship between treatment based on recovery principles and clinical outcomes.

2. Specifications Denominator:

Consumers with a severe mental illness who received a mental health service during a specified period and completed a Mental Health Statistics Improvement Program (MHSIP) consumer survey

Numerator:

Consumers from the denominator who responded “strongly agree” or “agree” to the statement “Staff here believe that I can grow, change, and recover” (MHSIP consumer survey question 11)

Data sources:

Administrative data, patient survey/instrument

3.

Development

Users:

Minnesota Department of Human Services

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, health plan/provider choice by consumers, external quality improvement

References and Instruments Anthony W: Recovery from mental illness: the guiding vision of the mental health service system in the 1990s. Psychosoc Rehabil J 16:11–23, 1993 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996

Treatment Measures

❚ 441

TABLE 10–93. Staff attention to recovery potential (continued) Frese FJ III, Stanley J, Kress K, et al: Integrating evidence-based practices and the recovery model. Psychiatr Serv 52:1462–1468, 2001

❚

442

IMPROVING MENTAL HEALTHCARE

TABLE 10–94. Staff sensitivity to cultural/ethnic background 1. Summary

This measure assesses the proportion of consumers using mental health services who reported that staff lacked sensitivity to their cultural/ethnic background.

Clinical rationale:

Research studies have identified barriers to mental healthcare related to differences between clinicians and patients in culture, ethnicity, language, and age. Poor “cultural competency” among staff can contribute to consumer dissatisfaction, poor communication, and poor collaboration on treatment and has been associated with early termination of treatment. There is little empirical evidence addressing the association between clinician cultural competency and clinical outcomes.

2. Specifications Denominator:

Consumers who received a mental health service during a specified period of time and who completed a Mental Health Statistics Improvement Program (MHSIP) consumer survey

Numerator:

Consumers in the denominator who responded “strongly agree” or “agree” to the statement “Staff were not sensitive to my cultural/ethnic background” for question 20 on the MHSIP consumer survey

Data sources:

Administrative data, patient survey/instrument

3.

Development

Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

MHSIP

Users:

Commission on Accreditation of Rehabilitation Facilities, Tennessee Department of Mental Health

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

Treatment Measures

❚ 443

TABLE 10–94. Staff sensitivity to cultural/ethnic background (continued) References and Instruments Campbell J: How consumers/survivors are evaluating the quality of psychiatric care. Eval Rev 21:357–363, 1997 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Dana RH: Problems with managed mental health care for multicultural populations. Psychol Rep 83:293–294, 1998 Silove D, Manicavasagar V, Beltran R, et al: Satisfaction of Vietnamese patients and their families with refugee and mainstream mental health services. Psychiatr Serv 48:1064–1069, 1997 Woodward AM, Dwinell AD, Arons BS: Barriers to mental health care for Hispanic Americans: a literature review and discussion. J Ment Health Adm 19:224–236, 1992

444

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–95. Treatment plans for minor tranquilizer use 1. Summary

This measure assesses the number of adults in primary care who receive an initial prescription for a minor tranquilizer and have an adequate treatment plan documented in their medical record.

Clinical rationale:

Minor tranquilizers such as benzodiazepines have been found to be effective and relatively safe for anxiety and sleep disorders as well as other psychiatric and medical problems. In general, practice guidelines recommend short-term use. Because of potential risks associated with these agents (e.g., tolerance, dependence, discontinuation symptoms, and abuse), guidelines also recommend that physicians develop and document an adequate treatment plan in the medical record to guide the course of treatment and facilitate the coordination of care among providers. There is no empirical research assessing the association between these practices and clinical outcomes.

2. Specifications Denominator:

The total number of patients ages 18 and older enrolled in a health plan who are treated by a primary care physician and newly prescribed a minor tranquilizer medication during a specified time period

Numerator:

The number of patients from the denominator for whom an adequate treatment plan was documented in the medical record (adequate treatment plan is defined that counseling is offered or that both a goal for drug therapy are stated and criteria for discontinuing the drug are documented)

Data sources:

Administrative data, medical record

3.

Development

Developer:

Wells et al. 1988

Stakeholders:

Clinicians, researchers

Measure set:

Psychotropic Drug Use in Primary Care

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

56%, 578 patients across 16 academic internal medicine group practices (Wells et al. 1988)

Standards:

90% (Wells et al. 1988)

Treatment Measures

❚ 445

TABLE 10–95. Treatment plans for minor tranquilizer use (continued) Case-mix adjustment: Type:

Yes Analysis by subgroup: age, sex, race, education, insurance, mental health status, physical and role functioning

References and Instruments Jaski ME, Schwartzburg JG, Guttman RA, et al: Medication review and documentation in physician office practice. Eff Clin Pract 3:31–34, 2000 Soreff S, Gulkin T, Pike JG: The evolving clinical chart: how it reflects and influences psychiatric and medical practice and the quality of care. Psychiatr Clin North Am 13:127–133, 1990 Wells KB, Goldberg G, Brook RH, et al: Quality of care for psychotropic drug use in internal medicine group practices. J West Med 145:710–714, 1986 Wells KB, Goldberg G, Brook R, et al: Management of patients on psychotropic drugs in primary care clinics. Med Care 26:645–656, 1988

446

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–96. Hospital readmission rate 1.

Summary

Clinical rationale:

This measure assesses the proportion of inpatients treated in a substance abuse or mental health facility who are readmitted for treatment within 7 days of discharge. Hospital readmission rates are widely used as a proxy for relapse or complications after an inpatient stay for psychiatric and substance use disorders. Anecdotal reports support the use of readmission rates in quality improvement activities and have led to improved discharge planning and linkages between inpatient and outpatient care. Studies of the association between readmissions rates and other indicators of quality have been mixed. Lyons et al. (1997) found no association between psychiatric readmission rates (30- and 180-day) and clinical measures of outcome in a cohort of inpatients with diverse psychiatric disorders. In a study of veterans with service-related posttraumatic stress disorder (PTSD), Rosenheck et al. (1999) found small but significant correlations between 180-day readmission rates and other measures of quality but had nonsignificant findings for 14- and 30-day rates.

2. Specifications Denominator:

The number of inpatients discharged from an acute psychiatric or substance abuse facility within a 90-day period

Numerator:

The number of patients in the denominator who were readmitted to the same type of facility (substance abuse or psychiatric) within 7 days of discharge

Data sources:

Administrative data

Alternate versions:

Diagnostic groups: all mental disorders, all substance use disorders, PTSD, depression Readmission periods: 7, 14, 15, 30, 90, 180

3. Development Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Validity results:

Mixed or fair (PTSD)

Type:

Comparison with results or other methods or measures, gold standard validity testing

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

❚ 447

Treatment Measures

TABLE 10–96. Hospital readmission rate (continued) Selected results: Version

Conformance

User

7-day: mental disorder or substance use disorder

0%–18%, Massachusetts Medicaid beneficiaries

Network Health of Massachusetts 2000

14-day: mental disorder or substance use disorder

8.3%–9.6%, Veterans Affairs medical centers

Leslie and Rosenheck 2000

4.8%–8.8%, health plans

Leslie and Rosenheck 2000

8.1%–10.2%, psychiatric hospitals

NASMHPD Research Institute 2005

13.1%–15.3%, Veterans Affairs medical centers

Leslie and Rosenheck 2000

30-day: mental disorder

Case-mix adjustment: Type:

Yes Multivariate: age, sex, diagnoses, dual diagnoses, serviceconnected illness (mental disorder or substance use disorder) Analysis by subgroup: age, gender (mental disorder, substance use disorder)

References and Instruments Huff ED: Outpatient utilization patterns and quality outcomes after first acute episode of mental health hospitalization: is some better than none, and is more service associated with better outcomes? Eval Health Prof 23:441–456, 2000 Humphreys K, Weingardt KR: Assessing readmission to substance abuse treatment as an indicator of outcome and program performance. Psychiatr Serv 51:1568–1569, 2000 Leslie D, Rosenheck R: Comparing quality of mental health care for public-sector and privately insured populations. Psychiatr Serv 51:650–655, 2000 Lyons J, O’Mahoney M, Miller S, et al: Predicting readmission to the psychiatric hospital in a managed care environment: implications for quality indicators. Am J Psychiatry 154:337–340, 1997 Massachusetts Division of Medical Assistance: Quarterly Readmission Rate Reporting. Boston, MA, Massachusetts Division of Medical Assistance, 1999 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: NRI Performance Measurement System: National Public Rates, 2002. Available at: www.rdmc.org/nripms. Accessed June 25, 2005

448

❚

IMPROVING MENTAL HEALTHCARE

TABLE 10–96. Hospital readmission rate (continued) Network Health of Massachusetts: Network health behavioral health quarterly quality management results. Cambridge, MA, Network Health of Massachusetts, 2000 Rosenheck R, Fontana A, Stolar M: Assessing quality of care: administrative indicators and clinical outcomes in posttraumatic stress disorder. Med Care 37:180–188, 1999

Treatment Measures

❚ 449

TABLE 10–97. Family visits in child mental healthcare 1.

Summary

Clinical rationale:

This measure assesses the proportion of children under the age of 13 treated for a psychiatric disorder who have at least one psychotherapy session that includes a family member and/or guardian. Family members or guardians have an important role in the psychiatric treatment of children. Families are an important source of information about the presentation and course of psychiatric problems and are important collaborators in treatment interventions. Families can benefit from education and support. Family-based interventions have been shown to be effective for a variety of child and adolescent disorders; however, the impact of less intensive family involvement has not been studied.

2. Specifications Denominator:

All patients under age 13 receiving treatment for a diagnosed mental health condition during an 11-month period

Numerator:

Patients in the denominator who had at least one psychotherapy session that included a family member/ guardian during the specified period

Data sources:

Administrative data

3.

Development

Developer:

American Managed Behavioral Healthcare Association

Stakeholders:

Accrediting organizations, consumers, researchers

Measure set:

PERMS 2.0

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

External quality improvement

References and Instruments American Managed Behavioral Healthcare Association: PERMS 2.0: Performance Measures for Managed Behavioral Healthcare Programs. Washington, DC, American Managed Behavioral Healthcare Association, 1998 Diamond GS, Serrano AC, Dickey M, et al: Current status of family based outcome and process research. J Am Acad Child Adolesc Psychiatry 35:6–16, 1996 Murphy JM, Kelleher K, Pagano ME, et al: The family APGAR and psychosocial problems in children: a report from ASPN and PROS. J Fam Pract 46:54–64, 1998

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452

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TABLE 11–1.

IMPROVING MENTAL HEALTHCARE

Case management for dual diagnosis

1. Summary

This measure assesses the proportion of dually diagnosed individuals receiving case management who report that their mental health case manager assisted them in obtaining substance abuse treatment.

Clinical rationale:

Epidemiologic studies show a high rate of co-occurring substance use disorders among individuals with severe mental illness. Research studies have found poor treatment outcomes for psychiatric and substance use disorders if the comorbid condition is not also treated. Integrated care models and programs of assertive community treatment have been shown to improve outcomes. Research studies have not shown clear evidence of effectiveness of less intensive forms of case management.

2. Specifications Denominator:

The number of dually diagnosed individuals enrolled in a health plan and participating in mental health case management services who respond to a biannual consumer survey at a specified point in time

Numerator:

The number of participants from the denominator who report that their mental health case manager assisted them to obtain substance abuse treatment

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

95% (Performance Measures Workgroup 1999)

Coordination Measures

TABLE 11–1.

❚ 453

Case management for dual diagnosis (continued)

References and Instruments Drake RE, Mueser KT: Psychosocial approaches to dual diagnosis. Schizophr Bull 26:105–118, 2000 Gorey K, Leslie DR, Morris T, et al: The effectiveness of case management with severely and persistently mentally ill people. Community Ment Health J 34:241–250, 1998 Marshall M, Gray A, Lockwood A, et al: Case management for people with severe mental disorders. Cochrane Database Syst Rev (2):CD000050, 2000 Mueser KT, Bond GR, Drake RE, et al: Models of community care for severe mental illness: a review of research on case management. Schizophr Bull 24:37–74, 1998 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999

454

❚

TABLE 11–2.

IMPROVING MENTAL HEALTHCARE

Case management of medical comorbidity

1. Summary

This measure assesses the proportion of individuals receiving case management for severe mental illness who report that the case manager helped them to address their medical care needs.

Clinical rationale:

Research shows that consumers with severe mental illness experience high rates of medical comorbidity, and these problems are often undetected and untreated. Case management for mental illness provides an opportunity to improve access to and use of primary care services. There is little empirical research on the association between such interventions and patient outcomes.

2. Specifications Denominator:

The number of consumers with severe and persistent mental illness and/or serious emotional disorders in a health plan who participate in a case management program and respond to a biannual consumer survey

Numerator:

Of those in the denominator, the number of consumers who report that their mental health case manager helped them to address their medical care needs

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

95% (Performance Measures Workgroup 1999)

Coordination Measures

TABLE 11–2.

❚ 455

Case management of medical comorbidity (continued)

References and Instruments Gorey K, Leslie DR, Morris T, et al: The effectiveness of case management with severely and persistently mentally ill people. Community Ment Health J 34:241– 250, 1998 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999 Worley NK, Drago L, Hadley T: Improving the physical-mental health interface for the chronically mentally ill: could nurse case managers make a difference? Arch Psychiatr Nurs 4:108–113, 1990

456

❚

TABLE 11–3.

IMPROVING MENTAL HEALTHCARE

Case manager involvement in discharge planning

1. Summary

This measure assesses the proportion of inpatients enrolled in a case management program and discharged with a severe mental illness whose medical record reflects involvement of the case manager in discharge planning.

Clinical rationale:

Case managers may work with individuals with severe mental illness to assist in coordinating care across systems and levels of care. Reviews of studies of the effectiveness of case management for individuals with severe mental illness show varying results based on inclusion criteria, study design, intensity or model of case management; some evidence suggests improved compliance, reduced symptom severity, and lowered readmission rates. Participation in discharge planning is one potentially useful role for a case manager, but there is no research evidence specific to it. This measure has been audited but is not formally measured by the developing organization.

2. Specifications Denominator:

Consumers with severe and persistent mental illness and/or severe emotional disorders enrolled in a community-based case management program who are discharged from an inpatient or 24-hour residential facility within a 6-month period of time

Numerator:

Those consumers from the denominator whose medical record documents case manager involvement in the discharge planning process

Data sources:

Administrative data, medical record, program enrollment data

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

98% (Performance Measures Workgroup 1999)

Coordination Measures

TABLE 11–3.

❚ 457

Case manager involvement in discharge planning (continued)

References and Instruments Farrell SP, Blank MB, Koch JR, et al: Predicting whether patients receive continuity of care after discharge from state hospitals: policy implications. Arch Psychiatr Nurs 13:279–285, 1999 Gorey K, Leslie DR, Morris T, et al: Effectiveness of case management with severely and persistently mentally ill people. Community Ment Health J 34:241–250, 1998 Grant AB, Cohen NL, Sainz A: Impediments to the discharge planning effort for psychiatric inpatients. Soc Work Health Care 29:1–14, 1999 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999

458

❚

TABLE 11–4.

IMPROVING MENTAL HEALTHCARE

Consumer assessments of case management

1. Summary

This measure assesses the proportion of patients with severe mental illness who report that their case manager or managed behavioral healthcare organization (MBHO) assisted them in obtaining all necessary mental health and substance abuse services.

Clinical rationale:

Case management services may be provided to individuals with severe mental illness to assist in coordinating mental healthcare, medical care, and community-based services such as housing benefits and rehabilitative care. Three recent, comprehensive reviews have been conducted on the effectiveness of case management. One examined case management models collectively, including intensive programs such as assertive community treatment (ACT), and found strong evidence for effectiveness. The other two reviews looked separately at case management programs other than ACT and found a lack of conclusive evidence supporting effectiveness for these programs.

2. Specifications Denominator:

The total number of consumers with severe and persistent mental illness and/or serious emotional disorders in a health plan who participate in a case management program and respond to a biannual consumer survey

Numerator:

Of those in the denominator, the number of consumers who report that their case manager and/or their MBHO assisted them to obtain all necessary mental health and substance abuse services

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Coordination Measures

TABLE 11–4.

❚ 459

Consumer assessments of case management (continued)

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

95% (Performance Measures Workgroup 1999)

References and Instruments Gorey K, Leslie DR, Morris T, et al: The effectiveness of case management with severely and persistently mentally ill people. Community Ment Health J 34:241–250, 1998 Marshall M, Gray A, Lockwood A, et al: Case management for people with severe mental disorders. Cochrane Database Syst Rev (2):CD000050, 2000 Mueser KT, Bond GR, Drake RE, et al: Models of community care for severe mental illness: a review of research on case management. Schizophr Bull 24:37–74, 1998 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999

460

❚

TABLE 11–5.

IMPROVING MENTAL HEALTHCARE

Inpatient enrollment in case management

1. Summary

This measure assesses the proportion of individuals diagnosed with severe mental illness who were offered, accepted, and enrolled in mental health case management services prior to discharge from a 24-hour treatment facility.

Clinical rationale:

Case management services may be provided to individuals with severe mental illness to assist in coordinating mental healthcare, medical care, and community-based services such as housing, benefits, and rehabilitative care. Three recent, comprehensive reviews have been conducted on the effectiveness of case management. One examined case management models collectively, including intensive programs such as assertive community treatment (ACT), and found strong evidence favoring effectiveness. Two other reviews found a lack of evidence supporting effectiveness for less intensive models of care management.

2. Specifications Denominator:

The number of individuals diagnosed with severe and persistent mental illness or a serious emotional disorder who were discharged from an inpatient facility or 24-hour treatment facility during a specified duration (monthly, quarterly, biannually, annually)

Numerator:

Those individuals from the denominator who 1) were offered, 2) accepted, and 3) enrolled in mental health case management services prior to discharge

Data sources:

Administrative data, case management enrollment data, medical record

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Users:

Minnesota Department of Mental Health

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

100% “offered” (Performance Measures Workgroup 1999)

Coordination Measures

TABLE 11–5.

❚ 461

Inpatient enrollment in case management (continued)

References and Instruments Gorey K, Leslie DR, Morris T, et al: The effectiveness of case management with severely and persistently mentally ill people. Community Ment Health J 34:241–250, 1998 Marshall M, Gray A, Lockwood A, et al: Case management for people with severe mental disorders Cochrane Database Syst Rev (2):CD000050, 2000 Mueser KT, Bond GR, Drake RE, et al: Models of community care for severe mental illness: a review of research on case management. Schizophr Bull 24:37–74, 1998 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation 1999

462

❚

TABLE 11–6.

IMPROVING MENTAL HEALTHCARE

Case management use for disabling schizophrenia

1. Summary

This measure assesses the proportion of patients with schizophrenia and poor functioning who had contact with a case manager in the previous 3 months.

Clinical rationale:

Case management services may be provided to individuals with schizophrenia to assist in coordinating mental healthcare, medical care, and community-based services such as housing benefits and rehabilitative care. Three recent, comprehensive reviews have been conducted on the effectiveness of case management. One examined case management models collectively, including intensive programs such as assertive community treatment (ACT), and found strong evidence for effectiveness. Two other reviews found a lack of evidence supporting effectiveness for less intensive models of care management.

2. Specifications Denominator:

Consumers ages 18–65 who were in outpatient treatment for at least 3 months, had fewer than 21 inpatient days and at least one psychiatrist visit during this period, and were diagnosed with schizophrenia or schizoaffective disorder with a Global Assessment of Functioning scale score below 40

Numerator:

Consumers included in the denominator who have experienced at least one contact with a case manager during the 3 months prior to review

Data sources:

Administrative data, clinician-administered instrument, medical record

3. Development Developer:

Young et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

65%, 117 patients at two public mental health clinics (Young et al. 1998)

Coordination Measures

TABLE 11–6.

❚ 463

Case management use for disabling schizophrenia (continued)

References and Instruments Endicott J, Spitzer R, Fleiss I, et al: The global assessment scale: a procedure for measuring overall severity of psychiatric distance. Arch Gen Psychiatry 33:766–771, 1976 Gorey K, Leslie DR, Morris T, Carruthers WV, et al: The effectiveness of case management with severely and persistently mentally ill people. Community Ment Health J 34:241–250, 1998 Marshall M, Gray A, Lockwood A, et al: Case management for people with severe mental disorders. Cochrane Database Syst Rev (2):CD000050, 2000 Mueser KT, Bond GR, Drake RE, et al: Models of community care for severe mental illness: a review of research on case management. Schizophr Bull 24:37–74, 1998 Young A, Sullivan G, Burnam A, et al: Measuring the quality of outpatient treatment for schizophrenia. Arch Gen Psychiatry 55:611–617, 1998

464

❚

TABLE 11–7.

IMPROVING MENTAL HEALTHCARE

Communication between mental health and primary care

1. Summary

This measure assesses the proportion of psychiatric inpatients whose medical record documents contact between an inpatient clinician and the patient’s primary care clinician prior to discharge.

Clinical rationale:

Coordination between generalists and specialists is a problem in many areas of healthcare. This is a particularly important issue in mental healthcare, in which individuals with a number of psychiatric conditions have higher rates of medical illness and higher mortality rates than the general population. Despite this, medical illness often is undetected and undertreated in psychiatric settings, and there is poor coordination between mental health and primary care clinicians.

2. Specifications Denominator:

The number of individuals ages 19 and older discharged from an inpatient psychiatric unit who provided written consent to the treating facility to contact their primary care clinician

Numerator:

Those patients from the denominator whose chart contains evidence of telephonic or written notification by the inpatient facility to the patient’s primary care clinician prior to discharge

Data sources:

Administrative data, medical record

Alternate versions:

Population: Child/Adolescent (ages 18 and under) Setting: Outpatient

3. Development Developer:

Massachusetts Behavioral Health Partnership

Stakeholders:

Public sector payers and purchasers, clinicians, managed care organizations

Measure set:

Massachusetts Behavioral Health Partnership Performance Measures

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan provider contracting, external quality improvement

❚ 465

Coordination Measures

TABLE 11–7.

Communication between mental health and primary care (continued)

Selected results: Version

Conformance

Standard

User

Adult

73%, Massachusetts hospitals

80%

Massachusetts Behavioral Health Partnership 1998

90%

Comprehensive Behavioral Care 2000

80%

Massachusetts Behavioral Health Partnership 1998

–

Child/Adolescent

88%, Massachusetts hospitals

Outpatient

28%, Massachusetts Medicaid

–

References and Instruments Comprehensive Behavioral Care: National Quality Council Workplan. Tampa, FL, Comprehensive Behavioral Care, 2000 Lima B, Brooks M: Coordination of services for outpatients under concurrent medical and psychiatric care. Gen Hosp Psychiatry 7:330–333, 1985 Maricle R, Hoffman W, Bloom J, et al: The prevalence and significance of medical illness among chronically mentally ill patients. Community Ment Health J 23:81–90, 1987 Massachusetts Department of Medical Assistance: Massachusetts Behavioral Health Partnership Performance Measures, Fiscal Year 1999. Boston, MA, Massachusetts Department of Medical Assistance, 1999 Rabinowitz J, Mark M, Popper M, et al: Physical illness among all discharged psychiatric inpatients in a national case register. J Ment Health Adm 24:82–89, 1997

❚

466

TABLE 11–8.

IMPROVING MENTAL HEALTHCARE

Detailed communication between mental health and primary care for inpatients

1. Summary

This measure assesses the proportion of hospitalized psychiatric patients for whom there is substantive exchange of information between the patient’s inpatient psychiatric treaters and an outpatient primary care clinician.

Clinical rationale:

Coordination between generalists and specialists is a problem in many areas of healthcare. This is a particularly important issue in mental healthcare, in which individuals with a number of psychiatric conditions have higher rates of medical illness and higher mortality rates than the general population. Despite this, medical illness often is undetected and undertreated in psychiatric settings, and there is poor coordination between mental health and primary care treatment givers.

2.

Specifications

Denominator:

The number of members enrolled in a health plan who were discharged from an inpatient setting with a primary psychiatric diagnosis during a quarterly period

Numerator:

The number of cases from the denominator for whom the patient’s primary care clinician received written information including the day and date of admission and discharge, the location where the service was provided, the discharge diagnosis, and the discharge date within 30 calendar days after discharge

Data sources:

Administrative data, medical record

3. Development Developer:

M-CARE

Stakeholders:

Clinicians, consumers, delivery system managers

Measure set:

M-CARE Central Diagnostic and Referral Agency Quality Improvement Performance Measures

Users:

ValueOptions

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement; external quality improvement

Selected results:

15%–100%, three regional agencies, 1997–1998 (M-CARE 2000)

Standards:

90% (M-CARE 2000)

Coordination Measures

TABLE 11–8.

❚ 467

Detailed communication between mental health and primary care for inpatients (continued)

References and Instruments Halman LJ, Sheldon SJ: Continuity of care for mental health/chemical dependency treatment (poster session 37). Presented at the American Association of Health Plans-Agency for Healthcare Research and Quality-Centers for Disease Control and Prevention Building Bridges Conference, Atlanta, GA, April 2000 Lima B, Brooks M: Coordination of services for outpatients under concurrent medical and psychiatric care. Gen Hosp Psychiatry 7:330–333, 1985 Maricle R, Hoffman W, Bloom J, et al: The prevalence and significance of medical illness among chronically mentally ill patients. Community Ment Health J 23:81–90, 1987 M-CARE: Central Diagnostic and Referral Agency Quality Improvement Performance Measurement Report. Ann Arbor, MI, M-CARE, 2000 Rabinowitz J, Mark M, Popper M, et al: Physical illness among all discharged psychiatric inpatients in a national case register. J Ment Health Adm 24:82–89, 1997

468

❚

TABLE 11–9.

IMPROVING MENTAL HEALTHCARE

Informing primary care clinicians of psychiatric medications

1. Summary

This measure assesses the proportion of outpatients prescribed a psychotropic medication by a mental health clinician for whom the prescribing clinician provides the patient’s primary care clinician with treatment information.

Clinical rationale:

Coordination between generalists and specialists is a problem in many areas of healthcare. This is a particularly important issue in mental healthcare, in which individuals with a number of psychiatric conditions have higher rates of medical illness and higher mortality rates than the general population. Despite this, medical illness often is undetected and undertreated in psychiatric settings, and there is poor coordination between mental health and primary care treatment givers.

2. Specifications Denominator:

All members enrolled in a health plan with a primary psychiatric diagnosis who are prescribed psychotropic medication(s) by a mental health or substance abuse clinician during a 3-month period

Numerator:

Individuals from the denominator for whom the patient’s primary care clinician received written documentation including the prescribing physician, type and dosage of medication, diagnosis, and anticipated duration

Data sources:

Administrative data, medical record, pharmacy data

3. Development Developer:

M-CARE

Stakeholders:

Clinicians, consumers, delivery system managers

Measure set:

M-CARE Central Diagnostic and Referral Agency Quality Improvement Performance Measures

Users:

ValueOptions

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

15%–100%, three regional agencies, 1997–1998 (M-CARE 2000)

Standards:

90% (M-CARE 2000)

Coordination Measures

TABLE 11–9.

❚ 469

Informing primary care clinicians of psychiatric medications (continued)

References and Instruments Halman LJ, Sheldon SJ: Continuity of care for mental health/chemical dependency treatment (poster session 37). Presented at the AAHP-AHRQ-CDC Building Bridges Conference, Atlanta, GA, April 2000 Lima B, Brooks M: Coordination of services for outpatients under concurrent medical and psychiatric care. Gen Hosp Psychiatry 7:330–333, 1985 Maricle R, Hoffman W, Bloom J, et al: The prevalence and significance of medical illness among chronically mentally ill patients. Community Ment Health J 23:81–90, 1987 M-CARE: Central Diagnostic and Referral Agency Quality Improvement Performance Measurement Report. Ann Arbor, MI, M-CARE, 2000 Rabinowitz J, Mark M, Popper M, et al: Physical illness among all discharged psychiatric inpatients in a national case register. J Ment Health Adm 24:82–89, 1997

470

❚

IMPROVING MENTAL HEALTHCARE

TABLE 11–10. Use of primary care by individuals with mental illness 1. Summary

This measure assesses the proportion of individuals receiving mental health services for a primary psychiatric disorder who had at least one contact with a primary care clinician in a 12-month period.

Clinical rationale:

Individuals with severe mental illness have high rates of comorbid medical illness and higher mortality rates than the general population. Despite this, medical illness is undetected and undertreated. A single annual contact with a primary care physician is intended as a measure of preliminary access to primary care services rather than a measure of the adequacy of primary care.

2. Specifications Denominator:

The number of individuals who received at least one mental health service for a primary psychiatric disorder during a 12-month period

Numerator:

Individuals from the denominator who had at least one nonemergency face-to-face contact with a primary care physician during the 12-month period

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

National Association of State Mental Health Program Directors (NASMHPD)

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

NASMHPD Performance Measures for Mental Health Systems

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments Dixon L, Postrado L, Delahanty J, et al: The association of medical comorbidity in schizophrenia with poor physical and mental health. J Nerv Ment Dis 187:496–502, 1999 Druss BG, Rosenheck RA: Mental disorders and access to medical care in the United States. Am J Psychiatry 155:1775–1777, 1998

Coordination Measures

❚ 471

TABLE 11–10. Use of primary care by individuals with mental illness (continued) Jeste DV, Gladsjo JA, Lindamer LA, et al: Medical comorbidity in schizophrenia. Schizophr Bull 22:413–430, 1996 National Association of State Mental Health Program Directors: Performance Measures for Mental Health Systems: A Standardized Framework. Alexandria, VA, National Association of State Mental Health Program Directors, 1998

472

❚

IMPROVING MENTAL HEALTHCARE

TABLE 11–11. Assignment of primary care physician to individuals with schizophrenia 1. Summary

This measure assesses the proportion of plan members receiving active psychiatric treatment for a primary diagnosis of schizophrenia who are assigned a primary care physician.

Clinical rationale:

Research has shown that individuals with severe and persistent mental illness have a higher prevalence of medical comorbidities and shorter life spans than comparable populations. Medical conditions are often underdetected and undertreated in the course of psychiatric care. Practice guidelines recommend regular medical assessments for individuals with psychiatric disorders, and a number of state mental health authority initiatives have sought to improve patient access to and use of primary care services.

2. Specifications Denominator:

Enrollees who had either one inpatient admission or two outpatient visits with a primary diagnosis of schizophrenia within a 12-month period

Numerator:

The number of individuals in the denominator who were assigned a primary care physician

Data sources:

Administrative data, medical record

3. Development Developer:

Popkin et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

40%–49%, 377 Utah Medicaid beneficiaries (Popkin et al. 1998)

References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC, American Psychiatric Association, 1997 Jeste DV, Gladsjo JA, Lindamer LA, et al: Medical comorbidity in schizophrenia. Schizophr Bull 22:413–430, 1996 Lima B, Brooks M: Coordination of services for outpatients under concurrent medical and psychiatric care. Gen Hosp Psychiatry 7:330–333, 1985

Coordination Measures

❚ 473

TABLE 11–11. Assignment of primary care physician to individuals with schizophrenia (continued) Popkin MK, Callies AL, Lurie N, et al: An instrument to evaluate the process of psychiatric care in ambulatory settings. Psychiatr Serv 48:524–527, 1997 Popkin MK, Lurie N, Manning W, et al: Changes in the process of care for Medicaid patients with schizophrenia in Utah’s prepaid mental health plan. Psychiatr Serv 49:518–523, 1998

474

❚

IMPROVING MENTAL HEALTHCARE

TABLE 11–12. Criteria for discharge documented at admission 1. Summary

This measure assesses the proportion of patients with a primary psychiatric diagnosis discharged from an inpatient setting whose treatment plan on admission included criteria for discharge.

Clinical rationale:

The written treatment plan documents the goals of a patient’s mental healthcare, the therapies implemented, and symptoms and problems targeted. Payers and accrediting organizations require that an active treatment plan be part of the medical record and, for inpatient care, may require that discharge criteria be part of the initial plan. There is little empirical evidence on the association between early documentation of discharge criteria and length of stay or patient outcomes.

2. Specifications Denominator:

The total number of patients with a primary psychiatric diagnosis discharged from an inpatient setting during a specified time period

Numerator:

The number of patients from the denominator who had discharge criteria documented on the admission treatment plan

Data sources:

Administrative data, medical record

3. Development Developer:

Florida Council for Community Mental Health

Stakeholders:

Clinicians, delivery system managers

Measure set:

Florida Council for Community Mental Health

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Standards:

100% (Florida Council for Community Mental Health 2002)

References and Instruments Baker JG: A performance indicator spreadsheet for physicians in community mental health centers. Psychiatr Serv 49:1293–1298, 1998 Florida Council for Community Mental Health: FCCMH Performance Measurement System. Available online at http://www.fccmh.org/ measurehome.html. Accessed October 15, 2002

Coordination Measures

❚ 475

TABLE 11–12. Criteria for discharge documented at admission (continued) Nathenson P, Johnson C: The psychiatric treatment plan. Perspect Psychiatr Care 28:32–35, 1992 Soreff S, Gulkin T, Pike JG: The evolving clinical chart: how it reflects and influences psychiatric and medical practice and the quality of care. Psychiatr Clin North Am 13:127–133, 1990

476

❚

IMPROVING MENTAL HEALTHCARE

TABLE 11–13. Provider contact after missed appointment 1. Summary

This measure assesses the average length of time between a missed visit and follow-up contact by the provider.

Clinical rationale:

Individuals with severe mental illness have significant rates of missing scheduled mental health visits, and such discontinuities in care have been associated with medication noncompliance and hospital readmission. Evidence is mixed, but most studies found that contact (e.g., letters, telephone calls, and home visits) from a clinician after a missed appointment increased the likelihood that clients would attend subsequent appointments and decreased the need for emergency service use, although the impact on longer-term outcomes has not been well evaluated. This measure has been audited but is not formally measured by the developing organization.

2. Specifications Denominator:

The number of consumers continuously enrolled in a health plan during a specified time period who missed an appointment and were subsequently contacted personally by a provider

Numerator:

For consumers in the denominator, the sum of the durations between the missed appointment and personal contact (e.g., face-to-face session, telephone contact, or letter) from a provider

Data sources:

Patient contact/appointment data

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Coordination Measures

❚ 477

TABLE 11–13. Provider contact after missed appointment (continued) References and Instruments Blank MB, Chang MY, Fox JC, et al: Case manager follow-up to failed appointments and subsequent service utilization. Community Ment Health J 32:23–31, 1996 Hochstadt NJ, Trybula J Jr: Reducing missed initial appointments in a community mental health center. J Community Psychol 8:261–265, 1980 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999 Smoller J, McLean R, Otto M, et al: How do clinicians respond to patients who miss appointments? J Clin Psychiatry 59:330–338, 1998 Sparr LF, Moffitt MC, Ward MF: Missed psychiatric appointments: who returns and who stays away. Am J Psychiatry 150:801–805, 1993 Swenson TR, Pekarik G: Interventions for reducing missed initial appointments at a community mental health center. Community Ment Health J 24:205–218, 1988 Turner AJ, Vernon JC: Prompts to increase attendance in a community mentalhealth center. J Appl Behav Anal 9:141–145, 1976

478

❚

IMPROVING MENTAL HEALTHCARE

TABLE 11–14. Referral to post-detoxification services 1. Summary

This measure assesses the proportion of patients discharged from a substance-related detoxification who have documentation of a referral or transfer to a less intensive level of treatment.

Clinical rationale:

Detoxification treatment is an effective medical intervention used to manage an individual safely through the process of acute withdrawal, but it is not designed to address longstanding psychological, social, and behavioral problems associated with alcohol and drug disorders. Ideally, detoxification is followed by rehabilitative services that may include counseling, peer support, and other services. Research suggests that transitioning patients into rehabilitative treatment is an important component of detoxification treatment and may be associated with improved outcomes.

2. Specifications Denominator:

All patients discharged from a state-funded substance abuse treatment program

Numerator:

Patients from the denominator whose records contain documentation of completed detoxification and a referral or transfer to a less intensive level of treatment

Data sources:

Administrative data, medical record, proprietary client data system

Alternate versions:

Population: Child/Adolescent (< age 18)

3. Development Developer:

Texas Commission on Alcohol and Drug Abuse

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, researchers

Measure set:

Texas Commission on Alcohol and Drug Abuse Quality Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Coordination Measures

❚ 479

TABLE 11–14. Referral to post-detoxification services (continued) References and Instruments Hubbard RL, Craddock SG, Lynn PM, et al: Overview of 1-year follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychol Addict Behav 11:261–278, 1997 Irvin JE, Bowers CA, Dunn ME, et al: Efficacy of relapse prevention: a metaanalytic review. J Consult Clin Psychol 67:563–570, 1999 Latimer WW, Newcomb M, Winters KC, et al: Adolescent substance abuse treatment outcome: the role of substance abuse problem severity, psychosocial, and treatment factors. J Consult Clin Psychol 68:684–696, 2000 Moos RH, Finney JW, Ouimette PC, et al: A comparative evaluation of substance abuse treatment, I: treatment orientation, amount of care, and 1-year outcomes. Alcohol Clin Exp Res 23:529–536, 1999 Texas Commission on Alcohol and Drug Abuse: Definition source: 40 TEX.ADMIN.CODE Section 144.552. Data Source: TCADA Behavioral Health Integrated System. Austin, TX, 1999 Texas Commission on Alcohol and Drug Abuse: Texas Administrative Code, Chapter 144, Contract Administrative Requirements Rules for Funded Providers. Austin, TX, 2005. Available at: http://www.tcada.state.tx.us/rules/ 144_FINAL_RULES.doc. Accessed July 8, 2005.

480

❚

IMPROVING MENTAL HEALTHCARE

TABLE 11–15. Care planning for dual diagnosis 1. Summary

This measure assesses the proportion of individuals with a mental disorder and co-occurring substance disorder who are participating in a case management program and have a documented plan of a care to address both conditions.

Clinical rationale:

Epidemiologic studies show a high rate of co-occurring substance use disorders among individuals with severe mental illness. Research studies have found poor treatment outcomes for psychiatric and substance use disorders if the comorbid condition is not also treated. Integrated care models and programs of assertive community treatment have been shown to improve outcomes, but the influence of care planning alone has not been studied. This measure is not in use by the developing organization.

2. Specifications Denominator:

The number of individuals participating in a case management program who are dually diagnosed with a mental disorder and a substance abuse disorder during a 6-month period

Numerator:

Those individuals from the denominator for whom a case manager has documented a plan of care that addresses the consumer’s need for treatment of both conditions

Data sources:

Administrative data, medical record

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

98% (Performance Measures Workgroup 1999)

Coordination Measures

❚ 481

TABLE 11–15. Care planning for dual diagnosis (continued) References and Instruments Drake RE, Mueser KT: Psychosocial approaches to dual diagnosis. Schizophr Bull 26:105–118, 2000 Gorey K, Leslie DR, Morris T, et al: The effectiveness of case management with severely and persistently mentally ill people. Community Ment Health J 34:241–250, 1998 Marshall M, Gray A, Lockwood A, et al: Case management for people with severe mental disorders. Cochrane Database Syst Rev (2):CD000050, 2000 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999

482

❚

IMPROVING MENTAL HEALTHCARE

TABLE 11–16. Referral for substance abuse treatment among patients with positive assessment 1. Summary

This measure assesses the proportion of inpatients discharged with a primary diagnosis of schizophrenia and a positive assessment of recent substance abuse or dependence whose discharge treatment plan includes substance-related treatment.

Clinical rationale:

As many as half of inpatients with schizophrenia have a comorbid substance use disorder, but these problems often go unaddressed during hospital admissions for exacerbation of the psychiatric condition. Comorbid substance abuse is associated with poorer outcomes of schizophrenia, lower rates of treatment adherence, increased medical morbidity, and greater use of crisis services. A positive inpatient assessment for a substance use disorder should be followed by development of a treatment plan that includes substancerelated treatment, either in addition to or in combination with treatment for schizophrenia. Integrated outpatient treatment programs have been found to reduce alcohol intake and increase remission rates in this dually diagnosed population.

2. Specifications Denominator:

All patients admitted to a hospital during a specified time period with a primary diagnosis of schizophrenia whose inpatient admission or discharge assessment indicates the presence of a recent (<30 days) history of substance abuse or dependence

Numerator:

Patients from the denominator whose discharge plan includes a referral to substance abuse treatment or documentation that the patient refused substance abuse treatment

Data sources:

Administrative data, medical record

3. Development Developer:

Center for Quality Assessment and Improvement in Mental Health (CQAIMH)

Stakeholders:

Clinicians, researchers

Measure set:

CQAIMH Quality Measures

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Coordination Measures

❚ 483

TABLE 11–16. Referral for substance abuse treatment among patients with positive assessment (continued) Selected results:

38%, referred to inpatient treatment (Dickey et al. 2003) 19%, referred to outpatient treatment (Dickey et al. 2003)

References and Instruments Bartels SJ, Drake RE, Wallach MA: Long-term course of substance use disorders among patients with severe mental illness. Psychiatr Serv 46:248–251, 1995 Dickey B, Normand S, Hermann R, et al: Guideline recommendations for treatment of schizophrenia: the impact of managed care. Arch Gen Psychiatry 60:340–348, 2003 Drake R, Mercer-McFadden C, Mueser K, et al: Review of integrated mental health and substance abuse treatment for patients with dual disorders. Schizophr Bull 24:589–608, 1998 Kirchner J, Owen R, Nordquist C, et al: Diagnosis and management of substance use disorders among inpatients with schizophrenia. Psychiatr Serv 49:82–85, 1998

484

❚

IMPROVING MENTAL HEALTHCARE

TABLE 11–17. Timely inpatient contact with family 1. Summary

This measure assesses the proportion of inpatients whose family was contacted within 3 days of hospital admission.

Clinical rationale:

Contact between inpatient clinicians and family members of individuals hospitalized for a psychiatric disorder can be helpful both to patient care and to families. Family members can often inform patient assessment and treatment planning and can benefit from education, support, and information about the patient’s status. Family members who play a role in supporting the patient in the community should be part of treatment and discharge planning. Research studies specific to certain disorders suggest that working with families can contribute to clinical outcomes. There is no research on the relationship between clinician contact with family and outcome.

2. Specifications Denominator:

The total number of individuals admitted to an inpatient psychiatric facility during a specified time period, excluding individuals who decline to consent to clinician contact with family

Numerator:

Individuals from the denominator whose medical record documents that a family member or significant other was seen or contacted within 3 days of admission

Data sources:

Administrative data, medical record

3. Development Developer:

National Association of Social Workers

Stakeholders:

Accrediting organizations, clinicians, provider organizations

Measure set:

National Association of Social Workers Clinical Indicators for Social Work

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement

Standards:

95% (National Association of Social Workers 1990)

References and Instruments Dixon LB, Lehman AF: Family interventions for schizophrenia. Schizophr Bull 21:631–643, 1995 Hanson JG: Families’ perceptions of psychiatric hospitalization of relatives with a severe mental illness. Adm Policy Ment Health 22:531–541, 1995

Coordination Measures

❚ 485

TABLE 11–17. Timely inpatient contact with family (continued) National Association of Social Workers Commission on Health and Mental Health: NASW Clinical Indicators for Social Work and Psychosocial Services in the Acute Psychiatric Hospital. Washington, DC, National Association of Social Workers, 1990 Vourlekis BS: Quality assurance indicators for monitoring social work in psychiatric acute care hospitals. Hosp Community Psychiatry 42:460–461, 1991

486

❚

IMPROVING MENTAL HEALTHCARE

TABLE 11–18. Treatment plan for benefit termination 1. Summary

This measure assesses the proportion of plan members with continued need for mental health treatment after benefit limits are reached who have a documented plan for continued treatment.

Clinical rationale:

Healthcare benefits often limit the number of inpatient days or outpatient visits that will be covered, and in some cases patients exhaust their benefits before treatment goals are reached. Case managers at some managed behavioral healthcare organizations are required to document alternative plans for continued treatment. The effectiveness of this practice has not been evaluated.

2. Specifications Denominator:

The number of health plan members whose benefits have been exhausted during a specified time period

Numerator:

Individuals from the denominator for whom the case manager documented a plan for continued treatment if needed (plan could include continued treatment with existing provider at a reduced fee, a referral to a community agency or self-help group, or other mutually agreeable activities.)

Data sources:

Administrative data, medical record

3. Development Developer:

M-CARE

Stakeholders:

Clinicians, consumers, delivery system managers

Measure set:

M-CARE Central Diagnostic and Referral Agency Quality Improvement Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Internal quality improvement, external quality improvement

Standards:

100% (M-CARE 2000)

References and Instruments Johnson S, Prosser D, Bindman J, et al: Continuity of care for the severely mentally ill: concepts and measures. Soc Psychiatry Psychiatr Epidemiol 32:137–142, 1997 M-CARE: Central Diagnostic and Referral Agency Quality Improvement Performance Measurement Report. Ann Arbor, MI, M-CARE, 2000 Peel PB, Lave JR, Xu Y: Benefit limits in managed behavioral health care: do they matter? J Behav Health Serv Res 26:430–441, 1999

Coordination Measures

❚ 487

TABLE 11–18. Treatment plan for benefit termination (continued) Sturm R, Wells K: Health insurance may be improving—but not for individuals with mental illness. Health Serv Res 35:253–262, 2000

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C H A P T E R

1 2

Continuity Measures

489

490

❚

TABLE 12–1.

IMPROVING MENTAL HEALTHCARE

Follow-up after hospitalization for mental illness

1. Summary

This measure assesses the proportion of individuals with a psychiatric disorder who receive ambulatory follow-up care within 7 days of hospital discharge.

Clinical rationale:

Most patients treated in the inpatient setting for a psychiatric disorder require follow-up ambulatory care to promote further recovery and prevent relapse. Scheduling outpatient appointments proximally to discharge is generally recommended to address side effects that can result from inpatient medication changes and to support compliance with the treatment plan. The duration between hospital discharge and the first ambulatory follow-up visit varies widely, some of which is related to patient factors (e.g., severity of illness) and some to system factors (e.g., availability of outpatient appointments). Shorter gaps between discharge and aftercare may contribute to greater continuity of care and lower risk of relapse, although research findings are mixed among samples with diverse psychiatric conditions and absent for longer durations of follow-up (e.g., one visit over a 180-day period).

2. Specifications Denominator:

Individuals ages 6 and older hospitalized for treatment of selected mental health disorders

Numerator:

Those members from the denominator with an ambulatory mental health encounter or day/night treatment with a mental health practitioner within 7 days of discharge

Data sources:

Administrative data

Alternate versions:

Diagnostic groups: All mental disorders, all substance use disorders, posttraumatic stress disorder, major depression Follow-up periods: 30, 180 days

3.

Development

Developer:

National Committee for Quality Assurance (NCQA)

Stakeholders:

Accrediting organizations, public sector payers, purchasers, employer purchasers, consumers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Health Plan Employer Data and Information Set 2003

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Validity testing:

Mixed or fair

❚ 491

Continuity Measures

TABLE 12–1. Type:

Follow-up after hospitalization for mental illness (continued) Comparison with the results of other methods or measures, gold standard validity testing

5. Use Current status:

In routine use

Used in:

Plan purchasing, plan/provider choice by consumers, external quality improvement

Selected results: Version

Conformance

User

7-day: mental disorder

63%, Massachusetts Medicaid beneficiaries

Massachusetts DMA 1998

45%–48%, participating health plans

NCQA 2000–2001

67.4%, participating health plans

NCQA 2000

69%–99.1% Massachusetts Hospitals

Massachusetts Healthcare Purchaser Group 1997

Substance use disorder

40%, VA hospitals

Druss and Rosenheck 1997

Standards:

75%, 7-day

Massachusetts DMA 1998

30-day: mental disorder

References and Instruments Massachusetts Department of Medical Assistance (DMA): Massachusetts Behavioral Health Partnership Performance Standards, Fiscal Year 1999. Boston, MA, Massachusetts Department of Medical Assistance, 1999 Druss B, Rosenheck R: Evaluation of the HEDIS measure of behavioral health care quality. Psychiatr Serv 48:71–75, 1997 Foster EM: Do aftercare services reduce inpatient psychiatric readmissions? Health Serv Res 34:715–736, 1999 Huff ED: Outpatient utilization patterns and quality outcomes after first acute episode of mental health hospitalization: is some better than none, and is more service associated with better outcomes? Eval Health Prof 23:441–456, 2000 National Committee for Quality Assurance (NCQA): Health Plan Employer Data and Information Set 2003. Washington, DC, National Committee for Quality Assurance, 2002 Rosenheck R, Fontana A, Stolar M: Assessing quality of care: administrative indicators and clinical outcomes in posttraumatic stress disorder. Med Care 37:180–188, 1999 Schoenbaum SC, Cookson D, Stelovich S: Postdischarge follow-up of psychiatric inpatients in an HMO setting. Psychiatr Serv 46:943–945, 1995 Walker R, Minor-Schork D, Bloch R, et al: High risk factors for rehospitalization in six months. Psychiatr Q 67:235–243, 1996

492

❚

TABLE 12–2.

IMPROVING MENTAL HEALTHCARE

Ambulatory follow-up after emergency visit

1. Summary

This measure assesses the proportion of patients who attend an outpatient visit within 3 days after an emergency psychiatric visit.

Clinical rationale:

Studies have shown that compliance with scheduled outpatient appointments following emergency psychiatric care varies widely, between 30% and 80%. Although some of this variation is associated with patient characteristics, research suggests that a portion of the noncompliance may be responsive to clinical or organizational interventions. A shorter duration between the emergency encounter and the scheduled appointment has been associated with a higher show rate. In a randomized, controlled study, better show rates were obtained from a multifaceted intervention that included fixed appointment times, family involvement, contact with the aftercare clinician, and motivational counseling.

2. Specifications Denominator:

All patients who experienced an emergency psychiatric encounter in a specified year

Numerator:

Those patients in the denominator who attended at least one outpatient, non-emergency follow-up visit within 3 days of the encounter

Data sources:

Administrative data

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

Mental Health Statistics Improvement Program

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

Continuity Measures

TABLE 12–2.

❚ 493

Ambulatory follow-up after emergency visit (continued)

References and Instruments Axelrod S, Wetzler S: Factors associated with better compliance with psychiatric aftercare. Hosp Community Psychiatry 40:397–401, 1989 Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Dobscha SK, Delucci K, Young ML: Adherence with referrals for outpatient followup from a VA psychiatric emergency room. Community Ment Health J 35:451–458, 1999 Spooren D, Van Heeringen C, Jannes C: Strategies to increase compliance with outpatient aftercare among patients referred to a psychiatric emergency department: a multi-center controlled intervention study. Psychol Med 28:949–956, 1998.

494

❚

TABLE 12–3.

IMPROVING MENTAL HEALTHCARE

Attendance at first post-discharge appointment

1. Summary

This measure assesses the proportion of hospitalized patients with a primary psychiatric diagnosis who attend their first scheduled outpatient psychiatric appointment postdischarge.

Clinical rationale:

Most patients treated in the inpatient setting for a psychiatric disorder require follow-up ambulatory care to promote further recovery and prevent relapse. Subsequent outpatient visits can continue the treatment plan initiated on the inpatient unit, assess for medication response and side effects, provide support and education, and encourage compliance. Noncompliance with scheduled visits is a substantial problem for some patients with severe mental illness and has been associated with relapse and readmission. For psychiatric treatment facilities, missed appointments can result in inefficient use of staff time and resources. Studies have examined the impact of a number of interventions to improve the rate of kept appointments, with mixed results.

2. Specifications Denominator:

All patients discharged from an inpatient setting with a primary psychiatric or substance abuse disorder diagnosis who are scheduled for a follow-up outpatient appointment during a 1-month period

Numerator:

Patients from the denominator who attended their scheduled appointment

Data sources:

Administrative data, patient contact/appointment data

3. Development Users:

Comprehensive Behavioral Care

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Standards:

90% (Comprehensive Behavioral Care 2000)

Continuity Measures

TABLE 12–3.

❚ 495

Attendance at first post-discharge appointment (continued)

References and Instruments Allan AT: No-shows at a community mental health clinic: a pilot study. Int J Soc Psychiatry 43:40–46, 1988 Comprehensive Behavioral Care: National Quality Council Workplan. Tampa, FL, Comprehensive Behavioral Care, 2000 Deane FP: Improving attendance at intake in children’s outpatient services of a community mental health centre. Child Care Health Dev 17:115–121, 1991 Reda S, Makhoul S. Prompts to encourage appointment attendance for people with serious mental illness. Cochrane Database Syst Rev (2):CD002085, 2001 Smoller J, McLean R, Otto M, et al: How do clinicians respond to patients who miss appointments? J Clin Psychiatry 59:330–338, 1998 Swenson TR, Pekarik G: Interventions for reducing missed initial appointments at a community mental health center. Community Ment Health J 24:205–218, 1988

496

❚

TABLE 12–4.

IMPROVING MENTAL HEALTHCARE

Days to first aftercare visit

1. Summary

This measure assesses the average number of days between a patient’s discharge from inpatient psychiatric or substancerelated care and their first ambulatory visit.

Clinical rationale:

Most patients treated in the inpatient setting for a psychiatric disorder require follow-up ambulatory care to promote further recovery and prevent relapse. Scheduling outpatient appointments proximally to discharge is generally recommended to provide the patient with support during the transition, monitor for signs of relapse, address side effects resulting from changes in treatment, and encourage compliance with the treatment plan. Data indicate there is wide variability in the duration between hospital discharge and the first ambulatory follow-up visit, some of which is related to patient factors (e.g., severity of illness) and some to system factors (e.g., availability of outpatient appointments). Shorter gaps between discharge and aftercare may contribute to greater continuity of care and lower risk of relapse, although research evidence on this question is mixed.

2. Specifications Denominator:

All patients admitted to a hospital and discharged with a primary diagnosis of a psychiatric or substance use disorder during the first 6 months of a specified year

Numerator:

For all patients in the denominator, the sum of the total number of days between each patient’s index discharge and their first attended outpatient visit in the subsequent 180 days

Data sources:

Administrative data

3. Development Developer:

Leslie and Rosenheck 2000

Stakeholders:

Consumers, clinicians, delivery system managers, researchers

Measure set:

Veterans Health Administration Mental Health Program Performance Monitoring System

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Continuity Measures

TABLE 12–4.

❚ 497

Days to first aftercare visit (continued)

Selected results:

28.1–32.2, 172 Veterans Affairs medical centers (Leslie and Rosenheck 2000) 14.6–22.5, 200 private insurance plans nationwide (Leslie and Rosenheck 2000) 28.3–31.0, general psychiatric patients from 22 Veterans Integrated Service Networks 1998–1999 (Rosenheck and DiLella 2000) 27.2–27.3, substance abuse patients from 22 Veterans Integrated Service Networks 1998–1999 (Rosenheck and DiLella 2000)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, diagnosis, dual diagnosis, service connected illness

References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Substance Use Disorders: Alcohol, Cocaine, Opioids. Washington, DC, American Psychiatric Association, 1996 Leslie D, Rosenheck R: Comparing quality of mental health care for public-sector and privately insured populations. Psychiatr Serv 51:650–655, 2000 Rosenheck R, DiLella D: Department of Veterans Affairs National Mental Health Program Performance Monitoring System: Fiscal Year 1999 Report. West Haven, CT, Northeast Program Evaluation Center, 2000 Rosenheck R, Cichetti D: A Mental Health Program Performance Monitoring System for the Department of Veterans Affairs. West Haven, CT, Northeast Program Evaluation Center, 1995 Schoenbaum SC, Cookson D, Stelovich S: Postdischarge follow-up of psychiatric inpatients in an HMO setting. Psychiatr Serv 46:943–945, 1995 Walker R, Minor-Schork D, Bloch R, et al: High risk factors for rehospitalization in six months. Psychiatr Q 67:235–243, 1996

498

❚

TABLE 12–5.

IMPROVING MENTAL HEALTHCARE

Days to follow-up care within 6 months of discharge for posttraumatic stress disorder (PTSD)

1. Summary

This measure assesses the average number of days between discharge from inpatient care for individuals with PTSD and their first aftercare visit.

Clinical rationale:

Longitudinal studies suggest that psychiatric hospitalization among individuals with PTSD is common and follows a pattern consistent with a chronic disorder characterized by episodic exacerbations. Clinical research suggests that continued outpatient care following hospitalization can result in improved clinical outcomes. Data indicate there is wide variability in the duration between hospital discharge and the first ambulatory follow-up visit, some of which is related to patient factors (e.g., severity of illness) and some to system factors (e.g., availability of outpatient appointments). Shorter gaps between discharge and aftercare may contribute to greater continuity of care and lower risk of relapse, although research evidence on this question is mixed. A study of war-related PTSD found that follow-up within 30 and 180 days of discharge was not associated with several measures of clinical outcome. Severity of substance-related problems, a common comorbidity in this population, was lower among patients who received follow-up care.

2. Specifications Denominator:

The total number of patients discharged from inpatient or residential programs with a diagnosis of war-related PTSD who utilized outpatient services and had at least one outpatient visit within 180 days after discharge

Numerator:

For those patients in the denominator, the sum of the number of days per patient from discharge to the first outpatient visit within 180 days after discharge

Data sources:

Administrative data

3. Development Developer:

Rosenheck et al. 1999

Stakeholders:

Public sector payers and purchasers, clinicians, researchers

Measure set:

Administrative Indicators for PTSD (Rosenheck et al. 1999)

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Continuity Measures

TABLE 12–5.

❚ 499

Days to follow-up care within 6 months of discharge for posttraumatic stress disorder (PTSD) (continued)

Validity testing: Type:

Mixed or fair Comparison with the results of other methods or measures, gold standard validity testing

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Internal quality improvement, external quality improvement, research study

Selected results:

29.0–32.6, 62 Veterans Affairs hospitals (Rosenheck et al. 1999)

Case-mix adjustment:

Yes

Type: Cost data:

Analysis by subgroup: age, race, marital status, illness severity on admission Estimates from reported expenses

References and Instruments National Committee for Quality Assurance: Health Plan Employer Data and Information Set (HEDIS) 3.0, Vol 2. Washington, DC, National Committee for Quality Assurance, 1997 Ouimette PC, Moos RH, Finney JW: Two-year mental health service use and course of remission in patients with substance use and posttraumatic stress disorders. J Stud Alcohol 61:247–253, 2000 Rosenheck R, Fontana A: Changing patterns of care for war-related posttraumatic stress disorder at Department of Veterans Affairs medical centers: the use of performance data to guide program development. Mil Med 164:795–802, 1999 Rosenheck R, Fontana A, Stolar M: Assessing quality of care: administrative indicators and clinical outcomes in posttraumatic stress disorder. Med Care 37:180–188, 1999 Rubenstein LV, Lammers J, Yano EM, et al: Evaluation of the VA’s pilot program in institutional reorganization toward primary and ambulatory care, part I: changes in process and outcomes of care. Acad Med 71:772–783, 1996

500

❚

TABLE 12–6.

IMPROVING MENTAL HEALTHCARE

Follow-up appointment offered after hospitalization

1. Summary

This measure assesses the proportion of individuals hospitalized with a primary psychiatric diagnosis who were offered a follow-up psychiatric appointment within 7 days of discharge.

Clinical rationale:

Most patients treated in the inpatient setting for a psychiatric disorder require follow-up ambulatory care to promote further recovery and prevent relapse. Proximal outpatient visits can provide transitional assistance and support, address medication side effects, and encourage compliance. Data indicate there is wide variability in the duration between hospital discharge and the first ambulatory followup visit, some of which is related to patient factors (e.g., severity of illness) and some to system factors (e.g., availability of outpatient appointments). Shorter gaps between discharge and aftercare may contribute to greater continuity of care and lower risk of relapse, although research evidence on this question is mixed. Measures that examine “offered” visits rather than “attended” visits may better reflect quality of care, because they separate the clinician’s action from the patient’s compliance. Only attended visits, not offered visits, can be determined from claims data.

2. Specifications Denominator:

All members discharged from an inpatient setting with a primary psychiatric diagnosis during a 1-month period

Numerator:

Patients in the denominator who were offered an outpatient appointment within 7 days of discharge

Data sources:

Administrative data, patient contact/appointment data

3. Development Users:

Comprehensive Behavioral Care

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Standards:

90% (Comprehensive Behavioral Care 2000)

Continuity Measures

TABLE 12–6.

❚ 501

Follow-up appointment offered after hospitalization (continued)

References and Instruments Comprehensive Behavioral Care: National Quality Council Workplan. Tampa, FL, Comprehensive Behavioral Care, 2000 Druss B, Rosenheck R: Evaluation of the HEDIS measure of behavioral health care quality. Psychiatr Serv 48:71–75, 1997 Merrick EL: Treatment of major depression before and after implementation of a behavioral health carve-out plan. Psychiatr Serv 49:1563–1567, 1998 Schoenbaum SC, Cookson D, Stelovich S: Postdischarge follow-up of psychiatric inpatients in an HMO setting. Psychiatr Serv 46:943–945, 1995

502

❚

TABLE 12–7.

IMPROVING MENTAL HEALTHCARE

Follow-up care for co-occurring posttraumatic stress disorder (PTSD) and substance abuse

1. Summary

This measure assesses the proportion of patients discharged from inpatient or residential care with a diagnosis of PTSD and co-occurring substance abuse who had at least one psychiatric and one substance abuse clinic visit within 6 months of discharge.

Clinical rationale:

High rates of comorbid substance use disorders are seen among individuals with PTSD. These patients have higher rates of service utilization and worse outcomes compared to those with PTSD alone. Studies suggests that treatment of both conditions can result in improved outcomes and decreased service use. A study of patients hospitalized for war-related PTSD comorbid with a substance use disorder found that a follow-up visit for each condition within 6 months of discharge was not correlated with clinical outcomes.

2. Specifications Denominator:

The total number of patients discharged from inpatient or residential programs with a diagnosis of PTSD and cooccurring substance abuse over a specified interval

Numerator:

Patients from the denominator who had at least one psychiatric and one substance abuse clinic visit during the 6 months after inpatient discharge

Data sources:

Administrative data

3. Development Developer:

Rosenheck et al. 1999

Stakeholders:

Public sector payers and purchasers, clinicians, researchers

Measure set:

Administrative Indicators for PTSD (Rosenheck et al. 1999)

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Validity testing:

Mixed or fair

Type:

Comparison with the results of other methods or measures, gold standard validity testing

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Internal quality improvement, decisions by health plans about provider contracting, research study

Continuity Measures

❚ 503

TABLE 12–7.

Follow-up care for co-occurring posttraumatic stress disorder (PTSD) and substance abuse (continued)

Selected results:

13.3%–14.1%, patients at 62 Veterans Affairs hospitals (Rosenheck et al. 1999)

Case-mix adjustment:

Yes

Type: Cost data:

Analysis by subgroup: age, race, marital status, illness severity on admission Estimates from reported expenses

References and Instruments Leon SC, Lyons JS, Christopher NJ, et al: Psychiatric hospital outcomes of dual diagnosis patients under managed care. Am J Addict 7:81–86, 1998 Moos RH, Humphreys K, Ouimette PC, et al: Evaluating and improving VA substance abuse patients’ care. Am J Med Qual 14:45–54, 1999 Ouimette PC, Moos RH, Finney JW: Two-year mental health service use and course of remission in patients with substance use and posttraumatic stress disorders. J Stud Alcohol 61:247–253, 2000 Rosenheck R, Fontana A, Stolar M: Assessing quality of care: administrative indicators and clinical outcomes in posttraumatic stress disorder. Med Care 37:180–188, 1999

504

❚

TABLE 12–8.

IMPROVING MENTAL HEALTHCARE

Follow-up care within 6 months of discharge for posttraumatic stress disorder (PTSD)

1. Summary

This measure assesses the average number of outpatient visits attended by individuals with PTSD within 6 months of discharge from inpatient care.

Clinical rationale:

Longitudinal studies of PTSD suggest that chronicity is common and punctuated by episodic exacerbations. Inpatient care is sometimes indicated for acute episodes, and research suggests that continuing outpatient care following hospitalization is associated with better clinical outcomes. A study of war-related PTSD found that follow-up within 30 and 180 days of discharge was not associated with several measures of clinical outcome. Severity of substance-related problems, a common comorbidity in this population, was lower among patients who received follow-up care.

2. Specifications Denominator:

The total number of patients discharged from inpatient or residential programs with a diagnosis of war-related PTSD over a specified interval

Numerator:

Number of outpatient visits during the 6 months after inpatient discharge for patients from the denominator

Data sources:

Administrative data

3. Development Developer:

Rosenheck et al. 1999

Stakeholders:

Public sector payers and purchasers, clinicians, researchers

Measure set:

Administrative Indicators for PTSD (Rosenheck et al. 1999)

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Validity testing:

Mixed or fair

Type:

Comparison with the results of other methods or measures, gold standard validity testing

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Internal quality improvement, external quality improvement, research study

Selected results:

14.5–18.5, 62 Veterans Affairs hospitals (Rosenheck et al. 1999)

Continuity Measures

TABLE 12–8. Case-mix adjustment: Type: Cost data:

❚ 505

Follow-up care within 6 months of discharge for posttraumatic stress disorder (PTSD) (continued) Yes Analysis by subgroup: age, race, marital status, illness severity on admission Estimates from reported expenses

References and Instruments Huff ED: Outpatient utilization patterns and quality outcomes after first acute episode of mental health hospitalization: is some better than none, and is more service associated with better outcomes? Eval Health Prof 23:441–456, 2000 Ouimette PC, Moos RH, Finney JW: Two-year mental health service use and course of remission in patients with substance use and posttraumatic stress disorders. J Stud Alcohol 61:247–253, 2000 Rosenheck R, Fontana A: Changing patterns of care for war-related posttraumatic stress disorder at Department of Veterans Affairs medical centers: the use of performance data to guide program development. Mil Med 164:795–802, 1999 Rosenheck R, Fontana A, Stolar M: Assessing quality of care: administrative indicators and clinical outcomes in posttraumatic stress disorder. Med Care 37:180–188, 1999 Schoenbaum SC, Cookson D, Stelovich S: Postdischarge follow-up of psychiatric inpatients in an HMO setting. Psychiatr Serv 46:943–945, 1995

506

❚

TABLE 12–9.

IMPROVING MENTAL HEALTHCARE

Follow-up for medication management postdischarge

1. Summary

This measure assesses the proportion of individuals hospitalized for a psychiatric disorder who have a follow-up medication management visit within 60 days of discharge.

Clinical rationale:

Most patients treated in the inpatient setting for a psychiatric disorder require follow-up ambulatory care to promote further recovery and prevent relapse. Subsequent outpatient visits can continue the treatment plan initiated on the inpatient unit, assess for medication response and side effects, provide support and education, and encourage compliance. Data indicate there is wide variability in the duration between hospital discharge and the first ambulatory follow-up visit, some of which is related to patient factors (e.g., severity of illness) and some to system factors (e.g., availability of outpatient appointments). Shorter gaps between discharge and aftercare may contribute to greater continuity of care and lower risk of relapse, although research evidence on this question is mixed.

2. Specifications Denominator:

All members enrolled in a health plan who were discharged with a psychiatric diagnosis from an inpatient mental health facility and taking psychotropic medication during a quarterly time period

Numerator:

Those discharges from the denominator who had an ambulatory follow-up medication management visit within 60 calendar days from the date of discharge (follow-up visits documented using acceptable current procedural terminology codes for adults [90805, 90807, 90809, 90862] and children [90811, 90813, 90815, 90862])

Data sources:

Administrative data, pharmacy data

3. Development Developer:

M-CARE

Stakeholders:

Clinicians, consumers, delivery system managers

Measure set:

M-CARE Central Diagnostic and Referral Agency Quality Improvement Performance Measuress

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Continuity Measures

TABLE 12–9.

❚ 507

Follow-up for medication management postdischarge (continued)

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Standards:

90% (M-CARE 2000)

References and Instruments Druss B, Rosenheck R: Evaluation of the HEDIS measure of behavioral health care quality. Psychiatr Serv 48:71–75, 1997 Foster EM: Do aftercare services reduce inpatient psychiatric readmissions? Health Serv Res 34:715–736, 1999 M-CARE: Central Diagnostic and Referral Agency Quality Improvement Performance Measurement Report. Ann Arbor, MI, M-CARE, 2000 Nelson EA, Maruisch ME, Axler JL: Effects of discharge planning and compliance with outpatient appointments on readmission rates. Psychiatr Serv 51:885–889, 2000 Schoenbaum SC, Cookson D, Stelovich S: Postdischarge follow-up of psychiatric inpatients in an HMO setting. Psychiatr Serv 46:943–945, 1995 Stickney SK, Hall RC, Garnder ER: The effect of referral procedures on aftercare compliance. Hosp Community Psychiatry 31:567–569, 1980

508

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–10. Follow-up contact in antidepressant treatment 1. Summary

This measure assesses the proportion of individuals who were prescribed an antidepressant medication and had follow-up clinical contact within 6 weeks.

Clinical rationale:

Follow-up contact serves an important role in the treatment of depression. Many patients discontinue antidepressants during the first month of treatment, before they are likely to be effective. Clinicians can influence compliance with medication through education, encouragement, and addressing side effects. For those who complete the first 4–6 weeks of treatment, reevaluation is typically indicated for assessment of response and change in dosage or medication if warranted. Agency for Healthcare Research and Quality (AHRQ) practice guidelines for depression in primary care recommend visits every 1–2 weeks during the acute treatment phase. Recent research suggests that follow-up contact after treatment initiation for depression is associated with improved outcome when combined with other practice enhancements, but follow-up contact alone is not.

2. Specifications Denominator:

The total number of individuals ages 18 and older enrolled in a health plan who were prescribed an antidepressant medication for the first time during a specified time period

Numerator:

Those individuals from the denominator who had a followup visit or received a telephone call, documented in the medical record, within 6 weeks of the initial prescription

Data sources:

Administrative data, medical record, pharmacy data

3. Development Developer:

Wells et al. 1988

Stakeholders:

Clinicians, researchers

Measure set:

Psychotropic Drug Use in Primary Care

Users:

Katon et al. 2000

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

69%, 578 patients across 16 academic internal medicine group practices (Wells et al. 1988) 47.8%, 109 outpatients (Sleath et al. 2001)

Continuity Measures

❚ 509

TABLE 12–10. Follow-up contact in antidepressant treatment (continued) Standards:

80% (Wells, et al. 1988)

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age, sex, race, education, insurance, mental health status, physical and role functioning

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 2: Treatment of Major Depression. Clinical Practice Guideline Number 5. Rockville, MD, U.S. Department of Health and Human Services, 1993 Bull SA, Hu XH, Hunkeler EM, et al: Discontinuation of use and switching of antidepressants: influence of patient–physician communication. JAMA 288:1403–1409, 2002 Katon W, Ruter C, Lin E, et al: Are there detectable differences in quality of care or outcome of depression across primary care providers? Med Care 38:552–561, 2000 Simon GE, VonKorff M, Rutter C, et al: Randomised trial of monitoring, feedback, and management of care by telephone to improve treatment of depression in primary care. BMJ 320:550–554, 2000 Sleath B, Rubin RH, Huston S: Resident physician management of Hispanic and nonHispanic white patients on antidepressants. Int J Qual Health Care 13:231–238, 2001 Wells KB, Goldberg G, Brook R, et al: Management of patients on psychotropic drugs in primary care clinics. Med Care 26:645–656, 1988

510

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–11. 14-Day follow-up after initiating substancerelated treatment 1. Summary

This measure assesses the proportion of patients who receive treatment within 14 days after an initial diagnosis of substance abuse or dependence.

Clinical rationale:

Hospitalization for substance abuse generally occurs when a person is at risk of serious physical or psychiatric complications resulting from abuse, dependence, or withdrawal. Continuing treatment after hospital discharge is typically necessary to address ongoing problems and decrease the likelihood of relapse. The American Psychiatric Association’s Practice Guidelines for Treatment of Substance Abuse Disorders indicate that frequency of relapse monitoring should be intensified during transitions from higher to lower levels of care. Research evidence shows that the duration, frequency, and intensity of treatment are positively related to treatment outcomes, but studies have not specifically examined the utilization evaluated by this measure.

2. Specifications Denominator:

The number of patients enrolled in a health plan during a specified interval who receive a service-related diagnosis of an alcohol or drug disorder

Numerator:

The subset of patients in the denominator who receive any additional alcohol or drug treatment services within 14 days of the initial diagnosis

Data sources:

Administrative data

3. Development Developer:

Washington Circle Group

Stakeholders:

Accrediting organizations, public sector payers and purchasers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Washington Circle Group Core Performance Measures

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Continuity Measures

❚ 511

TABLE 12–11. 14-Day follow-up after initiating substancerelated treatment (continued) References and Instruments Alterman AI, Bedrick J, Howden D, et al: Reducing waiting time for substance abuse treatment does not reduce attrition. J Subst Abuse 6:325–332, 1994 Brown BS, Hickey JE, Chung AS, et al: The functioning of individuals on a drug abuse treatment waiting list. Am J Drug Alcohol Abuse 15:261–274, 1989 Huff ED: Outpatient utilization patterns and quality outcomes after first acute episode of mental health hospitalization: is some better than none, and is more service associated with better outcomes? Eval Health Prof 23:441–456, 2000 McCorry F, Garnick D, Bartlett J, et al: Improving Performance Measurement for Alcohol and Other Drug Services: Report of the Washington Circle Group. Rockville, MD, Washington Circle Group and the Center for Substance Abuse Treatment, 2000 Schoenbaum SC, Cookson D, Stelovich S: Postdischarge follow-up of psychiatric inpatients in an HMO setting. Psychiatr Serv 46:943–945, 1995

❚

512

IMPROVING MENTAL HEALTHCARE

TABLE 12–12. Medication visit attended 14 days after hospital discharge 1. Summary

This measure assesses the proportion of psychiatric inpatients discharged with a medication prescription who attended at least one outpatient medication visit within 14 business days of discharge.

Clinical rationale:

Most patients treated in the inpatient setting for a psychiatric disorder require follow-up ambulatory care to promote further recovery and prevent relapse. An outpatient medication management visit can continue to implement medication changes initiated on the inpatient unit, assess patient response and monitor for side effects to medications, and encourage medication compliance. A retrospective study found that scheduled appointments closer to the date of discharge were associated with higher rates of patient compliance and lower rates of rehospitalization. Overall, however, research evidence is mixed on the association between aftercare rates and rehospitalization.

2.

Specifications

Denominator:

All patients, age 19 and older, hospitalized with a primary psychiatric diagnosis and discharged during a specified time period

Numerator:

Those individuals in the denominator who attend at least one outpatient medication visit within 14 business days (20 calendar days) of discharge

Data sources:

Administrative data

Alternate versions:

Population: Child/adolescent (age 18 and under)

3. Development Users:

Massachusetts Behavioral Health Partnership

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan provider contracting, external quality improvement

❚ 513

Continuity Measures

TABLE 12–12. Medication visit attended 14 days after hospital discharge (continued) Selected results: Version

Conformance

Standard

User

Adult

80%, Massachusetts hospitals

90%

Massachusetts DMA 1998

Child/Adolescent

80%, Massachusetts hospitals

90%

Massachusetts DMA 1998

References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Substance Use Disorders: Alcohol, Cocaine, Opioids. Washington, DC, American Psychiatric Association, 1996 Foster EM: Do aftercare services reduce inpatient psychiatric readmissions? Health Serv Res 34:715–736, 1999 Massachusetts Department of Medical Assistance (DMA): Massachusetts Behavioral Health Partnership Performance Standards, Fiscal Year 1999. Boston, MA, Massachusetts Department of Medical Assistance, 1999 Nelson EA, Maruisch ME, Axler JL: Effects of discharge planning and compliance with outpatient appointments on readmission rates. Psychiatr Serv 51:885–889, 2000 Schoenbaum SC, Cookson D, Stelovich S: Postdischarge follow-up of psychiatric inpatients in an HMO setting. Psychiatr Serv 46:943–945, 1995

514

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–13. Multiple outpatient visits after substance-related hospitalization 1. Summary

This measure assesses the proportion of individuals discharged from a substance abuse inpatient unit during a 1-year period who had two or more outpatient mental health or substance abuse visits within 30 days of discharge.

Clinical rationale:

Hospitalization for substance abuse generally occurs when a person is at risk of serious physical or psychiatric complications resulting from abuse, dependence, or withdrawal. Continuing treatment after hospital discharge is typically necessary to address ongoing problems and decrease the likelihood of relapse. The American Psychiatric Association’s Practice Guidelines for Treatment of Substance Abuse Disorders indicates that frequency of relapse monitoring should be intensified during transitions from higher to lower levels of care. Research evidence shows that the duration, frequency, and intensity of treatment are positively related to treatment outcomes.

2. Specifications Denominator:

All inpatients treated in substance abuse units during the fiscal year who remained in the community for at least 30 days following their index discharge

Numerator:

Those patients from the denominator who had two or more outpatient mental health visits within 30 days of discharge

Data sources:

Administrative data

3. Development Developer:

Department of Veterans Affairs–Palo Alto Health Care System

Stakeholders:

Public sector payers and purchasers, delivery system managers, researchers

Measure set:

Veterans Affairs Substance Abuse Services Performance Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Selected results:

32%, FY1997 36%, FY1998 (Fong and Piette 1999)

Continuity Measures

❚ 515

TABLE 12–13. Multiple outpatient visits after substance-related hospitalization (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Substance Use Disorders: Alcohol, Cocaine, Opioids. Washington, DC, American Psychiatric Association, 1996 Fong WX, Piette JD. VA Care for Substance Abuse Patients: Indicators of Facility and VISN Performance (Fiscal Years 1997 and 1998). Palo Alto, CA, Veterans Affairs Palo Alto Healthcare System, 1999 Foster EM: Do aftercare services reduce inpatient psychiatric readmissions? Health Serv Res 34:715–736, 1999 Hubbard RL, Craddock SG, Lynn PM, et al: Overview of 1-year follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychol Addict Behav 11:261–278, 1997 Tims FM, Fletcher BW, Hubbard RL: Treatment outcomes for drug abuse clients. NIDA Res Monogr 106:93–113, 1991

516

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–14. Outpatient visit within 3 days of discharge (substance abuse) 1. Summary

This measure assesses the proportion of inpatients discharged with a diagnosis of substance abuse during a 1-year period who had one or more specialized substance abuse clinic visits within 3 days of discharge.

Clinical rationale:

Hospitalization for substance abuse generally occurs when a person is at risk of serious physical or psychiatric complications resulting from abuse, dependence, or withdrawal. Continuing treatment after hospital discharge is typically necessary to address ongoing problems and decrease the likelihood of relapse. The American Psychiatric Association’s Practice Guidelines for Treatment of Substance Abuse Disorders indicates that frequency of relapse monitoring should be intensified during transitions from higher to lower levels of care. Research evidence shows that the duration, frequency, and intensity of treatment are positively related to treatment outcomes, but studies have not specifically examined the utilization evaluated by this measure.

2. Specifications Denominator:

All inpatients discharged with a diagnosis of substance abuse during a 1-year period who remained in the community for at least 30 days after discharge

Numerator:

Those patients from the denominator who had one or more outpatient visits for a primary or secondary diagnosis of substance abuse within 3 days of their index discharge

Data sources:

Administrative data

3.

Development

Developer:

Department of Veterans Affairs–Palo Alto Health Care System

Stakeholders:

Public sector payers and purchasers, delivery system managers, researchers

Measure set:

Veterans Affairs Substance Abuse Services Performance Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Selected results:

10% (Fong and Piette 1999)

Continuity Measures

❚ 517

TABLE 12–14. Outpatient visit within 3 days of discharge (substance abuse) (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Substance Use Disorders: Alcohol, Cocaine, Opioids. Washington, DC, American Psychiatric Association, 1996 Fong WX, Piette JD: VA Care for Substance Abuse Patients: Indicators of Facility and VISN Performance (Fiscal Years 1997 and 1998) December 1999 Foster EM: Do aftercare services reduce inpatient psychiatric readmissions? Health Serv Res 34:715–736, 1999 Hubbard RL, Craddock SG, Lynn PM, et al: Overview of 1-year follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychol Addict Behav 11:261–278, 1997 Tims FM, Fletcher BW, Hubbard RL: Treatment outcomes for drug abuse clients. NIDA Res Monogr 106:93–113, 1991

518

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–15. Timeliness of ambulatory aftercare 1. Summary

This measure assesses the average duration between hospital discharge and first ambulatory visit for patients discharged from psychiatric hospitalization, residential program, or substance detoxification admission.

Clinical rationale:

In the treatment of severe and persistent mental illness, community-based aftercare is typically necessary to sustain and build upon progress made during inpatient treatment. Data indicate there is wide variability in the duration between hospital discharge and the first ambulatory followup visit, some of which is related to patient factors (e.g., severity of illness) and some to system factors (e.g., availability of outpatient appointments or services to support patient transitions between levels of care). Shorter gaps between discharge and aftercare may contribute to greater continuity of care and lower risk of relapse, although research evidence on this question is mixed.

2. Specifications Denominator:

For each discharging facility, the total number of discharges from inpatient psychiatric hospitals, detoxification centers, or residential care facilities during a specified time period

Numerator:

From those discharges in the denominator, the sum of the total number of days per patient between the recorded discharge date and the first ambulatory follow-up visit

Data sources:

Administrative data

3. Development Developer:

Delaware Health and Social Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers, providers organizations

Measure set:

Delaware Performance Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Continuity Measures

❚ 519

TABLE 12–15. Timeliness of ambulatory aftercare (continued) References and Instruments Delaware Health and Social Services, Division of Alcoholism, Drug Abuse and Mental Health: Performance Indicators for Managed Long Term Behavioral Health Care, Version 3.0. Newcastle, DE, Delaware Health and Social Services, 1999 Dorwart RA, Hoover CW: A national study of transitional hospital services in mental health. Am J Public Health 84:1229–1234, 1994 Johnson S, Prosser D, Bindman J, et al: Continuity of care for the severely mentally ill: concepts and measures. Soc Psychiatry Psychiatr Epidemiol 32:137–142, 1997 Sytema S, Micciolo R, Tansella M: Continuity of care for patients with schizophrenia and related disorders: a comparative south-Verona and Groningen case-register study. Psychol Med 27:1355–1362, 1997

520

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–16. Treatment engagement of children with attention-deficit/hyperactivity disorder (ADHD) 1. Summary

This measure assesses the proportion of individuals who have a psychiatric evaluation or treatment for a new exacerbation of ADHD and have a subsequent psychiatric service within 60 days.

Clinical rationale:

Children with ADHD can be effectively treated with medication and certain types of therapy. However, a substantial proportion of children terminate treatment early, and observational studies suggests that they have worse outcomes compared with children who complete a prescribed treatment course. Studies show that factors influencing continuation of treatment include patient and family attitudes toward therapy and medication, the frequency of medication dosing, and parents’ views of the feasibility of regular therapy sessions. Although clinicians’ influence on patient attendance is limited, strategies have been proposed to encourage attendance at scheduled appointments and engage individuals at risk for early dropout.

2. Specifications Denominator:

The number of continuously enrolled members in a health plan who had a new episode of ADHD (defined as a primary diagnosis of ADHD and no encounters for that diagnosis in the prior 90 days) during a specified period

Numerator:

Those members from the denominator who received a second psychiatric service (defined as an outpatient visit [MD, DO, ARNP, PA], or inpatient visit or detoxification, observation/hold bed, residential, partial hospitalization) within 60 days

Data sources:

Administrative data

3. Development Developer:

ValueOptions

Stakeholders:

Consumers, clinicians, managed care organizations, delivery system managers

Measure set:

ValueOptions Corporate Quality Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Continuity Measures

❚ 521

TABLE 12–16. Treatment engagement of children with attention-deficit/hyperactivity disorder (ADHD) (continued) 5. Use Current status:

In routine use

Used in:

External quality improvement

Standards:

85% (ValueOptions 2000)

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: Medicaid populations, commercial populations

References and Instruments American Academy of Pediatrics: Clinical practice guideline: diagnosis and evaluation of the child with attention-deficit/hyperactivity disorder. Pediatrics 105:1158–1170, 2000 Kazdin AE, Mazurick JL, Siegel TC: Treatment outcome among children with externalizing disorder who terminate prematurely versus those who complete psychotherapy. J Am Acad Child Adolesc Psychiatry 33:549–557, 1994 National Institutes of Health: National Institutes of Health Consensus Development Conference statement: diagnosis and treatment of attention-deficit hyperactivity disorder (ADHD). J Am Acad Child Adolesc Psychiatry 39:182–193, 2000 ValueOptions: Corporate Quality Management, Quality Indicator Methodology Manual. Norfolk, VA, ValueOptions, 2000

522

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–17. Treatment engagement of consumers by race/ ethnicity 1. Summary

This measure assesses the proportion of plan enrollees using mental health services, by race/ethnicity, who had only one mental health contact.

Clinical rationale:

This measure attempts to assess engagement in treatment of individuals from different racial/ethnic groups. Patients from minority racial/ethnic groups have been shown in some research studies to have lower utilization and less satisfaction with healthcare compared with nonminority populations. Reports describe how culture, ethnicity, language, and age may impose barriers to mental health services. Poor “cultural competence” of staff may contribute to consumer discomfort, poor communication, or poor collaboration regarding diagnosis and treatment, leading to dissatisfaction with care and early termination. One study has shown a relationship between patient–provider cultural compatibility and mental health service use. However, at present there is little empirical evidence that specifically addresses the association between cultural competence and clinical outcomes.

2. Specifications Denominator:

All plan enrollees receiving one or more mental health service(s) during a specified 12-month period

Numerator:

Total number of consumers in the denominator who had only one mental health contact during the 12-month period (results should be presented for all consumers and for the following subgroups: Hispanic, non-Hispanic, white, African American, Asian, other)

Data sources:

Administrative data, program enrollment data

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system mangers, researchers

Measure set:

Mental Health Statistics Improvement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Continuity Measures

❚ 523

TABLE 12–17. Treatment engagement of consumers by race/ ethnicity (continued) 5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

References and Instruments Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Dana RH: Problems with managed mental health care for multicultural populations. Psychol Rep 83:293–294, 1998 Flaskerud JH: Matching client and therapist ethnicity, language, and sex: a review of research. Issues Ment Health Nurs 11:321–336, 1990 Herrick CA, Brown NH: Underutilization of mental health services by AsianAmericans residing in the United States. Issues Ment Health Nurs 19:225–240, 1998 Padgett DK, Patrick C, Burns BJ, et al: Women and outpatient mental health services: use by black, Hispanic, and white women in a national insured population. J Ment Health Adm 21:347–360, 1994 Woodward AM, Dwinell AD, Arons BS: Barriers to mental health care for Hispanic Americans: a literature review and discussion. J Ment Health Adm 19:224–236, 1992

524

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–18. Treatment engagement of individuals with depression 1. Summary

This measure assesses the proportion of individuals who have a psychiatric evaluation or treatment for a new episode of depression and have a subsequent psychiatric service within 30 or 90 days.

Clinical rationale:

Although major depression can be effectively treated with antidepressant medication or psychotherapy, many patients discontinue treatment prematurely, resulting in failure to achieve remission or relapse. Studies have found that patients continuing medication for 4–9 months after remission are less likely to relapse than those who do not. Studies of psychotherapy have found remission to occur after an average of 8–12 visits. A well-designed crosssectional study found a strong association between patient continuation of antidepressants and clinician–patient communication about treatment goals and side effects.

2. Specifications Denominator:

The number of continuously enrolled members in a health plan who had a new episode of major depression (defined as a primary diagnosis of major depression and no encounters for that diagnosis in the prior 90 days) during a specified period

Numerator:

Those members from the denominator who received a second psychiatric service (defined as an outpatient visit [MD, DO, ARNP, PA] or inpatient visit or detoxification, observation/hold bed, residential, partial hospitalization) within 30 and 90 days

Data sources:

Administrative data

3. Development Developer:

ValueOptions

Stakeholders:

Consumers, clinicians, managed care organizations, delivery system managers

Measure set:

ValueOptions Corporate Quality Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Standards:

85% (ValueOptions 2000)

Continuity Measures

❚ 525

TABLE 12–18. Treatment engagement of individuals with depression (continued) Case-mix adjustment: Type:

Yes Analysis by subgroup: Medicaid populations, commercial populations

References and Instruments Agency for Health Care Policy and Research Depression Guideline Panel: Depression in Primary Care, Vol 1: Detection and Diagnosis. Washington, DC, U.S. Department of Health and Human Services, 1993 Bull SA, Hu XH, Hunkeler EM, et al: Discontinuation of use and switching of antidepressants: influence of patient-physician communication. JAMA 288:1403– 1409, 2002 Hirschfeld RM, Keller MB, Panico S, et al: The National Depressive and ManicDepressive Association consensus statement on the undertreatment of depression. JAMA 277:333–340, 1997 Simon GE, VonKorff M, Rutter C, et al: Randomised trial of monitoring, feedback, and management of care by telephone to improve treatment of depression in primary care. BMJ 320:550–554, 2000 ValueOptions: Corporate Quality Management, Quality Indicator Methodology Manual. Norfolk, VA, ValueOptions, 2000

526

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–19. Treatment engagement of individuals with schizophrenia 1. Summary

This measure assesses the proportion of individuals who have a psychiatric evaluation or treatment for a new exacerbation of schizophrenia and have a subsequent psychiatric service within 14 or 90 days.

Clinical rationale:

Research has shown that 30%–50% of individuals with severe mental illness fail to attend scheduled outpatient visits. Although antipsychotic medication and certain forms of therapy are effective for schizophrenia, early treatment termination can lead to acute relapse. One study found that attendance at a follow-up visit after initial evaluation was associated with patient factors (age, employment status, and previous exposure to mental health treatment), system factors (time between the evaluation and first appointment), and clinical factors (lower Global Assessment of Functioning ratings and psychosis). Although clinicians’ influence on patient attendance is limited, strategies have been proposed to encourage attendance at scheduled appointments and engage individuals at risk for early dropout.

2. Specifications Denominator:

The number of continuously enrolled members in a health plan with a new exacerbation of schizophrenia (defined as a primary diagnosis of schizophrenia and no encounters for that diagnosis in the prior 90 days) during a specified time period

Numerator:

Those members from the denominator who received a second psychiatric service (defined as an outpatient visit [MD, DO, ARNP, PA] or inpatient visit or detoxification, observation/hold bed, residential, partial hospitalization) within 14 and 90 days

Data sources:

Administrative data

3. Development Developer:

ValueOptions

Stakeholders:

Consumers, clinicians, managed care organizations, delivery system managers

Measure set:

ValueOptions Corporate Quality Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Continuity Measures

❚ 527

TABLE 12–19. Treatment engagement of individuals with schizophrenia (continued) 5. Use Current status:

In routine use

Used in:

External quality improvement

Standards:

85% (ValueOptions 2000)

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: Medicaid populations, commercial populations

References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Patients With Schizophrenia. Washington, DC: American Psychiatric Association, 1997 Greeno CG, Anderson CM, Shear MK, et al: Initial treatment engagement in a rural community mental health center. Psychiatr Serv 50:1634–1636, 1999 Reda S, Makhoul S. Prompts to encourage appointment attendance for people with serious mental illness. Cochrane Database Syst Rev (2):CD002085, 2001 Smoller J, McLean R, Otto M, et al: How do clinicians respond to patients who miss appointments? J Clin Psychiatry 59:330–338, 1998 ValueOptions: Corporate Quality Management, Quality Indicator Methodology Manual. Norfolk, VA, ValueOptions, 2000

528

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–20. Intensity of aftercare for schizophrenia 1. Summary

This measure assesses the proportion of individuals hospitalized for a primary diagnosis of schizophrenia who average at least one ambulatory visit monthly for 6 months after discharge.

Clinical rationale:

Schizophrenia typically follows a chronic course with periodic exacerbation. After an acute exacerbation requiring hospitalization, close ambulatory follow-up is needed to continue stabilizing activities, carry out changes to the treatment plan initiated during the hospitalization, assess patient response and monitor for medication side effects, provide support, and address social service, family, and other issues. One practice guideline for schizophrenia recommends at least monthly visits for stable outpatients with schizophrenia and more frequent contact for others, such as patients after hospitalization. Little empirical research assesses the association between frequency of aftercare and outcome for this population.

2. Specifications Denominator:

The number of patients discharged from inpatient care with a primary diagnosis of schizophrenia, during a specified time period, multiplied by six

Numerator:

Number of outpatient visits attended by patients in the denominator over a 6-month period

Data sources:

Administrative data

3. Development Developer:

Fischer and Owen 1999

Stakeholders:

Researchers

Measure set:

Quality Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

References and Instruments Center for Outcomes Research and Effectiveness, University of Arkansas for Medical Sciences: NetOutcomes Performance Indicators (0522–01). Little Rock, AR, Center for Outcomes Research and Effectiveness, University of Arkansas for Medical Sciences, 2000

Continuity Measures

❚ 529

TABLE 12–20. Intensity of aftercare for schizophrenia (continued) Expert Consensus Guideline Series: Treatment of schizophrenia. J Clin Psychiatry 57:1–59, 1996 Fischer E, Owen R: Quality of public sector care for schizophrenia in Arkansas. Ment Health Serv Res 1:213–221, 1999 Foster EM: Do aftercare services reduce inpatient psychiatric readmissions? Health Serv Res 34:715–736, 1999 Sytema S, Burgess P: Continuity of care and readmission in two service systems: a comparative Victorian and Groningen case-register study. Acta Psychiatr Scand 100:212–219, 1999

530

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–21. Intensity of aftercare within 180 days of discharge (psychiatric/substance abuse) 1. Summary

This measure assesses the average number of outpatient visits during the 180 days after patients’ discharge from psychiatric or substance-related inpatient care.

Clinical rationale:

Most individuals receiving inpatient treatment for a psychiatric disorder require follow-up ambulatory care to promote further recovery and prevent relapse. A number of studies have examined the association between the frequency of aftercare after hospitalization and the likelihood of readmission, but results have been mixed. Herz (2000) conducted a controlled trial demonstrating the efficacy of a multimodal intervention to prevent relapse in schizophrenia that included more frequent outpatient visits, but did not study the influence of frequent outpatient visits alone.

2.

Specifications

Denominator:

All patients admitted to a hospital and discharged with a primary diagnosis of a psychiatric or substance use disorder during the first 6 months of a specified year

Numerator:

The number of outpatient visits attended by patients from the denominator during the first 180 days after inpatient discharge

Data sources:

Administrative data

3. Development Developer:

Leslie and Rosenheck 2000

Stakeholders:

Consumers, clinicians, delivery system managers, researchers

Measure set:

Veterans Health Administration Mental Health Program

Development:

Fully operationalized

Performance Monitoring System 4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Continuity Measures

❚ 531

TABLE 12–21. Intensity of aftercare within 180 days of discharge (psychiatric/substance abuse) (continued) Selected results:

8.7–12.4, 172 Veterans Affairs medical centers 11.6–13.0, 200 private insurance plans (Leslie and Rosenheck 2000) 17.6–17.9, general psychiatric patients 25.8–26.4, substance abuse patients from 22 Veterans Integrated Service Networks 1998–99 (Rosenheck and DiLella 2000)

Case-mix adjustment:

Yes

Type: Cost data:

Multivariate: age, sex, diagnosis, dual diagnosis, serviceconnected illness Estimates from reported expenses

References and Instruments Foster EM: Do aftercare services reduce inpatient psychiatric readmissions? Health Serv Res 34:715–736, 1999 Herz MI, Lamberti JS, Mintz J, et al: A program for relapse prevention in schizophrenia: a controlled study. Arch Gen Psychiatry 57:277–283, 2000 Klinkenberg WD, Calsyn RJ: Predictors of psychiatric hospitalization: a multivariate analysis. Adm Policy Ment Health 25:403–410, 1998 Leslie D, Rosenheck R: Comparing quality of mental health care for public-sector and privately insured populations. Psychiatr Serv 51:650–655, 2000 Rosenheck R, DiLella D: Department of Veterans Affairs National Mental Health Program Performance Monitoring System: Fiscal Year 1999 Report. West Haven, CT, Northeast Program Evaluation Center, 2000 Rosenheck R, Cichetti D: A Mental Health Program Performance Monitoring System for the Department of Veterans Affairs. West Haven, CT, Northeast Program Evaluation Center, 1995

532

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–22. Intensity of post-discharge ambulatory care (psychiatric) 1. Summary

This measure assesses the proportion of inpatients discharged with a psychiatric disorder who have three or more psychiatric outpatient visits within 12 months of discharge.

Clinical rationale:

Most individuals receiving inpatient treatment for a psychiatric disorder require follow-up ambulatory care to promote further recovery and prevent relapse. Limited research evidence suggests a relationship between postdischarge care and subsequent patient outcomes. In retrospective studies, ambulatory follow-up after discharge was associated with better medication compliance, longer community stays, and reduced rehospitalization rates, although these studies were typically unable to control for potentially confounding factors. A multifaceted intervention for schizophrenia that included increased ambulatory visits and early pharmacological intervention for prodromal symptoms was associated with lower rates of relapse and rehospitalization in a randomized, controlled study.

2. Specifications Denominator:

All inpatients discharged with a primary psychiatric disorder during the first 6 months of a specified calendar year

Numerator:

Patients in the denominator who had three or more psychiatric outpatient visits during the 12 months following the index discharge date

Data sources:

Administrative data

3. Development Developer:

Veterans Health Administration: Northeast Program Evaluation Center

Stakeholders:

Consumers, clinicians, delivery system managers, researchers

Measure set:

Veterans Health Administration Mental Health Program Performance Monitoring System

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

41.8%–79.4%, inpatients with primary psychiatric disorders from Veterans Affairs medical centers (Rosenheck and Cichetti 1995)

Continuity Measures

❚ 533

TABLE 12–22. Intensity of post-discharge ambulatory care (psychiatric) (continued) Case-mix adjustment: Type: Cost data:

Yes Analysis by subgroup: age, sex, race, primary psychiatric diagnosis, total number of discharge diagnoses Estimates from reported expenses

References and Instruments Herz MI, Lamberti JS, Mintz J, et al: A program for relapse prevention in schizophrenia: a controlled study. Arch Gen Psychiatry 57:277–283, 2000 Klinkenberg WD, Calsyn RJ: Predictors of psychiatric hospitalization: a multivariate analysis. Adm Policy Ment Health 25:403–410, 1998 Rosenheck R, Cichetti D: A Mental Health Program Performance Monitoring System for the Department of Veterans Affairs. West Haven, CT, Northeast Program Evaluation Center, 1995 Schoenbaum SC, Cookson D, Stelovich S: Postdischarge follow-up of psychiatric inpatients in an HMO setting. Psychiatr Serv 46:943–945, 1995

534

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–23. Outpatient follow-up after initial substancerelated visit (two or more visits) 1. Summary

This measure assesses the proportion of individuals beginning substance abuse treatment as an outpatient who have two or more follow-up visits within 30 days of their first visit.

Clinical rationale:

Alcohol and drug abuse/dependence is prevalent and associated with reduced social functioning, reduced work productivity, poorer health status, and higher medical costs. Effective treatments are available, however, many individuals with substance use disorders leave treatment prematurely. Although confounded by other patient characteristics, observational studies suggest that these patients are subsequently at greater risk for relapse than those who complete a prescribed treatment course. Although clinicians have limited influence in regard to patient engagement in treatment, strategies have been proposed to engage and motivate individuals at risk for early dropout.

2. Specifications Denominator:

All patients attending an initial outpatient visit for a substance-related disorder who do not have an inpatient admission for substance-related disorder in the prior 12 months

Numerator:

Those patients from the denominator who had two or more outpatient visits for a substance-related disorder within 30 days of the initial visit

Data sources:

Administrative data

3. Development Developer:

Department of Veterans Affairs–Palo Alto Health Care System

Stakeholders:

Public sector payers and purchasers, delivery system managers, researchers

Measure set:

Veterans Affairs Substance Abuse Services Performance Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Selected results:

40%, FY1997; 42%, FY1998 (Fong and Piette 1999)

Continuity Measures

❚ 535

TABLE 12–23. Outpatient follow-up after initial substancerelated visit (two or more visits) (continued) References and Instruments American Psychiatric Association: Practice Guideline for the Treatment of Substance Use Disorders: Alcohol, Cocaine, Opioids. Washington, DC, American Psychiatric Association, 1996 Fong WX, Piette JD: VA care for Substance Abuse Patients: Indicators of Facility and VISN Performance (Fiscal Years 1997 and 1998). Palo Alto, CA, Veterans Affairs Palo Alto Health Care System, 1999 Foster EM: Do aftercare services reduce inpatient psychiatric readmissions? Health Serv Res 34:715–736, 1999 Hubbard RL, Craddock SG, Lynn PM, et al: Overview of 1-year follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychol Addict Behav 11:261–278, 1997 Tims FM, Fletcher BW, Hubbard RL: Treatment outcomes for drug abuse clients. NIDA Res Monogr 106:93–113, 1991

536

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–24. Outpatient follow-up after first substance abuse visit 1. Summary

This measure assesses the proportion of patients who receive at least three substance-related services within 30 days of an initial diagnosis of a substance use disorder.

Clinical rationale:

Alcohol and drug abuse/dependence is prevalent and associated with reduced social functioning, work productivity, poorer health status, and higher medical costs. Effective treatments are available; however, many individuals with substance use disorders leave treatment prematurely. Although confounded by other patient characteristics, observational studies suggest that these patients are subsequently at greater risk for relapse than those who complete a prescribed treatment course. Although clinicians have limited influence in regard to patient engagement in treatment, strategies have been proposed to engage and motivate individuals at risk for early dropout.

2. Specifications Denominator:

The number of patients ages 18 and older enrolled in a health plan who receive a service-related diagnosis of a substance use disorder

Numerator:

Patients from the denominator who receive 1) one or 2) three plan-provided alcohol or drug treatment services within 30 days after the index service

Data sources:

Administrative data

3. Development Developer:

Washington Circle Group

Stakeholders:

Accrediting organizations, public sector payers and purchasers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Washington Circle Group Core Performance Measures

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Continuity Measures

❚ 537

TABLE 12–24. Outpatient follow-up after first substance abuse visit (continued) References and Instruments Fiorentine R, Anglin MD: More is better: counseling participation and the effectiveness of outpatient drug treatment. J Subst Abuse Treat 13:341–348, 1996 Hubbard RL, Craddock SG, Lynn PM, et al: Overview of 1-year follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychol Addict Behav 11:261–278, 1997 McCorry F, Garnick D, Bartlett J, et al: Improving Performance Measurement for Alcohol and Other Drug Services: Report of the Washington Circle Group. Rockville, MD, Washington Circle Group and the Center for Substance Abuse Treatment, 2000 Simpson DD, Joe GW, Rowan-Szal G, et al: Client engagement and change during drug abuse treatment. J Subst Abuse Treat 7:117–134, 1995

538

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–25. Change in primary mental health provider 1. Summary

This measure assesses the proportion of individuals using mental health services who experience a change in their principal mental health provider during a 12-month period.

Clinical rationale:

For individuals with severe and persistent mental illness, a number of research studies support the value of continuity of care. A primary mental health clinician may be responsible for coordinating services provided by multiple treaters and agencies, deciding what interventions may be useful in different phases of the illness, and establishing a therapeutic alliance with the patient, his or her family members, and other important sources of support for the patient. Frequent changes in primary clinicians, for example, due to staff turnover, could be detrimental to achieving these goals. There is little empirical evidence that specifically addresses changes in primary clinician.

2. Specifications Denominator:

The total number of individuals in a health plan ages 18 and older who received a mental health service over a specified 12-month period

Numerator:

The number of patients in the denominator who experienced a change in the principal mental health provider

Data sources:

Administrative data

3. Development Developer:

Center for Mental Health Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

Mental Health Statistics Improvement Program

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, health plan purchasing, health plan/provider choice by consumers, health plan provider contracting, external quality improvement

Continuity Measures

❚ 539

TABLE 12–25. Change in primary mental health provider (continued) References and Instruments Center for Mental Health Services: The Final Report of the Mental Health Statistics Improvement Project (MHSIP) Task Force on a Consumer-Oriented Mental Health Report Card. Rockville, MD, Center for Mental Health Services, 1996 Johnson S, Prosser D, Bindman J, et al: Continuity of care for the severely mentally ill: concepts and measures. Soc Psychiatry Psychiatr Epidemiol 32:137–142, 1997 Lehman AF, Postrado LT, Roth D, et al: Continuity of care and client outcomes in the Robert Wood Johnson Foundation Program on Chronic Mental Illness. Milbank Q 72:105–122, 1994 Tehrani E, Krussel J, Borg L, et al: Dropping out of psychiatric treatment: a prospective study of a first admission cohort. Acta Psychiatr Scand 94:266–271, 1996

540

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–26. Change of primary therapist for schizophrenia 1. Summary

This measure assesses the proportion of individuals with schizophrenia who changed primary therapists during a 12-month period.

Clinical rationale:

Changes in treaters occur due to clinician departures, patient preferences, and changing treatment needs. When not related to patient needs, changes in clinicians can be disruptive to patients, their family, and continuity of care. There are no studies that examine the impact of treatment team changes and outcomes.

2. Specifications Denominator:

Enrollees who had either one inpatient admission or two outpatient visits with a primary diagnosis of schizophrenia over a 12-month period and are treated by a primary therapist (i.e., the same therapist) on a regular basis

Numerator:

The number of individuals in the denominator who changed primary therapists

Data sources:

Administrative data, medical record

3. Development Developer:

Popkin et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

23%–25%, 377 Utah Medicaid beneficiaries (Popkin et al. 1998)

References and Instruments Brekke JS, Ansel M, Long J, et al: Intensity and continuity of services and functional outcomes in the rehabilitation of persons with schizophrenia. Psychiatr Serv 50:248–256, 1999 Popkin MK, Callies AL, Lurie N, et al: An instrument to evaluate the process of psychiatric care in ambulatory settings. Psychiatr Serv 48:524–527, 1997 Popkin MK, Lurie N, Manning W, et al: Changes in the process of care for Medicaid patients with schizophrenia in Utah’s prepaid mental health plan. Psychiatr Serv 49:518–523, 1998

Continuity Measures

❚ 541

TABLE 12–27. Treatment absence longer than 90 days 1. Summary

This measure assesses the proportion of patients in the caseload of a facility or clinician who have received no services for a 90-day period.

Clinical rationale:

For patients with chronic mental illness, an absence of treatment longer than 90 days may indicate patient termination against medical advice, a failed follow-up or transfer of the patient within a system, or an inactive patient remaining in an active caseload. Research has shown that among patient reasons for terminating services is dissatisfaction with care or a belief that further treatment is unnecessary. Monitoring prolonged patient absences from treatment and aggregate rates may identify patients at risk or weaknesses in a delivery system’s procedures.

2. Specifications Denominator:

All patients included in the specified case count of an outpatient mental health treatment provider, excluding patients in an assertive community treatment program

Numerator:

All patients in the denominator who received no services during a specified 90-day period

Data sources:

Administrative data

3. Development Developer:

Baker 1998

Stakeholders:

Clinicians, delivery system managers, provider organizations

Measure set:

Physician Performance Indicator Spreadsheet

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments Baker JG: A performance indicator spreadsheet for physicians in community mental health centers. Psychiatr Serv 49:1293–1298, 1998 Tehrani E, Krussel J, Borg L, et al: Dropping out of psychiatric treatment: a prospective study of a first admission cohort. Acta Psychiatr Scand 94:266–271, 1996 Young AS, Grusky O, Jordan D, et al: Routine outcome monitoring in a public mental health system: the impact of patients who leave. Psychiatr Serv 51:85–91, 2000

542

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–28. Incomplete referrals for mental health services 1. Summary

This measure assesses the proportion of consumers enrolled in a case management program who are referred to another provider but indicate they never received a service from the provider.

Clinical rationale:

Case management services assist individuals with severe mental illness in obtaining needed clinical care and social services. Case managers initiate referrals, but a substantial proportion of referrals are not completed. Research suggests that waiting times, proximity, and the quality of contact between the referral source and the new clinician are associated with the likelihood of a patient’s follow-through with a referral.

2. Specifications Denominator:

The total number of consumers enrolled in a health plan’s case management program who respond to a consumer survey at a specified point in time

Numerator:

Of those consumers in the denominator, the number who report on the consumer survey that they were referred for a mental health service by a case manager but did not receive the service

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Tennessee Department of Mental Health and Mental Retardation

Stakeholders:

Public sector payers and purchasers, consumers, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

TennCare Partners Program Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Standards:

Less than 3% (Performance Measures Workgroup 1999)

Continuity Measures

❚ 543

TABLE 12–28. Incomplete referrals for mental health services (continued) References and Instruments Lloyd M, Bradford C, Webb S. Non-attendance at outpatient clinics: is it related to referral process? Fam Pract 10:111–117, 1993 Performance Measures Workgroup: Recommendations for TennCare Partners Program Performance Measures. Nashville, TN, Tennessee Department of Mental Health and Mental Retardation, 1999 Wilkinson LK, Blixen CE, Mallasch NI, et al: Mental health problems in hospitalbased clinics: patient profile and referral patterns. J Am Psychiatr Nurs Assoc 1:140–145, 1995 Wu CH, Kao JC, Chang CJ: Analysis of outpatient referral failures. J Fam Pract 42:498–502, 1996

544

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–29. Mental health appointment no-show rate 1. Summary

This measure assesses the proportion of scheduled appointments for ambulatory mental health visits that patients missed during a specified time period.

Clinical rationale:

Noncompliance with scheduled psychiatric visits is a significant problem for many individuals with severe mental illness. Missed appointments may be related to patient forgetfulness; problems with cognition, organization, or motivation; transportation difficulties; scheduling inconvenience; dissatisfaction with care; or patient belief that no further treatment is necessary. Failure to attend appointments has also been linked to poor social functioning, greater illness severity, and increased likelihood of hospitalization at 6- and 12-month follow-up. For psychiatric treatment facilities, missed appointments can result in inefficient use of staff time and resources. System changes aimed at decreasing no-show rates have been studied with mixed results. The association of improvement in this area with patient outcomes has not been examined.

2. Specifications Denominator:

Total number of appointments for ambulatory mental health visits scheduled within a specified period of time for all patients in a provider’s monthly case count, excluding patients in an assertive community treatment program

Numerator:

The number of appointments included in the denominator that were missed

Data sources:

Administrative data, patient contact/appointment data

3.

Development

Developer:

Baker 1998

Stakeholders:

Clinicians, delivery system managers, provider organizations

Measure set:

Physician Performance Indicator Spreadsheet

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

~60% (Smoller et al. 1998)

Continuity Measures

❚ 545

TABLE 12–29. Mental health appointment no-show rate (continued) References and Instruments Baker JG: A performance indicator spreadsheet for physicians in community mental health centers. Psychiatr Serv 49:1293–1298, 1998 Killaspy H, Banerjee S, King M, et al: Prospective controlled study of psychiatric outpatient non-attendance: characteristics and outcome. Br J Psychiatry 176:160–165, 2000 Reda S, Makhoul S: Prompts to encourage appointment attendance for people with serious mental illness. Cochrane Database Syst Rev (2):CD002085, 2001 Smoller J, McLean R, Otto M, et al: How do clinicians respond to patients who miss appointments? J Clin Psychiatry 59:330–338, 1998 Sparr LF, Moffitt MC, Ward MF: Missed psychiatric appointments: who returns and who stays away. Am J Psychiatry 150:801–805, 1993 Swenson TR, Pekarik G: Interventions for reducing missed initial appointments at a community mental health center. Community Ment Health J 24:205–218, 1988

546

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–30. Termination of treatment for schizophrenia 1. Summary

This measure assesses the proportion of individuals diagnosed with schizophrenia who terminated treatment or were lost to follow-up within the 12-month period.

Clinical rationale:

Studies indicate that premature termination of therapy (including outpatients “lost to follow-up” or who terminate care against clinician’s advice) is common; in one study it comprised 25% of an outpatient sample. Studies comparing patients who do and do not complete a recommended course of treatment have found premature termination to be associated with poorer outcomes and higher rates of subsequent hospitalization. Clinical interventions aimed at premature termination have included clarifying patient preferences for treatment and active outreach after missed visits.

2. Specifications Denominator:

Enrollees who had either one inpatient admission or two outpatient visits with a primary diagnosis of schizophrenia within the 12-month period

Numerator:

The number of individuals in the denominator who terminated treatment or were lost to follow-up (cessation of patient–provider contact due to known or unknown causes, excluding patient death)

Data sources:

Administrative data, medical record

3. Development Developer:

Popkin et al. 1998

Stakeholders:

Clinicians, researchers

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Pilot-testing complete, not yet implemented for routine use

Used in:

Research study

Selected results:

8%–9%, 377 Utah Medicaid beneficiaries (Popkin et al. 1998)

References and Instruments Brekke JS, Ansel M, Long J, et al: Intensity and continuity of services and functional outcomes in the rehabilitation of persons with schizophrenia. Psychiatr Serv 50:248–256, 1999 Popkin MK, Callies AL, Lurie N, et al: An instrument to evaluate the process of psychiatric care in ambulatory settings. Psychiatr Serv 48:524–527, 1997

Continuity Measures

❚ 547

TABLE 12–30. Termination of treatment for schizophrenia (continued) Popkin MK, Lurie N, Manning W, et al: Changes in the process of care for Medicaid patients with schizophrenia in Utah’s prepaid mental health plan. Psychiatr Serv 49:518–523, 1998 Young AS, Grusky O, Jordan D, et al: Routine outcome monitoring in a public mental health system: the impact of patients who leave. Psychiatr Serv 51:85–91, 2000

548

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–31. 60-Day continuation of substance abuse treatment 1. Summary

This measure assesses the proportion of individuals who remain in treatment after more than 60 days but fewer than 90 days after admission.

Clinical rationale:

Many individuals with substance abuse disorders leave treatment prematurely. Although limited by confounding with other patient characteristics, research suggests that termination of substance abuse treatment prior to completing a prescribed course is associated with a greater likelihood of relapse than for patients who complete the course. Studies also show that individuals who complete substance abuse programs are more likely to experience positive outcomes (e.g., abstinence, employment, fewer psychological problems) than patients who failed to return following intake. Although clinicians have limited influence in regard to patient continuation in treatment, strategies have been proposed to engage and motivate individuals at risk for early dropout. This measure is part of a set of measures proposed for testing and has not been adopted by the developing organization.

2. Specifications Denominator:

All plan members who are admitted to an inpatient, intensive outpatient, or alternative intensive setting for a primary diagnosis of substance abuse and have at least one claimsbased encounter during a specified time period (patients with nicotine and caffeine disorders are excluded)

Numerator:

Patients in the denominator who remain in treatment after more than 60 days but fewer than 90 days after admission

Data sources:

Administrative data

3. Development Developer:

American Managed Behavioral Healthcare Association

Stakeholders:

Accrediting organizations, consumers, researchers

Measure set:

PERMS 2.0: Leadership Testing Set

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Continuity Measures

❚ 549

TABLE 12–31. 60-Day continuation of substance abuse treatment (continued) References and Instruments American Managed Behavioral Healthcare Association: PERMS 2.0: Performance Measures for Managed Behavioral Healthcare Programs. Washington, DC, American Managed Behavioral Healthcare Association, 1998 American Psychiatric Association: Practice Guideline for the Treatment of Substance Use Disorders: Alcohol, Cocaine, Opioids. Washington, DC, American Psychiatric Association, 1996 Gottheil E, Sterling RC, Weinstein SP: Pretreatment dropouts: characteristics and outcomes. J Addict Disord 16:1–14, 1997 Simpson DD, Joe GW, Rowan-Szal G, et al: Client engagement and change during drug abuse treatment. J Subst Abuse Treat 7:117–134, 1995

550

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–32. Attendance at initial medication appointment 1. Summary

This measure assesses the proportion of individuals who attend their scheduled initial medication appointment.

Clinical rationale:

Noncompliance with scheduled psychiatric visits is a significant problem for many individuals with severe mental illness. Missed appointments may be related to patient forgetfulness; problems with cognition, organization, or motivation; transportation difficulties; scheduling inconvenience; dissatisfaction with care; or patient belief that no further treatment is necessary. Failure to attend appointments has also been linked to poor social functioning, greater illness severity, and increased likelihood of hospitalization at 6- and 12-month follow-up. For psychiatric treatment facilities, missed appointments can result in inefficient use of staff time and resources. System changes aimed at decreasing no-show rates have been studied with mixed results. The association of improvement in this area with patient outcomes has not been examined.

2.

Specifications

Denominator:

Total number of clients scheduled for an initial medication appointment in a 1-month period of time

Numerator:

Those clients from the denominator who attended their initial medication appointment

Data sources:

Administrative data, patient contact/appointment data

3. Development Developer:

Nevada Division of Mental Health and Developmental Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, legislative members

Measure set:

Nevada Reform Grant Outcome Measures

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Selected results:

52%–57%, Nevada Division of Mental Health clients (Nevada Division of Mental Health and Developmental Services 2002)

Continuity Measures

❚ 551

TABLE 12–32. Attendance at initial medication appointment (continued) References and Instruments Hochstadt NJ, Trybula J Jr: Reducing missed initial appointments in a community mental health center. J Community Psychol 8:261–265, 1980 Nevada Division of Mental Health and Developmental Services: Nevada’s Consumer Oriented Outcome Measures. Carson City, NV, Nevada Department of Human Resources, 2000 Nevada Division of Mental Health and Developmental Services: Performance Indicators, 4th Quarter, FY2002. Carson City, NV, Nevada Department of Human Resources, 2002 Reda S, Makhoul S: Prompts to encourage appointment attendance for people with serious mental illness. Cochrane Database Syst Rev (2):CD002085, 2001 Reust CE, Thomlinson RP, Lattie D: Keeping or missing the initial behavioral health appointment: a qualitative study of referrals in a primary care setting. Fam Syst Health 17:399–411, 1999 Swenson TR, Pekarik G: Interventions for reducing missed initial appointments at a community mental health center. Community Ment Health J 24:205–218, 1988

552

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–33. Attendance at rescheduled medication appointments 1. Summary

This measure assesses the proportion of individuals who attend a rescheduled initial medication appointment.

Clinical rationale:

Noncompliance with scheduled psychiatric visits is a significant problem for many individual with severe mental illness. Missed appointments may be related to patient forgetfulness; problems with cognition, organization, or motivation; transportation difficulties; scheduling inconvenience; dissatisfaction with care; or patient belief that no further treatment is necessary. Failure to attend appointments has also been linked to poor social functioning, greater illness severity, and increased likelihood of hospitalization at 6- and 12-month follow-up. For psychiatric treatment facilities, missed appointments can result in inefficient use of staff time and resources. System changes aimed at decreasing no-show rates have been studied with mixed results.

2. Specifications Denominator:

Total number of clients who missed an initial medication appointment during a 1-month period of time and rescheduled their appointment

Numerator:

Total number of clients in the denominator who rescheduled their appointment and attended the rescheduled visit

Data sources:

Administrative data

3. Development Developer:

Nevada Division of Mental Health and Developmental Services

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, legislative members

Measure set:

Nevada Reform Grant Outcome Measures

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Continuity Measures

❚ 553

TABLE 12–33. Attendance at rescheduled medication appointments (continued) References and Instruments Nevada Division of Mental Health and Developmental Services: Nevada’s Consumer Oriented Outcome Measures. Carson City, NV, Nevada Department of Human Resources, 2000 Reda S, Makhoul S: Prompts to encourage appointment attendance for people with serious mental illness. Cochrane Database Syst Rev (2):CD002085, 2001 Reust CE, Thomlinson RP, Lattie D: Keeping or missing the initial behavioral health appointment: a qualitative study of referrals in a primary care setting. Fam Syst Health 17:399–411, 1999 Smoller J, McLean R, Otto M, et al: How do clinicians respond to patients who miss appointments? J Clin Psychiatry 59:330–338, 1998 Sparr LF, Moffit MC, Ward MF: Missed psychiatric appointments: who returns and who stays away. Am J Psychiatry 150:801–805, 1993

554

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–34. Continuity of care for dual diagnoses 1. Summary

This measure assesses the proportion of inpatients discharged with both psychiatric and substance-related disorders who receive at least four psychiatric and four substance abuse outpatient visits within 12 months after discharge.

Clinical rationale:

Comorbid psychiatric and substance abuse disorders ( i.e., “dual diagnoses”) are associated with higher treatment costs, lower compliance, and poorer treatment outcomes than either category of conditions individually. Research studies have found that providing appropriate treatment for both conditions is associated with an increased likelihood of abstinence, improved psychiatric outcomes, and a lower likelihood of subsequent hospitalization.

2. Specifications Denominator:

The number of inpatients discharged with diagnoses for both psychiatric and substance-related disorders

Numerator:

Those patients in the denominator who receive at least four psychiatric and four substance abuse outpatient visits within the 12-month period after discharge

Data sources:

Administrative data

3. Development Developer:

Veterans Health Administration: Northeast Program Evaluation Center

Stakeholders:

Consumers, clinicians, delivery system managers, researchers

Measure set:

Veterans Health Administration Mental Health Program Performance Monitoring System

Users:

Veterans Health Administration

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Reliability testing results:

Positive

Type:

Internal consistency results available

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

3.8%–50.2%, inpatients from Veterans Affairs medical centers (Rosenheck and Cichetti 1995)

Continuity Measures

❚ 555

TABLE 12–34. Continuity of care for dual diagnoses (continued) Case-mix adjustment: Type:

Cost data:

Yes Analysis by subgroup: age, sex, race, primary psychiatric diagnosis, total number of discharge diagnoses, dual diagnosis Estimates from reported expenses

References and Instruments Dixon L: Dual diagnosis of substance abuse in schizophrenia: prevalence and impact on outcomes. Schizophr Res 35(suppl):S93–S100, 1999 Moggi F, Ouimette PC, Finney JW, et al: Effectiveness of treatment for substance abuse and dependence for dual diagnosis patients: a model of treatment factors associated with one-year outcomes. J Stud Alcohol 60:856–866, 1999 Rosenheck R, Cichetti D: A Mental Health Program Performance Monitoring System for the Department of Veterans Affairs. West Haven, CT, Northeast Program Evaluation Center, 1995 Swindle RW, Phibbs CS, Paradise MJ, et al: Inpatient treatment for substance abuse patients with psychiatric disorders: a national study of determinants of readmission. J Subst Abuse 7:79–97, 1995

556

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–35. Continuity of outpatient rehabilitation visits 1. Summary

This measure assesses the average number of days between the first (index) and second (follow-up) appointment among individuals initiating ambulatory behavioral health rehabilitative treatment.

Clinical rationale:

Rehabilitation in behavioral health services encompasses treatment of substance abuse problems as well as traditional psychosocial rehabilitation for mental disorders. Barton (1999) described the latter as “a range of social, educational, occupational, behavioral, and cognitive interventions for increasing the role performance of persons with serious and persistent mental illness…services aimed at long-term recovery and maximization of self-sufficiency, as distinguished from the symptom stabilization function of acute care” (p. 526). Studies have found that the intensity and continuity of rehabilitative services are associated with improved patient outcomes. However, the duration between the first and second appointment has not been studied specifically.

2. Specifications Denominator:

The total number of new patients with an initial scheduled visit and a second scheduled appointment during a specified period

Numerator:

The total number of days for all patients in the denominator between appointments for the initial and second appointments

Data sources:

Administrative data, patient contact/appointment data

3. Development Developer:

Rehabilitation Accreditation Commission

Stakeholders:

Accrediting organizations, consumers, clinicians, researchers, provider organizations

Measure set:

Rehabilitation Accreditation Commission Performance Indicators

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

External quality improvement

Continuity Measures

❚ 557

TABLE 12–35. Continuity of outpatient rehabilitation visits (continued) References and Instruments Barton R: Psychosocial rehabilitation services in community support systems: a review of outcomes and policy recommendations. Psychiatr Serv 50:525–534, 1999 Brekke JS, Ansel M, Long J, et al: Intensity and continuity of services and functional outcomes in the rehabilitation of persons with schizophrenia. Psychiatr Serv 50:248–256, 1999 Foster EM: Do aftercare services reduce inpatient psychiatric readmissions? Health Serv Res 34:715–736, 1999 Wilkerson D, Shen D, Duhaime M: Performance Indicators for Rehabilitation Programs, Version 1.1. Tucson, AZ, Rehabilitation Accreditation Commission, 1998 Yeaman C, Craine WH, Gorsek J, et al: Performance improvement teams for better psychiatric rehabilitation. Adm Policy Ment Health 27:113–127, 2000

558

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–36. Continuity of outpatient visits post-discharge 1. Summary

This measure assesses the average number of 2-month periods within the first 6 months of discharge from inpatient psychiatric or substance-related care during which patients attended two or more outpatient visits.

Clinical rationale:

Most individuals receiving inpatient treatment for a psychiatric disorder require follow-up ambulatory care to promote further recovery and prevent relapse. A number of studies have examined the association between the frequency of aftercare after hospitalization and the likelihood of readmission, but results have been mixed. Herz (2000) conducted a controlled trial demonstrating the efficacy of a multimodal intervention to prevent relapse in schizophrenia that included more frequent outpatient visits, but did not study the influence of frequent outpatient visits alone.

2. Specifications Denominator:

All patients discharged with a primary diagnosis of a psychiatric or substance use disorder during the first 6 months of a specified year

Numerator:

The number of 2-month periods during the 180 days after discharge that a patient from the denominator attended two or more outpatient visits, summed among all patients from the denominator

Data sources:

Administrative data

3. Development Developer:

Leslie and Rosenheck 2000

Stakeholders:

Consumers, clinicians, delivery system managers, researchers

Measure set:

Veterans Health Administration Mental Health Program Performance Monitoring System

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Continuity Measures

❚ 559

TABLE 12–36. Continuity of outpatient visits post-discharge (continued) Selected results:

1.06–1.16, patients from 172 Veterans Affairs medical centers (Leslie and Rosenheck 2000) 2.2, general psychiatric patients 1.8–1.9 substance abuse patients from 22 Veterans Integrated Service Networks 1998–1999 (Rosenheck and DiLella 2000)

Case-mix adjustment:

Yes

Type: Cost data:

Multivariate: age, sex, diagnosis, dual diagnosis, service connected illness Estimates from reported expenses

References and Instruments Dietzen LL, Bond GR: Relationship between case manager contact and outcome for frequently hospitalized psychiatric clients. Hosp Community Psychiatry 44:839–843, 1993 Foster EM: Do aftercare services reduce inpatient psychiatric readmissions? Health Serv Res 34:715–736, 1999 Herz MI, Lamberti JS, Mintz J, et al: A program for relapse prevention in schizophrenia: a controlled study. Arch Gen Psychiatry 57:277–283, 2000 Klinkenberg WD, Calsyn RJ: Predictors of psychiatric hospitalization: a multivariate analysis. Adm Policy Ment Health 25:403–410, 1998 Leslie D, Rosenheck R: Comparing quality of mental health care for public-sector and privately insured populations. Psychiatr Serv 51:650–655, 2000 Rosenheck R, DiLella D: Department of Veterans Affairs National Mental Health Program Performance Monitoring System: Fiscal Year 1999 Report. West Haven, CT, Northeast Program Evaluation Center, 2000 Rosenheck R, Cichetti D: A Mental Health Program Performance Monitoring System for the Department of Veterans Affairs. West Haven, CT, Northeast Program Evaluation Center, 1995

560

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–37. Planned discharge from child residential programs 1. Summary

This measure assesses the proportion of children who have a “planned” discharge from a residential facility.

Clinical rationale:

“Planned” discharges from residential settings for children and adolescents are those that result from a patient meeting treatment goals (e.g., improving to the point of requiring a less restrictive placement) or the emergence of a more appropriate way to meet their needs (e.g., finding longerterm placement). Conversely, “unplanned” discharges may be due to factors extraneous to patient status or care (such as funding loss or reduction) or due to potentially avoidable aspects of care (e.g., a child running away, patient or family dissatisfaction with service). Based on these considerations, planned versus unplanned discharges are often used as a proxy for the quality and continuity of care.

2. Specifications Denominator:

Number of discharges for patients ages 11 and younger during a given month that were reported by the provider as either “planned” (due to a child meeting treatment goals, needing a less restrictive placement, having found longerterm placement, and/or their treatment goals have been met by the expiration of their contracted stay) or “unplanned” (due to a loss or reduction in funding, a premature termination of services, dissatisfaction with services, the need for more restrictive care, an inability to meet the child’s needs, the child running away, the child’s inability to adjust, or the child’s exhibition of unmanageable behaviors)

Numerator:

Number of discharges from the denominator reported as “planned” (as defined in denominator)

Data sources:

Administrative data, medical record

Alternate versions:

Population: Adolescents (ages 12–21)

3. Development Developer:

Bluegrass Regional Mental Health–Mental Retardation Board Inc.

Stakeholders:

Public sector payers and purchasers, clinicians, delivery system managers, researchers

Measure set:

Bluegrass Regional Children’s Review Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Continuity Measures

❚ 561

TABLE 12–37. Planned discharge from child residential programs (continued) 5. Use Current status:

In routine use

Used in:

External quality improvement

Selected results:

68%, adolescents, statewide data (Bluegrass Regional Mental Health–Mental Retardation Board 2000)

References and Instruments Bluegrass Regional Mental Health–Mental Retardation Board: The Children’s Review Program: Performance Measurement System Implementation Guide, Version 2.0. Lexington, KY, Bluegrass Regional Mental Health–Mental Retardation Board, 2000 Stage SA: Predicting adolescents’ discharge status following residential treatment. Residential Treatment for Children and Youth 16:37–56, 1999

562

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–38. Continuation after substance-related treatment initiation 1. Summary

This measure assesses the proportion of patients who utilize at least three general medical or substance-related services within 30 days of a diagnosis of a substance use disorder.

Clinical rationale:

Alcohol abuse and dependence are prevalent and associated with reduced social functioning and work productivity, poorer health status, and higher medical costs. Effective treatments are available; however, many individuals with substance use disorders leave treatment prematurely. Although confounded by other patient characteristics, observational studies suggest that these patients are subsequently at greater risk for relapse than those who complete a prescribed treatment course. Although clinicians have limited influence in regard to patient engagement in treatment, strategies have been proposed to engage and motivate individuals at risk for early dropout.

2. Specifications Denominator:

All members of a health plan who have an outpatient visit for a primary diagnosis of a substance use disorder during a specified period

Numerator:

Those members in the denominator who within 30 days of diagnosis utilize 1) three substance abuse specialty outpatient visits, consecutive inpatient days, or consecutive residential days; 2) three general medical outpatient visits for a primary diagnosis of substance abuse disorder; or 3) three visits consisting of either specialty substance abuse treatment or general medical treatment

Data sources:

Administrative data

3. Development Developer:

Washington Circle Group

Stakeholders:

Public sector payers and purchasers, clinicians, managed care organizations, delivery system managers, researchers

Measure set:

Washington Circle Group Year 1 Performance Measures

Users:

American Managed Behavioral Healthcare Association

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Continuity Measures

❚ 563

TABLE 12–38. Continuation after substance-related treatment initiation (continued) 5. Use Current status:

Measure defined, not yet pilot-tested

Used in:

Health plan purchasing, health plan/provider choice by consumers, decisions by health plans about provider contracting

References and Instruments Fiorentine R, Anglin MD: More is better: counseling participation and the effectiveness of outpatient drug treatment. J Subst Abuse Treat 13:341–348, 1996 Hubbard RL, Craddock SG, Lynn PM, et al: Overview of 1-year follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychol Addict Behav 11:261–278, 1997 Moos RH, Finney JW, Ouimette PC, et al: A comparative evaluation of substance abuse treatment, I: treatment orientation, amount of care, and 1-year outcomes. Alcohol Clin Exp Res 23:529–536, 1999 Simpson DD, Joe GW, Rowan-Szal G, et al: Client engagement and change during drug abuse treatment. J Subst Abuse Treat 7:117–134, 1995 Washington Circle Group: Improving Performance Measurement by Managed Care Plans for Substance Abuse. Rockville, MD, Washington Circle Group, 1999

564

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–39. Substance abuse maintenance treatment 1. Summary

This measure assesses the proportion of patients who report that services or monitoring were provided following acute treatment for substance abuse or dependence.

Clinical rationale:

Following the completion of inpatient substance abuse treatment, continued engagement of the patient in psychosocial and/or psychopharmacological services is typically needed to maintain the patient’s abstinence. For many patients, successful recovery after discharge involves the use of self-management strategies, self-help groups, and relapse prevention services. Research has found that aftercare services, along with follow-up calls, mailed reminders, and other monitoring strategies, can contribute to relapse prevention.

2. Specifications Denominator:

The number of patients ages 18 and older in a health plan discharged from inpatient or outpatient treatment with a primary or secondary diagnosis of an alcohol or drug disorder

Numerator:

The subset of patients from the denominator who report receiving specific services and/or monitoring by the plan to promote and sustain positive treatment outcomes postdischarge

Data sources:

Administrative data, patient survey/instrument

3. Development Developer:

Washington Circle Group

Stakeholders:

Accrediting organizations, public sector payers and purchasers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Washington Circle Group Core Performance Measures

Development:

Incomplete

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

Measure defined, not yet pilot-tested

Used in

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Continuity Measures

❚ 565

TABLE 12–39. Substance abuse maintenance treatment (continued) References and Instruments Irvin JE, Bowers CA, Dunn ME, et al: Efficacy of relapse prevention: a metaanalytic review. J Consult Clin Psychol 67:563–570, 1999 McCorry F, Garnick D, Bartlett J, et al: Improving Performance Measurement for Alcohol and Other Drug Services: Report of the Washington Circle Group. Rockville, MD, Washington Circle Group and the Center for Substance Abuse Treatment, 2000 Ouimette PC, Moos RH, Finney JW: Influence of outpatient treatment and 12-step group involvement on one-year substance abuse treatment outcomes. J Stud Alcohol 59:513–522, 1998

566

❚

IMPROVING MENTAL HEALTHCARE

TABLE 12–40. Substance abuse treatment after detoxification 1. Summary

This measure assesses the proportion of patients who receive further treatment in the 14-day period after discharge from detoxification treatment.

Clinical rationale:

Although detoxification treatment is an effective medical intervention used to manage an individual safely through the process of acute withdrawal, it is not designed to address the long-standing psychological, social, and behavioral problems associated with alcohol and drug disorders. Ideally, detoxification should be followed by rehabilitative services that include education, counseling, peer support, and other services.

2. Specifications Denominator:

The number of patients ages 18 and older enrolled in a health plan who were diagnosed with a substance abuse or dependence disorder and discharged from detoxification treatment within a defined time period

Numerator:

The number of patients in the denominator who entered alcohol or drug treatment services within 14 days after discharge from detoxification treatment

Data sources:

Administrative data

3. Development Developer:

Washington Circle Group

Stakeholders:

Accrediting organizations, public sector payers and purchasers, clinicians, managed care organizations, delivery system managers, researchers, provider organizations

Measure set:

Washington Circle Group Core Performance Measures

Users:

American College of Mental Health Administration/Santa Fe, Moos R., Veterans Affairs Substance Abuse

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers, external quality improvement

Selected results:

<5%, 12 of 62 reporting areas (Institute of Medicine 1990) >25%, 14 of 62 reporting areas (Institute of Medicine 1990) 4%–9%, seven managed care organizations (Garnick et al. 2002)

Continuity Measures

❚ 567

TABLE 12–40. Substance abuse treatment after detoxification (continued) References and Instruments Garnick D, Lee M, Chalk M, et al: Establishing the feasibility of performance measures for alcohol and other drugs. J Subst Abuse Treat 23:375–385, 2002 Gruber K, Chutape MA, Stitzer ML: Reinforcement-based intensive outpatient treatment for inner city opiate abusers: a short-term evaluation. Drug Alcohol Depend 57:211–223, 2000 Institute of Medicine: Treating Drug Problems: A Study of the Evolution, Effectiveness, and Financing of Public and Private Drug Treatment Systems, Vol 1. Washington, DC, National Academy Press, 1990 McCorry F, Garnick D, Bartlett J, et al: Improving Performance Measurement for Alcohol and Other Drug Services: Report of the Washington Circle Group. Rockville, MD, Washington Circle Group and the Center for Substance Abuse Treatment, Substance Abuse and Mental Health Services Administration, 2000 Wesson DR: Detoxification From Alcohol and Other Drugs. Treatment Improvement Protocol, Series 19 (DHHS publ No SMA 95–3046). Rockville, MD, Substance Abuse and Mental Health Services Administration, 1995

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C H A P T E R

1 3

Patient Safety Measures

569

570

❚

TABLE 13–1.

IMPROVING MENTAL HEALTHCARE

Inpatient days in restraint

1. Summary

This measure assesses the proportion of patient days in an adult psychiatric unit with one or more involuntary restraint events during a 3-month period.

Clinical rationale:

Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. State mental health authorities and other oversight groups commonly monitor provider restraint rates and associated adverse events. Although these data are useful for comparing facilities and identifying outliers, little is known about what would constitute a rate or how such a rate should be adjusted for clinical characteristics of patient populations. The Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards to safeguard patient autonomy and promote safe practices in restraint use. The Cochrane Collaboration 1999 review of restraint use documented reports of serious adverse events resulting from restraints but found no systematic studies that assessed the value of restraints or compared the practice with alternatives.

2. Specifications Denominator:

The number of patient days in an adult inpatient psychiatric unit during a specified 3-month period

Numerator:

The number of inpatient days in the specified period in which the patient was restrained

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

TABLE 13–1.

❚ 571

Inpatient days in restraint (continued)

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000

❚

572

TABLE 13–2.

IMPROVING MENTAL HEALTHCARE

Inpatients restrained per patient day

1. Summary

This measure assesses the number of inpatients experiencing one or more restraint events per inpatient day in an adult psychiatric unit during a 3-month reporting period.

Clinical rationale:

Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. State mental health authorities and other oversight groups commonly monitor provider restraint rates and associated adverse events. Although these data are useful for comparing facilities and identifying outliers, little is known about what would constitute a rate or how such a rate should be adjusted for clinical characteristics of patient populations. The Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards to safeguard patient autonomy and promote safe practices in restraint use. The Cochrane Collaboration 1999 review of restraint use documented reports of serious adverse events resulting from restraints but found no systematic studies that assessed the value of restraints or compared the practice with alternatives.

2. Specifications Denominator:

The number of patient days in an adult inpatient psychiatric unit during a specified 3-month period

Numerator:

Discharged inpatients who experienced one or more involuntary physical restraints during their hospitalization

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3.

Development

Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

TABLE 13–2.

❚ 573

Inpatients restrained per patient day (continued)

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000

574

❚

TABLE 13–3.

IMPROVING MENTAL HEALTHCARE

Duration of restraint in a child residential program

1. Summary

This measure assesses the average number of minutes per therapeutic hold for a child/adolescent residential facility during a specified 1-month period.

Clinical rationale:

A therapeutic hold is a form of involuntary physical restraint used for children. Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. State mental health authorities and other oversight groups commonly monitor provider restraint rates and associated adverse events. Although these data are useful for comparing facilities and identifying outliers, little is known about what would constitute a rate or how such a rate should be adjusted for clinical characteristics of patient populations. The Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards to safeguard patient autonomy and promote safe practices in restraint use. The Cochrane Collaboration 1999 review of restraint use documented reports of serious adverse events resulting from restraints but found no systematic studies that assessed the value of restraints or compared the practice with alternatives.

2. Specifications Denominator:

Number of therapeutic holds that occur at a child and adolescent 24-hour residential behavioral healthcare facility within a calendar month

Numerator:

Sum of the duration in minutes of all therapeutic holds from the denominator

Data sources:

Administrative data, medical record, occurrence report

3.

Development

Developer:

Child and Adolescent Residential Psychiatric Programs (CHARPP)

Stakeholders:

Accrediting organizations, delivery system managers, provider organizations

Measure set:

CHARPP Improvement Measurement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

TABLE 13–3.

❚ 575

Duration of restraint in a child residential program (continued)

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Child and Adolescent Residential Psychiatric Programs: CHIMP User’s Guide. Corvallis, OR, Child and Adolescent Residential Psychiatric Programs, 1999 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000 U.S. Department of Health and Human Services: Use of Restraint and Seclusion in Psychiatric Residential Treatment Facilities Providing Inpatient Psychiatric Services to Individuals Under Age 21. Washington, DC, Health Care Financing Administration, 2001

❚

576

TABLE 13–4.

IMPROVING MENTAL HEALTHCARE

Frequency of restraints among inpatients

1. Summary

This measure assesses the number of involuntary restraint events per adult inpatient who was restrained during an inpatient psychiatric stay.

Clinical rationale:

Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. State mental health authorities and other oversight groups commonly monitor provider restraint rates and associated adverse events. Although these data are useful for comparing facilities and identifying outliers, little is known about what would constitute a rate or how such a rate should be adjusted for clinical characteristics of patient populations. The Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards to safeguard patient autonomy and promote safe practices in restraint use. The Cochrane Collaboration 1999 review of restraint use documented reports of serious adverse events resulting from restraints but found no systematic studies that assessed the value of restraints or compared the practice with alternatives.

2. Specifications Denominator:

The number of adult inpatients who experienced an involuntary physical restraint during psychiatric hospitalization in a 3-month period

Numerator:

The number of involuntary physical restraints occurring in an adult inpatient psychiatric unit during the 3-month period

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3.

Development

Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

TABLE 13–4.

❚ 577

Frequency of restraints among inpatients (continued)

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000

578

❚

TABLE 13–5. 1.

IMPROVING MENTAL HEALTHCARE

Physical management of children in residential programs

Summary

Clinical rationale:

This measure assesses the proportion of children who experience “physical management” by staff in a residential treatment program. A number of “physical management” techniques are used for restraining children in residential treatment programs, including transports and individual or team holdings. These procedures are used to prevent patients from disrupting a treatment program or to prevent them from harming themselves or others. However, these procedures also expose residents and program staff to risk of injury. Potentially safer alternatives to physical management techniques have been developed, including programmatic interventions, conflict de-escalation, psychotherapy, and medications, and their use has been encouraged. Accreditors, voluntary collaboratives, and regulators have monitored rates of physical management and sought reductions in their use.

2. Specifications Denominator:

Total number of resident days × 100, for individuals ages 11 and younger, during a given month

Numerator:

Total number of physical management events, including transports and individual or team holdings (excluding “escorts”), during the month

Data sources:

Administrative data, medical record

Alternate versions:

Population: Adolescents (ages 12–21)

3. Development Developer:

Bluegrass Regional Mental Health–Mental Retardation Board Inc.

Stakeholders:

Public sector payers and purchasers, clinicians, delivery system managers, researchers

Measure set:

Bluegrass Regional Children’s Review Program

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement

Selected results:

2.0–3.69, Adolescents, statewide data (Bluegrass Regional Mental Health–Mental Retardation Board 2000)

Patient Safety Measures

TABLE 13–5.

❚ 579

Physical management of children in residential programs (continued)

References and Instruments Bluegrass Regional Mental Health–Mental Retardation Board: The Children’s Review Program: Performance Measurement System: Implementation Guide, Version 2.0. Lexington, KY, Bluegrass Regional Mental Health–Mental Retardation Board, 2000 Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 Singh NN, Singh SD, Davis CM, et al: Reconsidering the use of seclusion and restraints in inpatient child and adult psychiatry. J Child Fam Stud 8:243–253, 1999 U.S. Department of Health and Human Services: Use of Restraint and Seclusion in Psychiatric Residential Treatment Facilities Providing Inpatient Psychiatric Services to Individuals Under Age 21. Washington, DC, Health Care Financing Administration, 2001

580

❚

TABLE 13–6.

IMPROVING MENTAL HEALTHCARE

Physical restraint use in nursing homes

1. Summary

This measure assesses the proportion of nursing home residents who were physically restrained.

Clinical rationale:

Physical restraints are used in nursing homes to prevent injury, accident, or assault resulting from altered mental status, ambulatory problems, and/or poor behavioral control. Studies have documented adverse outcomes of restraint use in nursing homes, including agitation, nosocomial infection, pressure sores, injury and death. Ideally, restraint use reflects a balance between maintaining patient autonomy and preserving safety. However, research studies suggest wide variation among nursing homes in their use of restraints. In response to research findings, advocacy, and an Institute of Medicine report, the 1987 Nursing Home Reform Act regulated restraint use and mandated routine reporting. Little is known about what an “appropriate” prevalence of restraint use might be or how such a rate should be adjusted for population characteristics, but prevalence data may be useful for comparative purposes.

2. Specifications Denominator:

All residents of a nursing home facility at a given point in time

Numerator:

Residents from the denominator who were physically restrained on a “daily order” during the previous 7 days

Data sources:

Minimal Data Set 2.0 Resident Assessment Instrument

3. Development Developer:

Center for Health Systems Research and Analysis

Stakeholders:

Clinicians, researchers

Measure set:

University of Wisconsin–Nursing Home Quality Indicators

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

External quality improvement, research study

Selected results:

21%, 4,215 residents in 268 nursing homes (Castle and Mor 1998) 8.7%–10.3%, residents from nursing facilities nationwide, 2000–2001(HCFA 2002) 7.6%–8.2%, 512 nursing facilities in two states (Karon et al. 1999) 4.3%–9.5%, 113 nursing facilities (Rantz et al. 2001)

Patient Safety Measures

TABLE 13–6. Standards:

❚ 581

Physical restraint use in nursing homes (continued) Lower (good) threshold, 1.5% Upper (problematic) threshold, 6.9% (Rantz et al. 2000)

References and Instruments Castle N, Mor V: Physical restraints in nursing homes: a review of the literature since the Nursing Home Reform Act of 1987. Med Care Res Rev 55:171–176, 1998 Guttman R, Altman RD, Karlan MS: Report of the Council on Scientific Affairs, American Medical Association: use of restraints for patients in nursing homes. Arch Fam Med 8:101–105, 1999 Health Care Financing Administration (HCFA): MDS Quality Indicator Report. Washington, DC, Health Care Financing Administration, 2002 Karon S, Sainfort F, Zimmerman D: Stability of nursing home quality indicators over time. Med Care 37:570–579, 1999 Rantz MJ, Petroski GF, Madsen RW, et al: Setting thresholds for quality indicators derived from MDS data for nursing home quality improvement reports: an update. Jt Comm J Qual Improv 26:101–110, 2000 Rantz MJ, Popejoy L, Petroski GF, et al: Randomized clinical trial of a quality improvement intervention in nursing homes. Gerontologist 41:525–538, 2001 Zimmerman DR, Karon SL, Arling G, et al: Development and testing of nursing home quality indicators. Health Care Financ Rev 16:107–127, 1995

582

❚

TABLE 13–7.

IMPROVING MENTAL HEALTHCARE

Physical restraints per inpatient day

1. Summary

This measure assesses the number of restraints per patient day in an adult psychiatric unit during a 3-month reporting period.

Clinical rationale:

Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. State mental health authorities and other oversight groups commonly monitor provider restraint rates and associated adverse events. Although these data are useful for comparing facilities and identifying outliers, little is known about what would constitute a rate or how such a rate should be adjusted for clinical characteristics of patient populations. The Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards to safeguard patient autonomy and promote safe practices in restraint use. The Cochrane Collaboration 1999 review of restraint use documented reports of serious adverse events resulting from restraints but found no systematic studies that assessed the value of restraints or compared the practice with alternatives.

2. Specifications Denominator:

The number of patient days in an adult inpatient psychiatric unit during a specified 3-month period

Numerator:

The number of involuntary physical restraints during the specified period

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

9.2/1,000 among adults (median, SAMHSA 1998)

Patient Safety Measures

TABLE 13–7.

❚ 583

Physical restraints per inpatient day (continued)

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000 Substance Abuse and Mental Health Services Administration (SAMHSA): The FiveState Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Rockville, MD, Substance Abuse and Mental Health Services Administration, 1998

❚

584

TABLE 13–8.

IMPROVING MENTAL HEALTHCARE

Physical restraints per discharge

1. Summary

This measure assesses the number of restraint events per discharge in an inpatient adult psychiatric unit.

Clinical rationale:

Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. State mental health authorities and other oversight groups commonly monitor provider restraint rates and associated adverse events. Although these data are useful for comparing facilities and identifying outliers, little is known about what would constitute a rate or how such a rate should be adjusted for clinical characteristics of patient populations. The Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards to safeguard patient autonomy and promote safe practices in restraint use. The Cochrane Collaboration 1999 review of restraint use documented reports of serious adverse events resulting from restraints but found no systematic studies that assessed the value of restraints or compared the practice with alternatives.

2. Specifications Denominator:

The number of discharges from an adult inpatient psychiatric unit during a 3-month period

Numerator:

The number of involuntary physical restraints during the 3-month period

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

TABLE 13–8.

❚ 585

Physical restraints per discharge (continued)

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000

❚

586

TABLE 13–9.

IMPROVING MENTAL HEALTHCARE

Proportion of inpatients restrained

1. Summary

This measure assesses the proportion of individuals discharged from an adult psychiatric unit who experienced one or more involuntary restraint events during their inpatient stay.

Clinical rationale:

Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. State mental health authorities and other oversight groups commonly monitor provider restraint rates and associated adverse events. Although these data are useful for comparing facilities and identifying outliers, little is known about what would constitute a rate or how such a rate should be adjusted for clinical characteristics of patient populations. The Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards to safeguard patient autonomy and promote safe practices in restraint use. The Cochrane Collaboration 1999 review of restraint use documented reports of serious adverse events resulting from restraints but found no systematic studies that assessed the value of restraints or compared the practice with alternatives.

2. Specifications Denominator:

The number of discharges from an adult inpatient psychiatric unit during a 3-month period

Numerator:

Discharged inpatients who experienced one or more involuntary physical restraints during their hospitalization

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3.

Development

Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

TABLE 13–9.

❚ 587

Proportion of inpatients restrained (continued)

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000

588

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–10. Proportion of inpatient hours in restraint 1. Summary

This measure assesses the proportion of patient hours spent in restraints at a psychiatric facility.

Clinical rationale:

Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. State mental health authorities and other oversight groups commonly monitor provider restraint rates and associated adverse events. Although these data are useful for comparing facilities and identifying outliers, little is known about what would constitute a rate or how such a rate should be adjusted for clinical characteristics of patient populations. The Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards to safeguard patient autonomy and promote safe practices in restraint use. The Cochrane Collaboration 1999 review of restraint use documented reports of serious adverse events resulting from restraints but found no systematic studies that assessed the value of restraints or compared the practice with alternatives.

2. Specifications Denominator:

The number of inpatients on a hospital unit each day (excluding clients on leave status) summed over a specified reporting period, multiplied by 24 hours

Numerator:

Total number of hours spent in restraint by all clients in the denominator during the specified reporting period

Data sources:

Administrative data, medical record, occurrence report

3. Development Developer:

National Association of State Mental Health Program Directors (NASMHPD)

Stakeholders:

Public sector payers and purchasers, clinicians, delivery system managers, researchers

Measure set:

NASMHPD Performance Measures for Mental Health Systems

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 589

TABLE 13–10. Proportion of inpatient hours in restraint (continued) Selected results:

(1.03–2.33)/1,000 inpatient hours, patients from state psychiatric hospitals, 1999–2001 (NASMHPD Research Institute 2002) (0.31–2.44)/1,000 inpatient hours, four states (Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services 2002)

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 National Association of State Mental Health Program Directors (NASMHPD): Performance Measures for Mental Health Systems: A Standardized Framework. Alexandria, VA, National Association of State Mental Health Program Directors, 1998 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: NRI Performance Measurement System: National Public Rates. Available at: http://www.rdmc.org/nripms. Accessed June 15, 2002. Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000 Substance Abuse and Mental Health Services Administration: The Five-State Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Washington, DC, Substance Abuse and Mental Health Services Administration, 1998 Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services: Performance and Outcome Measurement System (POMS) 2001 Annual Report. Richmond, VA, Office of Research and Evaluation, Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services, 2002

590

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–11. Proportion of inpatients in physical restraints 1.

Summary

Clinical rationale:

This measure assesses the proportion of individuals discharged from an inpatient facility who experienced at least one restraint event during their inpatient stay. Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. State mental health authorities and other oversight groups commonly monitor provider restraint rates and associated adverse events. Although these data are useful for comparing facilities and identifying outliers, little is known about what would constitute a rate or how such a rate should be adjusted for clinical characteristics of patient populations. The Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards to safeguard patient autonomy and promote safe practices in restraint use. The Cochrane Collaboration 1999 review of restraint use documented reports of serious adverse events resulting from restraints but found no systematic studies that assessed the value of restraints or compared the practice with alternatives.

2. Specifications Denominator:

The total number of unduplicated inpatients at a psychiatric facility during a specified period

Numerator:

Those from the denominator who were restrained at least once during the specified reporting period

Data sources:

Administrative data, medical record, occurrence report

3. Development Developer:

National Association of State Mental Health Program Directors (NASMHPD)

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

NASMHPD Performance Measures for Mental Health Systems

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 591

TABLE 13–11. Proportion of inpatients in physical restraints (continued) Selected results:

3.5%–4.6%, patients from state psychiatric hospitals nationwide, 1999–2000 (NASMHPD Research Institute 2002) 9.2/1,000 patient days (SAMHSA 1998) 3.9%–12.4%, four states (Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services 2002)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, race, length of stay, unit number, previous report of restraint or seclusion, discharge or current diagnosis

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 National Association of State Mental Health Program Directors (NASMHPD): Performance Measures for Mental Health Systems: A Standardized Framework. Alexandria, VA, National Association of State Mental Health Program Directors, 1998 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: NRI Performance Measurement System: National Public Rates. Available at: http://www.rdmc.org/nripms. Accessed June 15, 2002. Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000 Substance Abuse and Mental Health Services Administration (SAMHSA): The FiveState Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Washington, DC, Substance Abuse and Mental Health Services Administration, 1998 Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services: Performance and Outcome Measurement System (POMS) 2001 Annual Report. Richmond, VA, Office of Research and Evaluation, Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services, 2002

592

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–12. Therapeutic holds in child residential programs 1. Summary

This measure assesses the number of therapeutic holds per child/adolescent patient day in a stay at a residential behavioral healthcare program over a specified 1-month period.

Clinical rationale:

A therapeutic hold is a form of involuntary physical restraint used for children. Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. State mental health authorities and other oversight groups commonly monitor facility restraint rates and associated adverse events. Although these data are useful for comparing facilities and identifying outliers, little is known about what would constitute an “appropriate” rate or how such a comparison should be adjusted for clinical characteristics of patient populations. The Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards to promote safe practices in restraint use and to safeguard patient autonomy. The Cochrane Collaboration 1999 review of restraint use documented reports of serious adverse events resulting from restraints but found no systematic studies that assessed the value of restraints or compared the practice with alternatives.

2. Specifications Denominator:

Number of child and adolescent (ages 3–21) patient days at a 24-hour residential behavioral healthcare facility within a calendar month

Numerator:

Number of therapeutic holds that occur within a calendar month

Data sources:

Administrative data, medical record, occurrence report

3.

Development

Developer:

Child and Adolescent Residential Psychiatric Programs (CHARPP)

Stakeholders:

Accrediting organizations, delivery system managers, provider organizations

Measure set:

CHARPP Improvement Measurement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Patient Safety Measures

❚ 593

TABLE 13–12. Therapeutic holds in child residential programs (continued) 5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Child and Adolescent Residential Psychiatric Programs: CHIMP User’s Guide. Corvallis, OR, Child and Adolescent Residential Psychiatric Programs, 1999 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000 U.S. Department of Health and Human Services: Use of Restraint and Seclusion in Psychiatric Residential Treatment Facilities Providing Inpatient Psychiatric Services to Individuals Under Age 21. Washington, DC, Health Care Financing Administration, 2001

❚

594

IMPROVING MENTAL HEALTHCARE

TABLE 13–13. Inpatient days in seclusion 1. Summary

This measure assesses the proportion of patient days in an adult psychiatric unit with the occurrence of one or more seclusion events.

Clinical rationale:

Seclusion is used in psychiatric treatment settings to prevent patient or staff injury. In order to promote safe practices and safeguard patient autonomy, the Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards for seclusion in psychiatric care. The Cochrane Collaboration published an extensive review of seclusion use in 1999, concluding that although there are reports documenting serious adverse events resulting from seclusion use, there are no systematic studies assessing the value of seclusion or comparing the practice with alternatives. Although utilization rates are commonly calculated, little is known about what would constitute an “appropriate” rate of seclusion or how such a rate should be adjusted for clinical characteristics of patient populations. However, utilization rates may be useful for comparative purposes among institutions treating similar populations or for individual institutions assessing their rates over time.

2. Specifications Denominator:

The number of patient days in an adult inpatient psychiatric unit during a specified 3-month period

Numerator:

The number of patient days with an involuntary seclusion during the 3-month period

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 595

TABLE 13–13. Inpatient days in seclusion (continued) References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000

❚

596

IMPROVING MENTAL HEALTHCARE

TABLE 13–14. Inpatients secluded per patient day 1. Summary

This measure assesses the number of inpatients who experienced one or more seclusion events per patient day in an adult psychiatric unit.

Clinical rationale:

Seclusion is used in psychiatric treatment settings to prevent patient or staff injury. In order to promote safe practices and safeguard patient autonomy, the Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards for seclusion in psychiatric care. The Cochrane Collaboration published an extensive review of seclusion use in 1999, concluding that although there are reports documenting serious adverse events resulting from seclusion use, there are no systematic studies assessing the value of seclusion or comparing the practice with alternatives. Although utilization rates are commonly calculated, little is known about what would constitute an “appropriate” rate of seclusion or how such a rate should be adjusted for clinical characteristics of patient populations. However, utilization rates may be useful for comparative purposes among institutions treating similar populations or for individual institutions assessing their rates over time.

2.

Specifications

Denominator:

The number of patient days in an adult inpatient psychiatric unit during a specified 3-month period

Numerator:

The number of inpatients undergoing a seclusion during the 3-month period

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3.

Development

Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 597

TABLE 13–14. Inpatients secluded per patient day (continued) References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000

❚

598

IMPROVING MENTAL HEALTHCARE

TABLE 13–15. Distribution of seclusion events by duration 1.

Summary

Clinical rationale:

This measure assesses the number of seclusion events in an adult psychiatric unit, distributed by their duration during a 3-month period. Seclusion is used in psychiatric treatment settings to prevent patient or staff injury. In order to promote safe practices and safeguard patient autonomy, the Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards for seclusion in psychiatric care. The Cochrane Collaboration published an extensive review of seclusion use in 1999, concluding that although there are reports documenting serious adverse events resulting from seclusion use, there are no systematic studies assessing the value of seclusion or comparing the practice with alternatives. Although utilization rates are commonly calculated, little is known about what would constitute an “appropriate” rate of seclusion or how such a rate should be adjusted for clinical characteristics of patient populations. However, utilization rates may be useful for comparative purposes among institutions treating similar populations or for individual institutions assessing their rates over time.

2. Specifications Denominator:

The number of seclusions occurring in an adult inpatient psychiatric unit during a 3-month period

Numerator:

The number of involuntary seclusions in the denominator that lasted for a period of time 1) less than or equal to 1 hour, 2) greater than 1 hour but less than or equal to 6 hours, 3) greater than 6 hours but less than or equal to 12 hours, 4) greater than 12 hours

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3.

Development

Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Patient Safety Measures

❚ 599

TABLE 13–15. Distribution of seclusion events by duration (continued) 5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000

600

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–16. Duration of seclusion in a child residential program 1. Summary

This measure assesses the average duration of a seclusion event at a child/adolescent residential facility during a specified 1-month period.

Clinical rationale:

Seclusion is used in psychiatric treatment settings to prevent patient or staff injury. In order to promote safe practices and safeguard patient autonomy, the Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards for seclusion in psychiatric care. The Cochrane Collaboration published an extensive review of seclusion use in 1999, concluding that although there are reports documenting serious adverse events resulting from seclusion use, there are no systematic studies assessing the value of seclusion or comparing the practice with alternatives. Although utilization rates are commonly calculated, little is known about what would constitute an “appropriate” rate of seclusion or how such a rate should be adjusted for clinical characteristics of patient populations. However, utilization rates may be useful for comparative purposes among institutions treating similar populations or for individual institutions assessing their rates over time.

2. Specifications Denominator:

Number of seclusion events administered to a child or adolescent ages 3–21 at a 24-hour residential behavioral healthcare facility within a calendar month

Numerator:

Sum of the duration in minutes of all seclusion events from the denominator

Data sources:

Administrative data, medical record, occurrence report

3. Development Developer:

Child and Adolescent Residential Psychiatric Programs (CHARPP)

Stakeholders:

Accrediting organizations, delivery system managers, provider organizations

Measure set:

CHARPP Improvement Measurement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 601

TABLE 13–16. Duration of seclusion in a child residential program (continued) References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Child and Adolescent Residential Psychiatric Programs: CHIMP User’s Guide. Corvallis, OR, Child and Adolescent Residential Psychiatric Programs, 1999 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001

❚

602

IMPROVING MENTAL HEALTHCARE

TABLE 13–17. Frequency of seclusion among inpatients 1. Summary

This measure assesses the number of involuntary seclusion events per adult inpatient who underwent seclusion during an inpatient psychiatric stay.

Clinical rationale:

Seclusion is used in psychiatric treatment settings to prevent patient or staff injury. In order to promote safe practices and safeguard patient autonomy, the Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards for seclusion in psychiatric care. The Cochrane Collaboration published an extensive review of seclusion use in 1999, concluding that although there are reports documenting serious adverse events resulting from seclusion use, there are no systematic studies assessing the value of seclusion or comparing the practice with alternatives. Although utilization rates are commonly calculated, little is known about what would constitute an “appropriate” rate of seclusion or how such a rate should be adjusted for clinical characteristics of patient populations. However, utilization rates may be useful for comparative purposes among institutions treating similar populations or for individual institutions assessing their rates over time.

2. Specifications Denominator:

The number of inpatients in an adult inpatient psychiatric unit who underwent a seclusion during a 3-month period

Numerator:

The number of involuntary seclusion events during the 3-month period

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 603

TABLE 13–17. Frequency of seclusion among inpatients (continued) References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000

❚

604

IMPROVING MENTAL HEALTHCARE

TABLE 13–18. Involuntary seclusions per discharge 1. Summary

This measure assesses the number of involuntary seclusion events per discharge in an adult psychiatric unit.

Clinical rationale:

Seclusion is used in psychiatric treatment settings to prevent patient or staff injury. In order to promote safe practices and safeguard patient autonomy, the Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards for seclusion in psychiatric care. The Cochrane Collaboration published an extensive review of seclusion use in 1999, concluding that although there are reports documenting serious adverse events resulting from seclusion use, there are no systematic studies assessing the value of seclusion or comparing the practice with alternatives. Although utilization rates are commonly calculated, little is known about what would constitute an “appropriate” rate of seclusion or how such a rate should be adjusted for clinical characteristics of patient populations. However, utilization rates may be useful for comparative purposes among institutions treating similar populations or for individual institutions assessing their rates over time.

2.

Specifications

Denominator:

The number of discharges from an adult inpatient psychiatric unit during a 3-month period

Numerator:

The number of involuntary seclusion events during the 3-month period

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 605

TABLE 13–18. Involuntary seclusions per discharge (continued) References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000

❚

606

IMPROVING MENTAL HEALTHCARE

TABLE 13–19. Involuntary seclusions per inpatient day 1. Summary

This measure assesses the number of involuntary seclusion events per patient day occurring in an adult psychiatric unit.

Clinical rationale:

Seclusion is used in psychiatric treatment settings to prevent patient or staff injury. In order to promote safe practices and safeguard patient autonomy, the Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards for seclusion in psychiatric care. The Cochrane Collaboration published an extensive review of seclusion use in 1999, concluding that although there are reports documenting serious adverse events resulting from seclusion use, there are no systematic studies assessing the value of seclusion or comparing the practice with alternatives. Although utilization rates are commonly calculated, little is known about what would constitute an “appropriate” rate of seclusion or how such a rate should be adjusted for clinical characteristics of patient populations. However, utilization rates may be useful for comparative purposes among institutions treating similar populations or for individual institutions assessing their rates over time.

2. Specifications Denominator:

The number of patient days in an adult inpatient psychiatric unit during a specified 3-month period

Numerator:

The number of involuntary seclusion events during the 3-month period

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

6.2/1,000 among adults (median for five states, SAMHSA 1998)

Patient Safety Measures

❚ 607

TABLE 13–19. Involuntary seclusions per inpatient day (continued) References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000 Substance Abuse and Mental Health Services Administration (SAMHSA): The Five-State Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Rockville, MD, Substance Abuse and Mental Health Services Administration, 1998

608

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–20. Proportion of inpatient hours in seclusion 1. Summary

This measure assesses the proportion of patient hours spent in seclusion at a psychiatric facility.

Clinical rationale:

Seclusion is used in psychiatric treatment settings to prevent patient or staff injury. In order to promote safe practices and safeguard patient autonomy, the Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards for seclusion in psychiatric care. The Cochrane Collaboration published an extensive review of seclusion use in 1999, concluding that although there are reports documenting serious adverse events resulting from seclusion use, there are no systematic studies assessing the value of seclusion or comparing the practice with alternatives. Although utilization rates are commonly calculated, little is known about what would constitute an “appropriate” rate of seclusion or how such a rate should be adjusted for clinical characteristics of patient populations. However, utilization rates may be useful for comparative purposes among institutions treating similar populations or for individual institutions assessing their rates over time.

2. Specifications Denominator:

The number of inpatients on a hospital unit (excluding clients on leave status) each day summed over a specified reporting period, multiplied by 24 hours

Numerator:

The total number of hours spent in seclusion by all clients in the denominator during the specified reporting period

Data sources:

Administrative data, medical record, occurrence report

3. Development Developer:

National Association of State Mental Health Program Directors (NASMHPD)

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

NASMHPD Performance Measures for Mental Health Systems

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Patient Safety Measures

❚ 609

TABLE 13–20. Proportion of inpatient hours in seclusion (continued) 5.

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Selected results:

(0.55–1.32)/1,000 inpatient hours, patients from state psychiatric hospitals, 1999–2001 (NASMHPD Research Institute 2002) (0.29–0.94)/1,000 inpatient hours, four states (Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services 2002)

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 National Association of State Mental Health Program Directors (NASMHPD): Performance Measures for Mental Health Systems: A Standardized Framework. Alexandria, VA, National Association of State Mental Health Program Directors, 1998 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: NRI Performance Measurement System: National Public Rates. Available at: www.rdmc.org/nripms. Accessed June 15, 2002 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000 Substance Abuse and Mental Health Services Administration: The Five-State Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Washington, DC, Substance Abuse and Mental Health Services Administration, 1998 Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services: Performance and Outcome Measurement System (POMS) 2001 Annual Report. Richmond, VA, Office of Research and Evaluation, Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services, 2002

610

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–21. Proportion of inpatients in seclusion 1. Summary

This measure assesses the proportion of inpatients who experienced at least one seclusion event during a psychiatric hospitalization.

Clinical rationale:

Seclusion is used in psychiatric treatment settings to prevent patient or staff injury. In order to promote safe practices and safeguard patient autonomy, the Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards for seclusion in psychiatric care. The Cochrane Collaboration published an extensive review of seclusion use in 1999, concluding that although there are reports documenting serious adverse events resulting from seclusion use, there are no systematic studies assessing the value of seclusion or comparing the practice with alternatives. Although utilization rates are commonly calculated, little is known about what would constitute an “appropriate” rate of seclusion or how such a rate should be adjusted for clinical characteristics of patient populations. However, utilization rates may be useful for comparative purposes among institutions treating similar populations or for individual institutions assessing their rates over time.

2. Specifications Denominator:

The total number of unduplicated clients who were inpatients at the facility during the reporting period

Numerator:

Those from the denominator who were secluded at least once during the specified reporting period

Data sources:

Administrative data, medical record, occurrence report

3. Development Developer:

National Association of State Mental Health Program Directors (NASMHPD)

Stakeholders:

Public sector payers and purchasers, consumers, clinicians, delivery system managers, researchers

Measure set:

NASMHPD Performance Measures for Mental Health Systems

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 611

TABLE 13–21. Proportion of inpatients in seclusion (continued) Selected results:

2.7%–4.7%, patients from state psychiatric hospitals nationwide, 1999–2000 (National Association of State Mental Health Program Directors Research Institute 2002) 6.2/1,000 patient days (SAMHSA 1998) 3.1%–17.9%, four states (Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services 2002)

Case-mix adjustment:

Yes

Type:

Multivariate: age, sex, race, length of stay, unit number, previous report of restraint or seclusion, discharge or current diagnoses, legal status

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001 National Association of State Mental Health Program Directors (NASMHPD): Performance Measures for Mental Health Systems: A Standardized Framework. Alexandria, VA, National Association of State Mental Health Program Directors, 1998 National Association of State Mental Health Program Directors (NASMHPD) Research Institute: NRI Performance Measurement System: National Public Rates. Available at www.rdmc.org/nripms. Accessed June 15, 2002 Sailas E, Fenton M: Seclusion and restraint for serious mental illnesses. Cochrane Database Syst Rev (2):CD001163, 2000 Substance Abuse and Mental Health Services Administration (SAMHSA): The FiveState Feasibility Study: Implementing Performance Measures Across State Mental Health Systems. Washington, DC, Substance Abuse and Mental Health Services Administration, 1998 Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services: Performance and Outcome Measurement System (POMS) 2001 Annual Report. Richmond, VA, Office of Research and Evaluation, Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services, 2002

612

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–22. Seclusion events per day in a child residential program 1. Summary

This measure assesses the number of incidents of seclusion per patient day at a child/adolescent residential facility.

Clinical rationale:

Seclusion is used in psychiatric treatment settings to prevent patient or staff injury. In order to promote safe practices and safeguard patient autonomy, the Joint Commission on Accreditation of Healthcare Organizations and the Health Care Financing Administration have developed standards for seclusion in psychiatric care. The Cochrane Collaboration published an extensive review of seclusion use in 1999, concluding that although there are reports documenting serious adverse events resulting from seclusion use, there are no systematic studies assessing the value of seclusion or comparing the practice with alternatives. Although utilization rates are commonly calculated, little is known about what would constitute an “appropriate” rate of seclusion or how such a rate should be adjusted for clinical characteristics of patient populations. However, utilization rates may be useful for comparative purposes among institutions treating similar populations or for individual institutions assessing their rates over time.

2. Specifications Denominator:

Number of child and adolescent (ages 3–21) patient days at a 24-hour residential behavioral healthcare facility within a calendar month

Numerator:

Number of incidents of seclusion use that occur within a calendar month

Data sources:

Administrative data, medical record, occurrence report

3. Development Developer:

Child and Adolescent Residential Psychiatric Programs (CHARPP)

Stakeholders:

Accrediting organizations, delivery system managers, provider organizations

Measure set:

CHARPP Improvement Measurement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Patient Safety Measures

❚ 613

TABLE 13–22. Seclusion events per day in a child residential program (continued) 5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Case-mix adjustment:

Yes

Type:

Analysis by subgroup: age

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Child and Adolescent Residential Psychiatric Programs: CHIMP User’s Guide. Corvallis, OR, Child and Adolescent Residential Psychiatric Programs, 1999 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999 Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001

❚

614

IMPROVING MENTAL HEALTHCARE

TABLE 13–23. Patient days with physical assaults among adolescent inpatients 1.

Summary

Clinical rationale:

This measure assesses the proportion of patient days in which one or more physical assault events were experienced in an adolescent inpatient facility during a 3-month reporting period. Despite supervision and containment, some inpatients with mental disorders assault staff or other patients. Compared with other inpatients, research studies have shown that assaultive patients have one or more of the following characteristics: young males, disordered thinking, a past history of violence, and a substance-use disorder. The incidence of assaults in inpatient facilities may be associated with assessment and observational practices, staffing level and training, or other facility characteristics, but there has been little study of these relationships. One report described a psychiatric hospital’s violence prevention program, which successfully reduced assault-related injuries to staff. Interventions included raising staff-to-patient ratios, providing additional staff training, assessing patients’ potential for violence, augmenting patient activities, and conducting debriefings and critiques following incidents of assault.

2. Specifications Denominator:

The number of inpatient days during a 3-month reporting period for an adolescent inpatient psychiatric unit

Numerator:

The number of inpatient days in which a physical assault was experienced during the 3-month period

Data sources:

Administrative data, medical record, occurrence report

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4.

Properties

Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 615

TABLE 13–23. Patient days with physical assaults among adolescent inpatients (continued) References and Instruments Flannery RB Jr, Hanson MA, Penk WE: Risk factors for psychiatric inpatient assaults on staff. J Ment Health Adm 21:24–31, 1994 Henk L, Nijman I, Rector G: Crowding and aggression on inpatient psychiatric wards. Psychiatr Serv 50:830–831, 1999 Kashani JH, Jones MR, Borduin CM, et al: Individual characteristics and peer relations of psychiatrically hospitalized aggressive youths: implications for treatment. Child Psychiatry Hum Dev 30:145–159, 2000 Stevenson S, Otto MP: Finding ways to reduce violence in psychiatric hospitals. J Healthc Qual 20:28–32, 1998 Vivona JM, Ecker B, Halgin RP, et al: Self- and other-directed aggression in child and adolescent psychiatric inpatients. J Am Acad Child Adolesc Psychiatry 34:434–444, 1995

❚

616

IMPROVING MENTAL HEALTHCARE

TABLE 13–24. Patient days with self-injuries among adolescent inpatients 1.

Summary

Clinical rationale:

This measure assesses the proportion of patient days in which one or more self-injury events were experienced in an adolescent inpatient facility during a 3-month reporting period. Despite observation and protective measures, some patients with mental disorders injure themselves in inpatient settings. Self-injuries include harmful acts—intended or not—that result from behavior related to psychiatric illness. (The measure excludes accidents such as falls.) Researchers have categorized self-injuries by associated clinical conditions (e.g., psychosis, mental retardation, personality disorder, posttraumatic stress disorder, and childhood behavioral disorders). One study found that adolescent inpatients who injured themselves were more likely to have lived in a foster home, committed antisocial acts, had multiple primary caretakers, and experienced abuse or neglect. The incidence and outcome of self-injury in inpatient facilities may be associated with assessment and observational practices, staffing level and training, or other facility characteristics, but there has been little study of these relationships.

2. Specifications Denominator:

The number of inpatient days during a 3-month reporting period for an adolescent inpatient psychiatric unit

Numerator:

The number of inpatient days in which a self-injury was experienced during the 3-month period

Data sources:

Administrative data, medical record, occurrence report

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 617

TABLE 13–24. Patient days with self-injuries among adolescent inpatients (continued) References and Instruments Favazza AR, Rosenthal RJ: Diagnostic issues in self-mutilation. Hosp Community Psychiatry 44:134–140, 1993 Langbehn DR, Pfohl B: Clinical correlates of self-mutilation among psychiatric inpatients. Ann Clin Psychiatry 5:45–51, 1993 Vivona JM, Ecker B, Halgin RP, et al: Self- and other-directed aggression in child and adolescent psychiatric inpatients. J Am Acad Child Adolesc Psychiatry 34:434–444, 1995 Winchel RM, Stanley M: Self-injurious behavior: a review of the behavior and biology of self-mutilation. Am J Psychiatry 148:306–317, 1991

618

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–25. Patient injury during child/adolescent restraint 1.

Summary

Clinical rationale:

This measure assesses the number of therapeutic holds resulting in an injury to a client at a child/adolescent residential facility during a 1-month period. A therapeutic hold is a form of involuntary physical restraint used for children. Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. Nonetheless, patient injuries during the restraint process have been reported. Children in particular may be at risk of physical injury due to their relative size and strength, and procedures have been developed to minimize the risk. The frequency of patient injury could be influenced by patient characteristics, program staffing levels, training, or physical layout of the facility; however, there is little empirical research examining the impact of these factors.

2. Specifications Denominator:

Number of therapeutic holds that occur at a child and adolescent (ages 3–21) 24-hour residential behavioral healthcare facility within a calendar month

Numerator:

Number of therapeutic holds resulting in an injury to a client within a calendar month

Data sources:

Administrative data, medical record, occurrence report

3. Development Developer:

Child and Adolescent Residential Psychiatric Programs (CHARPP)

Stakeholders:

Accrediting organizations, delivery system managers, provider organizations

Measure set:

CHARPP Improvement Measurement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Child and Adolescent Residential Psychiatric Programs: CHIMP User’s Guide. Corvallis, OR, Child and Adolescent Residential Psychiatric Programs, 1999

Patient Safety Measures

❚ 619

TABLE 13–25. Patient injury during child/adolescent restraint (continued) Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999

620

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–26. Patient injury during restraint or seclusion 1.

Summary

Clinical rationale:

This measure assesses the proportion of psychiatric inpatients restrained or secluded during a 1-month period who are injured during a restraint or seclusion event. The use of physical restraints during psychiatric hospitalization is intended to prevent patient or staff injury; nonetheless, patients are sometimes injured during the process. A 1999 Cochrane Collaboration review of restraint use documented reports of serious adverse events. State mental health authorities and other oversight groups monitor provider restraint rates and associated injuries, and these data can be useful for comparing facilities and identifying outliers. The frequency of patient injury could be influenced by program staffing levels, training, or physical layout of the facility; however, there is little empirical research examining the impact of these factors.

2. Specifications Denominator:

The total number of inpatients restrained or secluded in an inpatient psychiatric program during a specified 1-month period

Numerator:

The number of patients in the denominator who were injured during a restraint or seclusion event

Data sources:

Administrative data, medical record, occurrence report

3. Development Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers

References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999

Patient Safety Measures

❚ 621

TABLE 13–26. Patient injury during restraint or seclusion (continued) Joint Commission on Accreditation of Healthcare Organizations: Restraint and Seclusion Standards for Behavioral Health. Washington, DC, Joint Commission on Accreditation of Healthcare Organizations, 2001

❚

622

IMPROVING MENTAL HEALTHCARE

TABLE 13–27. Physical assaults per inpatient day 1.

Summary

Clinical rationale:

This measure assesses the number of physical assault events per day in an adult inpatient facility during a 3-month period. Despite supervision and containment, some inpatients with mental disorders assault staff or other patients. Compared with other inpatients, research studies have shown that assaultive patients have one or more of the following characteristics: young males, disordered thinking, a past history of violence, and a substance use disorder. The incidence of assaults in inpatient facilities may be associated with assessment and observational practices, staffing level and training, or other facility characteristics, but there has been little study of these relationships. One report described a psychiatric hospital’s violence prevention program, which successfully reduced assault-related injuries to staff. Interventions included raising staff-to-patient ratios, providing additional staff training, assessing patients’ potential for violence, augmenting patient activities, and conducting debriefings and critiques following incidents of assault.

2. Specifications Denominator:

The number of inpatient days during a 3-month reporting period for an adult inpatient psychiatric unit

Numerator:

The number of inpatient assaults sufficiently severe to require medical care

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 623

TABLE 13–27. Physical assaults per inpatient day (continued) References and Instruments Flannery RB Jr, Hanson MA, Penk WE: Risk factors for psychiatric inpatient assaults on staff. J Ment Health Adm 21:24–31, 1994 Kashani JH, Jones MR, Borduin CM, et al: Individual characteristics and peer relations of psychiatrically hospitalized aggressive youths: implications for treatment. Child Psychiatry Hum Dev 30:145–159, 2000 Stevenson S, Otto MP: Finding ways to reduce violence in psychiatric hospitals. J Healthc Qual 20:28–32, 1998 Vivona JM, Ecker B, Halgin RP, et al: Self- and other-directed aggression in child and adolescent psychiatric inpatients. J Am Acad Child Adolesc Psychiatry 34:434–444, 1995

❚

624

IMPROVING MENTAL HEALTHCARE

TABLE 13–28. Physical assaults per discharge among inpatients 1. Summary

This measure assesses the number of physical assault events per discharge in an adult inpatient facility during a 3-month period.

Clinical rationale:

Despite supervision and containment, some inpatients with mental disorders assault staff or other patients. Compared with other inpatients, research studies have shown that assaultive patients have one or more of the following characteristics: young males, disordered thinking, a past history of violence, and a substance use disorder. The incidence of assaults in inpatient facilities may be associated with assessment and observational practices, staffing level and training, or other facility characteristics, but there has been little study of these relationships. One report described a psychiatric hospital’s violence prevention program, which successfully reduced assault-related injuries to staff. Interventions included raising staff-to-patient ratios, providing additional staff training, assessing patients’ potential for violence, augmenting patient activities, and conducting debriefings and critiques following incidents of assault.

2. Specifications Denominator:

The number of discharges from an adult inpatient psychiatric unit during a 3-month period

Numerator:

The number of inpatient assaults sufficiently severe to require medical care

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 625

TABLE 13–28. Physical assaults per discharge among inpatients (continued) References and Instruments Flannery RB Jr, Hanson MA, Penk WE: Risk factors for psychiatric inpatient assaults on staff. J Ment Health Adm 21:24–31, 1994 Kashani JH, Jones MR, Borduin CM, et al: Individual characteristics and peer relations of psychiatrically hospitalized aggressive youths: implications for treatment. Child Psychiatry Hum Dev 30:145–159, 2000 Stevenson S, Otto MP: Finding ways to reduce violence in psychiatric hospitals. J Healthc Qual 20:28–32, 1998 Vivona JM, Ecker B, Halgin RP, et al: Self- and other-directed aggression in child and adolescent psychiatric inpatients. J Am Acad Child Adolesc Psychiatry 34:434–444, 1995

❚

626

IMPROVING MENTAL HEALTHCARE

TABLE 13–29. Self-injuries per inpatient day 1.

Summary

Clinical rationale:

This measure assesses the number of self-injury events per inpatient day in an adult inpatient facility during a 3-month period. Despite observation and protective measures, some patients with mental disorders injure themselves in inpatient settings. Self-injuries include harmful acts—intended or not— that result from behavior related to psychiatric illness. (The measure excludes accidents such as falls.) Researchers have categorized self-injuries by associated clinical conditions (e.g., psychosis, mental retardation, personality disorder, posttraumatic stress disorder, and childhood behavioral disorders). One study found that adolescent inpatients who injured themselves were more likely to have lived in a foster home, committed antisocial acts, had multiple primary caretakers, and experienced abuse or neglect. The incidence and outcome of self-injury in inpatient facilities may be associated with assessment and observational practices, staffing level and training, or other facility characteristics, but there has been little study of these relationships.

2. Specifications Denominator:

The number of inpatient days during a 3-month reporting period for an adult inpatient psychiatric unit

Numerator:

The number of inpatient events of self-harm sufficiently severe to require medical care

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3. Development Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 627

TABLE 13–29. Self-injuries per inpatient day (continued) References and Instruments Favazza AR, Rosenthal RJ: Diagnostic issues in self-mutilation. Hosp Community Psychiatry 44:134–140, 1993 Langbehn DR, Pfohl B: Clinical correlates of self-mutilation among psychiatric inpatients. Ann Clin Psychiatry 5:45–51, 1993 Vivona JM, Ecker B, Halgin RP, et al: Self- and other-directed aggression in child and adolescent psychiatric inpatients. J Am Acad Child Adolesc Psychiatry 34:434–444, 1995 Winchel RM, Stanley M: Self-injurious behavior: a review of the behavior and biology of self-mutilation. Am J Psychiatry 148:306–317, 1991

❚

628

IMPROVING MENTAL HEALTHCARE

TABLE 13–30. Self-injuries per discharge among inpatients 1. Summary

This measure assesses the number of self-injury events per discharge in an adult inpatient facility during a 3-month period.

Clinical rationale:

Despite observation and protection measures, some patients with mental disorders injure themselves in inpatient settings. Self-injuries include harmful acts—intended or not— that result from behavior related to psychiatric illness. (The measure excludes accidents such as falls.) Researchers have categorized these injuries on the basis of associated clinical conditions (e.g., psychosis, mental retardation, character disorder, posttraumatic stress disorder, and childhood disorders) and contexts (e.g., penal institutionalization). Others have defined a form of self-mutilation that is typically milder, repetitive, associated with substance abuse and personality disorder, and most commonly takes the form of superficial cutting of the skin. The incidence of selfinjury on an inpatient psychiatric unit may be associated with assessment and observational practices, staffing level and training, and other unit procedures, but there is little research on these relationships.

2. Specifications Denominator:

The number of discharges from an adult inpatient psychiatric unit during a 3-month period

Numerator:

The number of inpatient events of self-harm sufficiently severe to require medical care

Data sources:

Administrative data, medical record, occurrence report

Alternate versions:

Population: Adolescents

3.

Development

Users:

Florida Council for Community Mental Health, New Jersey Department of Mental Health, Virginia Department of Mental Health, Ohio Department of Mental Health, Massachusetts Department of Mental Health, Mental Health Statistics Improvement Program

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 629

TABLE 13–30. Self-injuries per discharge among inpatients (continued) References and Instruments Favazza AR, Rosenthal RJ: Diagnostic issues in self-mutilation. Hosp Community Psychiatry 44:134–140, 1993 Langbehn DR, Pfohl B: Clinical correlates of self-mutilation among psychiatric inpatients. Ann Clin Psychiatry 5:45–51, 1993 Vivona JM, Ecker B, Halgin RP, et al: Self- and other-directed aggression in child and adolescent psychiatric inpatients. J Am Acad Child Adolesc Psychiatry 34:434–444, 1995 Winchel RM, Stanley M: Self-injurious behavior: a review of the behavior and biology of self-mutilation. Am J Psychiatry 148:306–317, 1991

630

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–31. Staff injury during child/adolescent restraint 1. Summary

This measure assesses the proportion of therapeutic holds in a child/adolescent residential facility that result in an injury to a member of staff during a specified 1-month period.

Clinical rationale:

A therapeutic hold is a form of involuntary physical restraint used for children. Involuntary physical restraints are used in psychiatric treatment settings to prevent patient or staff injury. Nonetheless, staff injuries during the restraint process have been reported. The rate of staff injury could be influenced by program staffing levels, training, facility layout, or patient population; however, there is little empirical research examining the impact of these factors. Research in psychiatric settings suggest that higher rates of restraints are associated with higher rates of staff injury and subsequent absence from work.

2. Specifications Denominator:

Number of therapeutic holds that occur at a child and adolescent 24-hour residential behavioral healthcare facility within a calendar month

Numerator:

Number of therapeutic holds resulting in an injury to staff within a calendar month

Data sources:

Administrative data, medical record, occurrence report

3. Development Developer:

Child and Adolescent Residential Psychiatric Programs (CHARPP)

Stakeholders:

Accrediting organizations, delivery system managers, provider organizations

Measure set:

CHARPP Improvement Measurement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 631

TABLE 13–31. Staff injury during child/adolescent restraint (continued) References and Instruments Busch A, Shore M: Seclusion and restraint: a review of recent literature. Harv Rev Psychiatry 8:261–270, 2000 Child and Adolescent Residential Psychiatric Programs: CHIMP User’s Guide. Corvallis, OR, Child and Adolescent Residential Psychiatric Programs, 1999 Fisher WA: Restraint and seclusion: a review of the literature. Am J Psychiatry 151:1584–1591, 1994 General Accounting Office: Mental Health: Improper Restraint or Seclusion Use Places People at Risk (GAO/HEHS-99–176). Washington, DC, General Accounting Office, 1999

632

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–32. Correct medication administration in child residential programs 1.

Summary

Clinical rationale:

This measure assesses the proportion of prescribed medication doses in a residential facility that are administered to children and adolescents as ordered in a specific month. Errors in the administration of medications include omission, commission, and administration of incorrect doses. Research suggests that these errors are fairly common, costly, and in some cases compromise the physical and mental health of patients. Estimates of the incidence of drug errors vary, but one recent study found an overall rate of prescribing errors of 4/1,000. Drug errors in mental healthcare and residential healthcare have not been well studied.

2. Specifications Denominator:

Number of medication doses prescribed to children and adolescents (ages 3–21) within a calendar month while residing in a 24-hour residential behavioral healthcare facility (excluding doses compromised due to patient refusals or pharmacy errors and medications scheduled for dispensation while the child is not under direct clinical supervision of program staff)

Numerator:

Number of medication doses from the denominator that are administered as ordered by a doctor or nurse and given to the correct patient within 60 minutes of the time designated by the doctor or nurse

Data sources:

Occurrence report, pharmacy data

3.

Development

Developer:

Child and Adolescent Residential Psychiatric Programs (CHARPP)

Stakeholders:

Accrediting organizations, delivery system managers, provider organizations

Measure set:

CHARPP Improvement Measurement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 633

TABLE 13–32. Correct medication administration in child residential programs (continued) References and Instruments Bates D, Cullen D, Laird N, et al: Incidence of adverse drug events and potential adverse drug events. JAMA 274:29–34, 1995 Bates DW, Spell N, Cullen DJ, et al: The costs of adverse drug events in hospitalized patients: Adverse Drug Events Prevention Study Group. JAMA 277:307–311, 1997 Child and Adolescent Residential Psychiatric Programs: CHIMP User’s Guide. Corvallis, OR, Child and Adolescent Residential Psychiatric Programs, 1999 Classen DC, Pestotnik SL, Evans RS, et al: Computerized surveillance of adverse drug events in hospital patients. JAMA 266:2847–2851, 1991 Kohn L, Corrigan J, Donaldson M (eds): To Err Is Human: Building a Safer Health System. Washington, DC, Institute of Medicine, 1999

634

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–33. Delayed medication doses in child residential programs 1.

Summary

Clinical rationale:

This measure assesses the proportion of prescribed medication doses in a residential facility that are administered to children and adolescents more than 60 minutes late in a specified month. Errors in the administration of medications include omission, commission, and administration of incorrect doses. Research suggests that these errors are fairly common, costly, and in some cases compromise the physical and mental health of patients. Estimates of the incidence of drug errors vary, but one recent study found an overall rate of prescribing errors of 4/1,000. Drug errors in mental healthcare and residential healthcare have not been well studied.

2. Specifications Denominator:

Number of medication doses prescribed to children and adolescents (ages 3–21) within a calendar month while residing in a 24-hour residential behavioral healthcare facility (excluding doses compromised due to patient refusals or pharmacy errors and medications scheduled for dispensation while the child is not under direct clinical supervision of program staff)

Numerator:

Number of medication doses from the denominator administered 60 minutes or more after the time ordered by a doctor or nurse

Data sources:

Occurrence report, pharmacy data

3.

Development

Developer:

Child and Adolescent Residential Psychiatric Programs (CHARPP)

Stakeholders:

Accrediting organizations, delivery system managers, provider organizations

Measure set:

CHARPP Improvement Measurement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 635

TABLE 13–33. Delayed medication doses in child residential programs (continued) References and Instruments Bates D, Cullen D, Laird N, et al: Incidence of adverse drug events and potential adverse drug events. JAMA 274:29–34, 1995 Bates DW, Spell N, Cullen DJ, et al: The costs of adverse drug events in hospitalized patients: Adverse Drug Events Prevention Study Group. JAMA 277:307–311, 1997 Child and Adolescent Residential Psychiatric Programs: CHIMP User’s Guide. Corvallis, OR, Child and Adolescent Residential Psychiatric Programs, 1999 Classen DC, Pestotnik SL, Evans RS, et al: Computerized surveillance of adverse drug events in hospital patients. JAMA 266:2847–2851, 1991 Kohn L, Corrigan J, Donaldson M (eds): To Err Is Human: Building a Safer Health System. Washington, DC, Institute of Medicine, 1999

636

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–34. Medication errors of commission, omission, and incorrect dosing 1. Summary

This measure assesses the proportion of medication administrations that include an error of commission, omission, or incorrect dosing during a monthly reporting period

Clinical rationale:

Errors in the administration of medications include omission, commission, and administration of incorrect doses. Errors of commission include administration of the wrong medication, by the wrong method, to a patient with a contraindication, or to the wrong patient. Errors of omission include when a medication is ordered but not administered or administered at a time other than indicated. Research in general medical care suggests that medication errors are fairly common, costly, and in some cases compromise patients’ health. Estimates vary, but one recent study found an overall rate of prescribing errors of 4/1,000. Drug errors have not been well studied in mental healthcare.

2.

Specifications

Denominator:

All medication administrations given via all routes during a monthly reporting period

Numerator:

From the medications in the denominator, all occurrences of 1) commission error (i.e., the wrong medication is administered or the medication is administered by wrong method or route, is given to the wrong patient or to a patient with a contraindication, or is inappropriately continued); 2) omission error (i.e., a medication is ordered and not administered or administered late); or 3) incorrect dosing

Data sources:

Occurrence report, pharmacy data

3. Development Developer:

Institute for Quality Healthcare

Stakeholders:

Accrediting organizations, researchers

Measure set:

Behavioral Health Measures

Development:

Incomplete

4.

Properties

Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 637

TABLE 13–34. Medication errors of commission, omission, and incorrect dosing (continued) References and Instruments Bates D, Cullen D, Laird N, et al: Incidence of adverse drug events and potential adverse drug events. JAMA 274:29–34, 1995 Bates DW, Spell N, Cullen DJ, et al: The costs of adverse drug events in hospitalized patients: Adverse Drug Events Prevention Study Group. JAMA 277:307–311, 1997 Institute for Quality Healthcare: Behavioral Health Measures. Iowa City, IA, University of Iowa 2000 Kohn L, Corrigan J, Donaldson M (eds): To Err Is Human: Building a Safer Health System. Washington, DC, Institute of Medicine, 1999 Lesar TS, Briceland L, Stein DS. Factors related to errors in medication prescribing. JAMA 277(4):312–317, 1997

638

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–35. Medication errors in child residential programs 1. Summary

This measure assesses the proportion of prescribed medication doses in a residential facility that are erroneously administered to children and adolescents in a specified month.

Clinical rationale:

Errors in the administration of medications include omission, commission, and administration of incorrect doses. Research suggests that these errors are fairly common, costly, and in some cases compromise the physical and mental health of patients. Estimates of the incidence of drug errors vary, but one recent study found an overall rate of prescribing errors of 4/1,000. Drug errors in mental healthcare and residential healthcare have not been well studied.

2. Specifications Denominator:

Number of medication doses prescribed to children and adolescents (ages 3–21) within a calendar month while residing in a 24-hour residential behavioral healthcare facility (excluding doses compromised due to patient refusals or pharmacy errors and medications scheduled for dispensation while the child is not under direct clinical supervision of program staff)

Numerator:

Number of medication doses given to the wrong individual or given in a dosing strength other than that ordered by a nurse or doctor

Data sources:

Occurrence report, pharmacy data

3. Development Developer:

Child and Adolescent Residential Psychiatric Programs (CHARPP)

Stakeholders:

Accrediting organizations, delivery system managers, provider organizations

Measure set:

CHARPP Improvement Measurement Program

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

5. Use Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 639

TABLE 13–35. Medication errors in child residential programs (continued) References and Instruments Bates D, Cullen D, Laird N, et al: Incidence of adverse drug events and potential adverse drug events. JAMA 274:29–34, 1995 Bates DW, Spell N, Cullen DJ, et al: The costs of adverse drug events in hospitalized patients: Adverse Drug Events Prevention Study Group. JAMA 277:307–311, 1997 Child and Adolescent Residential Psychiatric Programs: CHIMP User’s Guide. Corvallis, OR, Child and Adolescent Residential Psychiatric Programs, 1999 Classen DC, Pestotnik SL, Evans RS, et al: Computerized surveillance of adverse drug events in hospital patients. JAMA 266:2847–2851, 1991 Kohn L, Corrigan J, Donaldson M (eds): To Err Is Human: Building a Safer Health System. Washington, DC, Institute of Medicine, 1999

640

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–36. Medication errors per inpatient 1. Summary

This measure assesses the number of medication errors per psychiatric inpatient occurring on a specified day.

Clinical rationale:

Errors in the administration of medications include omission, commission, and administration of incorrect doses. Research suggests that these errors are fairly common, costly, and in some cases compromise the physical and mental health of patients. Estimates of the incidence of drug errors vary, but one recent study found an overall rate of prescribing errors of 4/1,000. Drug errors in mental healthcare have not been well studied.

2. Specifications Denominator:

The total number of patients in an inpatient facility on a specified day, including patients who remained in hospital, were discharged, or died

Numerator:

The number of medication errors occurring during the specified day

Data sources:

Administrative data, occurrence report

3. Development Users:

National Association of State Mental Health Program Directors

Development:

Fully operationalized

4. Properties Evidence basis:

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Validity testing:

Positive

Type:

Comparison with the results of other methods or measures, gold standard validity testing

5. Use Current status:

In routine use

Used in:

Health plan purchasing, health plan/provider choice by consumers

References and Instruments Bates D, Cullen D, Laird N, et al: Incidence of adverse drug events and potential adverse drug events. JAMA 274:29–34, 1995 Bates DW, Spell N, Cullen DJ, et al: The costs of adverse drug events in hospitalized patients: Adverse Drug Events Prevention Study Group. JAMA 277:307–311, 1997 Classen DC, Pestotnik SL, Evans RS, et al: Computerized surveillance of adverse drug events in hospital patients. JAMA 266:2847–2851, 199151. Kohn L, Corrigan J, Donaldson M (eds): To Err Is Human: Building a Safer Health System. Washington, DC, Institute of Medicine, 1999

Patient Safety Measures

❚ 641

TABLE 13–36. Medication errors per inpatient (continued) Lesar TS, Briceland L, Stein DS. Factors related to errors in medication prescribing. JAMA 277(4):312–317, 1997

642

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–37. Missed medication doses in child residential programs 1. Summary

This measure assesses the proportion of medication doses prescribed for children and adolescents in a residential facility that were not administered in a specified month.

Clinical rationale:

Errors in the administration of medications include omission, commission, and administration of incorrect doses. Research suggests that these errors are fairly common, costly, and in some cases compromise the physical and mental health of patients. Estimates of the incidence of drug errors vary, but one recent study found an overall rate of prescribing errors of 4/1,000. Drug errors in mental healthcare and residential healthcare have not been well studied.

2. Specifications Denominator:

Number of medication doses prescribed to children and adolescents (ages 3–21) within a calendar month while residing in a 24-hour residential behavioral healthcare facility (excluding doses compromised due to patient refusals or pharmacy errors and medications scheduled for dispensation while the child is not under direct clinical supervision of program staff)

Numerator:

Number of prescribed medication doses from the denominator scheduled for administration that were not administered

Data sources:

Occurrence report, pharmacy data

3. Development Developer:

Child and Adolescent Residential Psychiatric Programs (CHARPP)

Stakeholders:

Accrediting organizations, delivery system managers, provider organizations

Measure set:

CHARPP Improvement Measurement Program

Development:

Fully operationalized

4.

Properties

Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 643

TABLE 13–37. Missed medication doses in child residential programs (continued) References and Instruments Bates D, Cullen D, Laird N, et al: Incidence of adverse drug events and potential adverse drug events. JAMA 274:29–34, 1995 Bates DW, Spell N, Cullen DJ, et al: The costs of adverse drug events in hospitalized patients: Adverse Drug Events Prevention Study Group. JAMA 277:307–311, 1997 Child and Adolescent Residential Psychiatric Programs: CHIMP User’s Guide. Corvallis, OR, Child and Adolescent Residential Psychiatric Programs, 1999 Classen DC, Pestotnik SL, Evans RS, et al: Computerized surveillance of adverse drug events in hospital patients. JAMA 266:2847–2851, 1991 Kohn L, Corrigan J, Donaldson M (eds): To Err Is Human: Building a Safer Health System. Washington, DC, Institute of Medicine, 1999

644

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–38. Inpatient critical incident rates 1.

Summary

Clinical rationale:

This measure assesses the rate of critical incidents occurring at an inpatient psychiatric facility during a specified reporting period. As defined by the Joint Commission on Accreditation of Healthcare Organizations (JCAHO), a critical incident is an event associated with the delivery of healthcare with “the potential to lead to an undesirable outcome if left to progress.” In-depth analysis of critical incidents provides an opportunity for assessment and improvement of systems of care. JCAHO, which accredits inpatient facilities, and other regulatory organizations require hospitals to report critical incidents and to review factors contributing to the adverse event.

2. Specifications Denominator:

The average number of hospitalized inpatients per day within a facility during a specified reporting period × 1,000

Numerator:

Number of critical incidents in the facility during the reporting period, including treatment-related adverse events, aggressive acts, falls and other accidents, self-injury including suicide or suicide attempt, and escape or elopement

Data sources:

Administrative data, occurrence report

3. Development Developer:

Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services

Stakeholders:

Public sector payers and purchasers, consumers clinicians, delivery system managers, researchers

Measure set:

Virginia Performance and Outcomes Measurement System

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level C. Little research evidence, principally based on clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

Patient Safety Measures

❚ 645

TABLE 13–38. Inpatient critical incident rates (continued) References and Instruments Hansson L, Bjorkman T, Berglund I: What is important in psychiatric inpatient care? Quality of care from the patients perspective. Qual Assur Health Care 5:41–47, 1993 Joint Commission on Accreditation of Healthcare Organizations: Comprehensive Accreditation Manual for Behavioral Health Care: 2000 Supplement. Available at http://wwwb.jcaho.org/standard/bhc_supp/bhc_frm.html. Accessed February 11, 2000. Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services: Performance and Outcome Measurement System (POMS): Specification of Performance and Outcome Indicators, Phase I. Version 1.1. Richmond, VA, Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services, 1999 Wright M, Parker G: Incident monitoring in psychiatry. J Qual Clin Pract 18:249–261, 1998

646

❚

IMPROVING MENTAL HEALTHCARE

TABLE 13–39. Unplanned departures from inpatient psychiatric care 1. Summary

This measure assesses the proportion of adult inpatients who have an unplanned departure from a licensed psychiatric unit during a 3-month period.

Clinical rationale:

A hospital departure is unplanned when it occurs against medical advice (AMA), without a physician’s authorization, or when a patient decides not to return after an authorized leave. Unplanned departures can impede the attainment of treatment goals and continuity of care post-discharge. Studies of patients discharged AMA have shown higher symptom levels at discharge and higher rates of readmission than patients discharged on a planned, agreed-upon basis. Research on the course of patients after elopement is mixed.

2. Specifications Denominator:

The number of discharges, including deaths, from an adult inpatient psychiatric unit during a specified 3-month period

Numerator:

Number of discharges against medical advice and elopements during the 3-month period

Data sources:

Administrative data, medical record

Alternate versions:

Setting: Adolescent inpatient psychiatric unit

3.

Development

Development:

Fully operationalized

4. Properties Evidence basis: 5.

AHRQ Level B. Fair research-based evidence and supporting clinical consensus/opinion

Use

Current status:

In routine use

Used in:

Internal quality improvement, external quality improvement

References and Instruments Bowers L, Jarrett M, Clark N: Absconding: a literature review. J Psychiatr Ment Health Nurs 5:343–353, 1998 Dalrymple AJ, Fata M: Cross-validating factors associated with discharges against medical advice. Can J Psychiatry 38:285–289, 1993 Glick ID, Braff DL, Johnson G, et al: Outcome of irregularly discharged psychiatric patients. Am J Psychiatry 138:1472–1476, 1981 Pages KP, Russo JE, Wingerson DK, et al: Predictors and outcome of discharge against medical advice from the psychiatric units of a general hospital. Psychiatr Serv 49:1187–1192, 1998 Stage SA: Predicting adolescents’ discharge status following residential treatment. Residential Treatment for Children and Youth 16:37–56, 1999

A P P E N D I X

Directory of Measure Developers and Users

Agency for Healthcare Research and Quality (AHRQ) 540 Gaither Road Rockville, MD 20850 http://www.ahrq.gov American Academy of Child and Adolescent Psychiatry 3615 Wisconsin Avenue NW Washington, DC 20016-3007 http://www.aacap.org/ http://www.aacap.org/publications/pubcat/bpoutcom.htm American College of Mental Health Administration (ACMHA) 5 Waterside Place Pittsburgh, PA 15222 http://www.acmha.org American Managed Behavioral Healthcare Association (AMBHA) 1101 Pennsylvania Avenue NW Sixth Floor Washington, DC 20004 http://www.ambha.org

647

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IMPROVING MENTAL HEALTHCARE

American Medical Association 515 N. State Street Chicago, IL 60610 http://www.ama-assn.org/ American Psychiatric Association (APA) 1000 Wilson Boulevard, Suite 1825 Arlington, VA 22209-3901 http://www.psych.org Arkansas Department of Human Services Division of Behavioral Health Services 4313 West Markham Little Rock, AR 72205 http://www.state.ar.us/dhs/dmhs/ Bluegrass Regional Mental Health–Mental Retardation Board, Inc. 1351 Newtown Pike Lexington, KY 40511 http://www.bluegrass.org Center for Quality Assessment and Improvement in Mental Health (CQAIMH) Tufts–New England Medical Center The Health Institute 750 Washington Street, NEMC# 345 Boston, MA 02111 http://www.cqaimh.org Chesterfield County, VA, Community Services Board 6801 Lucy Corr Boulevard Chesterfield, VA 23832-0092 http://www.co.chesterfield.va.us/administration/communityservicesboard/csbhome.asp Child and Adolescent Residential Psychiatric Programs (CHARPP) 4455 N.E. Highway 20 Corvallis, OR 97330 http://www.charpp.org

Directory of Measure Developers and Users

❚ 649

Commission on Accreditation of Rehabilitation Facilities (CARF) 4891 E. Grant Road Tucson, AZ 85712 http://www.carf.org Comprehensive Behavioral Care, Inc. 200 South Hoover Boulevard Suite 200 Tampa, FL 33609 http://www.compcare.com Connecticut Department of Mental Health and Addiction Services 410 Capitol Avenue P.O. Box 341431 Hartford, CT 06134 http://www.dmhas.state.ct.us Delaware Health and Social Services, Division of Substance Abuse and Mental Health (DSAMH) 1901 N. Du Pont Highway, Main Building New Castle, DE 19720 http://www.state.de.us/dhss/dsamh/dmhhome.htm Department of Veterans Affairs (VA) Northeast Program Evaluation Center Northeast Program Evaluation Center (182) VA Health Services Research and Development Service VA Connecticut Healthcare System West Haven, CT 06516 http://www.nepec.org Department of Veterans Affairs (VA) Palo Alto Health Care System 3801 Miranda Avenue Palo Alto, CA 94304-1290 http://www.palo-alto.med.va.gov/ Digital Equipment Corporation Worldwide Benefits and Work/Life Solutions 111 Powdermill Road Maynard, MA 01754

650

❚

IMPROVING MENTAL HEALTHCARE

Florida Council for Community Mental Health (FCCMH) 316 E. Park Avenue Tallahassee, FL 32301-1514 http://www.fccmh.org Forum on Performance Measures in Behavioral Health and Related Systems http://www.mhindicators.org/ Foundation for Accountability (FACCT) http://www.markle.org/resources/facct/index.php Illinois Department of Human Services, Mental Health Division 401 S Clinton Street Chicago, IL 60607 http://www.dhs.state.il.us/mhdd/mh/ Iowa Department of Human Services Division of Mental Health and Developmental Disabilities 1305 East Walnut Fifth Floor, Hoover Building Des Moines, IA 50319-0114 http://www.dhs.state.ia.us/mhdd Joint Commission on Accreditation of Healthcare Organizations (JCAHO) One Renaissance Boulevard Oakbrook Terrace, IL 60181 http://www.jcaho.org Kentucky Department for Mental Health and Mental Retardation Services (DMHMRS) 100 Fair Oaks Lane 4E-B Frankfort, KY 40621 http://mhmr.ky.gov/default.asp Maine Department of Health and Human Services, Behavioral and Developmental Services 40 State House Station Augusta, ME 04333-0040 http://www.state.me.us/dmhmrsa/

Directory of Measure Developers and Users

❚ 651

Massachusetts Behavioral Health Partnership 150 Federal Street, 3rd Floor Boston, MA 02110 http://www.masspartnership.com Massachusetts Department of Mental Health Central Office 25 Staniford Street Boston, MA 02114 http://www.state.ma.us/dmh/ Massachusetts Division of Medical Assistance 600 Washington Street Boston, MA 02111 http://www.mass.gov/dma/ M-CARE 2301 Commonwealth Boulevard Ann Arbor, MI 48105-2945 http://www.mcare.org Mental Health Statistics Improvement Project (MHSIP) Center for Mental Health Services 5600 Fishers Lane Rockville, MD 20857 http://www.mhsip.org Minnesota Department of Human Services 444 Lafayette Road North Saint Paul, MN 55155 http://www.dhs.state.mn.us/default.htm National Association of Psychiatric Health Systems (NAPHS) 701 13th Street NW, Suit3 950 Washington, DC 20005-3903 http://www.naphs.org National Association of Social Workers 750 First Street NE, Suite 700 Washington, DC 20002-4241 http://www.naswdc.org/

652

❚

IMPROVING MENTAL HEALTHCARE

National Association of State Mental Health Program Directors (NASMHPD) 66 Canal Center Plaza, Suite 302 Alexandria, VA 22314 http://www.nasmhpd.org NASMHPD Research Institute (NRI) 2351 Huguenard Drive Lexington, KY 40503 http://www.rdmc.org/nripms/purpose.asp National Committee for Quality Assurance (NCQA) 2000 L Street NW, Suite 500 Washington, DC 20036 http://www.ncqa.org/ National Healthcare Quality Report http://www.qualitytools.ahrq.gov/qualityreport/ Nevada Division of Mental Health and Developmental Services Division Administrative Offices 505 East King Street, Room 602 Carson City, NV 89701-3790 http://mhds.state.nv.us/ New Jersey Division of Mental Health Services 50 East State Street PO Box 727 Trenton, NJ 08625-0727 http://www.state.nj.us/humanservices/dmhs/ New York State Office of Alcoholism and Substance Abuse Services (NYS-OASAS) 1450 Western Avenue Albany, NY 12203-3526 http://www.oasas.state.ny.us New York State Office of Mental Health 44 Holland Avenue Albany, NY 12229 http://www.omh.state.ny.us

Directory of Measure Developers and Users

❚ 653

Ohio Department of Mental Health 30 E. Broad Street, 8th Floor Columbus, OH 43215-3430 http://www.mh.state.oh.us Oklahoma Department of Mental Health and Substance Abuse Services 1200 NE 13th Street P.O. Box 53277 Oklahoma City, OK 73152 http://www.odmhsas.org Oregon Department of Human Services Office of Mental Health Services 500 Summer Street NE, E86 Salem, OR 97301 http://www.oregon.gov/DHS/mentalhealth/index.shtml Organisation for Economic Co-operation and Development (OECD) 2, rue André Pascal F-75775 Paris Cedex 16, France http://www.oecd.org Outcomes Roundtable for Children and Families http://orcf-forum.org/default.asp Rhode Island Department of Mental Health, Retardation and Hospitals 14 Harrington Road Cranston, RI 02920-3080 http://www.mhrh.state.ri.us/ Tennessee Department of Mental Health and Developmental Disabilities Cordell Hull Building 425 5th Avenue North, 3rd Floor Nashville, TN 37243-0675 http://www.state.tn.us/mental/

654

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IMPROVING MENTAL HEALTHCARE

Texas Department of State Health Services Substance Abuse Services P.O. Box 80529 Austin, TX 78708 http://www.tcada.state.tx.us Utah Division of Substance Abuse and Mental Health Utah Division of Mental Health 120 North 200 West, Room 209 Salt Lake City, UT 84103 http://www.hsmh.utah.gov/ Value Behavioral Health 240 Corporate Boulevard Norfolk, VA 23502 http://www.valueoptions.com Veterans Health Administration Office of Quality and Performance 810 Vermont Avenue NW Washington, DC 20420 http://www.oqp.med.va.gov/default.asp Virginia Department of Mental Health, Mental Retardation and Substance Abuse Services P.O. Box 1797 Richmond, VA 23218-1797 http://www.dmhmrsas.virginia.gov/ Washington Circle Group http://www.washingtoncircle.org/ Wisconsin Department of Health and Family Services Mental Health Programs 1 W. Wilson Street Madison, WI 53702 http://www.dhfs.state.wi.us/mentalhealth/index.htm

Subject Index All entries refer to Chapters 1–6. Page numbers printed in boldface type refer to tables or figures.

Access to mental healthcare, xi, 10 measures of, 35 Accountability in healthcare delivery, 12 Accreditors of health plans and hospitals, 32 ACT (assertive community treatment), 29–30 Administrative data, 37, 54 Administrative processes, 27 Agency for Healthcare Research and Quality, 72 Aggregate-level measures, 85 Antidepressant medication, 7 Antipsychotic medication, 85 Assertive community treatment (ACT), 29–30 Assessment, xi, 10, 35 Balanced scorecard model, 114, 115 Benchmarks, 89–92, 140 Bipolar disorder, quality of care for patients with, 8 Brainstorming, 116 Case-mix adjustment, 79–82, 84 to mental health quality measures, applications of, 83–84 patient factors used for, 79–80, 80 Case-mix issues in comparison of results, 77–85

Cause and effect diagrams, 117 Center for Quality Assessment and Improvement in Mental Health (CQAIMH), 82, 84, 91, 138 balanced scorecard approach to quality measurement in mental healthcare, 114, 115 core measure set, 62–63, 65, 66–68 characteristics of panelists in consensus development process for, 64 framework for selecting quality measures, 50, 51 Chronic conditions. See also Mental illness increased prevalence of, 5 Clinical practice guidelines, deriving quality measures from, 43 model process for, 44 Clinical processes of care, xi–xii, 27 domains of, 34–37 Clinical rationale, 139 Clinical settings, 58–59 Clinician-reported data, 38 Clinicians conducting internal measurementbased QI, 32 participation of, 110–111 Comorbidity, 80 Comparative data for interpreting measure results, 77, 85–93

655

656

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IMPROVING MENTAL HEALTHCARE

Comparison of results, case-mix issues in, 77–85 Computer-based information systems, 12–13 Confidentiality of patient health information, 54–55 Consumers, process measurement benefiting, 31 Continuity of care, xi, 10, 36, 78, 81, 82 defined, 36 Control limits, 114 Coordination of care, xi, 10, 105 measures of, 36 Core measure sets, 61. See also Measure sets initiatives to develop, 60–61 consensus across stakeholder groups, 62–63, 65–72 consensus within stakeholder groups, 61–62 Core measures, 61 for hospital-based inpatient psychiatric services (HBIPS), 70 Cost-containment strategies, 12, 114, 116 Cost of implementing measures, 53–54, 59, 140 CQAIMH. See Center for Quality Assessment and Improvement in Mental Health Cultural factors and measurementbased QI, 111 Current status, 140 Data sources, 37–39, 139 accuracy of, 54 availability of, 53 selecting among, 41 Decision matrices, 117 Denominator specifications, 139 Depression acute-phase medication treatment of, 40 quality of care for patients with, 7

factors contributing to poor outpatient, 118 treatment of acute, 90 Developer of measure, 139 Development of measures, 139 Diagnosis, 116–118 Diagnostic categories, 57 Diagramming processes, 117 ECHO (Experience of Care and Health Outcomes) Survey, 16 Electroconvulsive therapy (ECT), 9–10 Emerging practices in mental healthcare, 13 Employer purchasers of healthcare, 31–32 Environmental factors and measurement-based QI, 99 Evidence-based practices in mental healthcare, 13 Evidence-based process measures, 52 Evidence basis, 139 Experience of Care and Health Outcomes (ECHO) Survey, 16 External factors, 30–31 Face validity, 52 Federal partnerships with state mental health authorities, 61–62 Fidelity measures, 16 Financial aims. See Cost-containment strategies Fishbone diagrams, 117 Forum on Performance Measures in Behavioral Health, 65, 68 Functional assessment, 18 Global Assessment of Functioning (GAF), 18, 81 Government agencies, 33 Health Plan Employer Data and Information Set (HEDIS), 89, 91 continuity of care measure, 81, 82 Health plans. See also specific topics

Subject Index performance of Texas, 89, 90 Healthcare organizations, 99, 104–105 characteristics associated with better QI, 106–107 factors influencing quality improvement outcomes in, 104 Healthcare system as decentralized, fragmented, and hard to navigate, 5 interactions between consumers and, 14–17 level of, 59 HEDIS. See Health Plan Employer Data and Information Set Hospital-based, inpatient psychiatric services (HBIPS), core measures for, 70 Hospitals, physical restraint and seclusion use in, 85, 112–113, 113 Institute of Medicine (IOM), 11, 14 Instrument panels, 114 Intake data, 39 Internal factors, 30, 31, 97 Interpersonal processes, 16 Interpreting measure results challenges to, 77 comparative data for, 77, 85–93 IOM (Institute of Medicine), 11, 14 Joint Commission on Accreditation of Healthcare Organizations (JCAHO), 70, 102 Laboratory data, 38 Leapfrog Group, 98 Managed behavioral healthcare organizations (MBHOs), 33, 47, 86 Managers, healthcare conducting internal measurementbased QI, 32 Mean results, 87–89

❚ 657 Measure sets, 139. See also Core measure sets Measurement-based quality improvement (QI), xii, 97–98, 123, 128 adoption of, 102 in a broader context, 98–99 conducting, 108 diagnosis, 116–118 identifying a measure, 112–114, 116 planning and intervention, 119–120, 123 selecting a QI aim, 108–111 effectiveness of, 102–105, 108 research on, 102–103, 105 models for, 100–101, 101 principles of, 100 role of, 112 stages of, 100–101, 123, 128 Measures. See Measures Subject Index; Process measures; specific topics Medicaid managed behavioral healthcare, performance standards for quality measures applied to, 86, 87 Medical knowledge, growth in, 5 Medical records, 38 Medicare, ix, 81 Mental disorders, 57 Mental health quality measures, statistical benchmarks for, 92 Mental Health Statistics Improvement Program (MHSIP), 61 Consumer Survey, 16 Mental Health Quality Report, 71 Mental health system, xi–xii dimensions of, 57 clinical conditions, 57 clinical settings, 58–59 level of healthcare system, 59 modalities, 58 vulnerable populations, 57–58 ideal, xi

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IMPROVING MENTAL HEALTHCARE

Mental illness, quality of care for patients with serious, 9 MHSIP. See Mental Health Statistics Improvement Program Microsystems, 99 Multimodal interventions to improve quality of mental healthcare, 124–127 National agenda for quality assessment and improvement, 11–13 National Committee for Quality Assurance (NCQA), 32 National Healthcare Quality Report, 72 National Inventory of Mental Health Quality Measures, xiv, 50, 53, 56–58, 63, 137 Nominal group process, 116 Norms, 89 Numerator specifications, 139 ORCF. See Outcomes Roundtable for Children and Families Organisation for Economic Co-operation and Development (OECD), 72 Healthcare Quality Indicators Project, 72 Organizational activity, dimensions of, 114 Organizational determinants of QI outcomes, 104–105, 110–111 Organizations, mission/objectives of, 110 ORYX initiative, 32 Outcomes and outcome measures, 14, 17–20 Outcomes Roundtable for Children and Families (ORCF), 70–71 PACT (Program for Assertive Community Treatment), 30 Panic disorder, quality of medication treatment for primary care patients with, 8 Pareto charts, 117

Patient experience and measurementbased QI, 98–99 Patient-level measures, 85 Patient-reported data, 38 Physical restraint use in hospitals, 85, 112–113, 113 Practice guidelines. See Clinical practice guidelines Predictive validity, 52–53 President's Advisory Commission on Consumer Protection and Quality in the Health Care Industry, 11 Prevention, 10 Prevention measures, 34 Process control charts, 114 Process-flow diagrams, 117 Process measure uses and users, 30–31. See also Managed behavioral healthcare organizations accreditors, 32 clinicians and managers, 32 consumers, 31 employer purchasers, 31–32 government agencies, 33 mental health services researchers and program evaluators, 34 private and public payers, 33 Process measurement, 47 status of, xiii Process measures, 15–17, 27, 28–29, 29–30, 44. See also specific topics construction of, 39–40, 43–44, 44 denominator specifications, 41 deriving measures from guidelines, 43, 44 determination of quality, 42–43 information proxies, 42 numerator specifications, 41–42 selecting among data sources, 41 feasibility of, 59, 63, 65 meaningfulness of, 50, 59, 63, 65 Processes (of care), 15–17 defined, 14, 34 Program evaluators, mental health services, 34

Subject Index Program for Assertive Community Treatment (PACT), 30 Provider characteristics, adjusting for, 82 Provider selection, 30, 47–48 Providers comparing performance across, 77 consolidation of, 12 Psychiatric disorders, 57 QI. See Quality improvement Quality assessment, 6–11 framework for, 14 methods of, 14 outcome measures, 14, 17–20 process measures, 14–17 structural measures, 14, 15 national agenda for, 11–13 Quality assurance, 4 Quality improvement (QI), xii. See also Measurement-based quality improvement; specific topics aim reviewing progress toward, 111 selecting a, 108–111 effectiveness of modalities for, 120, 121–122, 123 external, 30–31 externally motivating, 48, 108, 111 historical overview of, 3–4 internal, 30, 31, 97 internally facilitating, 48–49 national agenda for, 11–13 outcomes, determinants of external, 108 organizational, 104–105 Quality measurement results, characteristics of metrics for interpreting, 93 Quality of care, 4–5. See also specific topics factors contributing to suboptimal, 5–6 Racial and ethnic minorities, 10 Rate-based measures, 39–40, 77 sampling for, 40

❚ 659 Reliability, 55, 140 Report card initiatives, 50 Research on effectiveness of measurementbased QI, 102–103, 105 on quality of care, 4 Research QI, 31 Researchers, mental health services, 34 Resources, variability in available, 5–6 Risk adjustment. See Case-mix adjustment Risk management records, 39 Root cause analysis, 109 Run charts, 112–114 Safety, patient, 11, 36–37 SAMHSA (Substance Abuse and Mental Health Services Administration), 65 Scheduling data, 39 Schizophrenic patients, 30 quality of care for, 9, 85 Screening, xi Seclusion use in hospitals, 112–113, 113 Selection of quality measures, 47–49, 72–73 framework for actionability, 59 comparability, 56 comprehensibility, 55–56 controllability, 56–57 interpretability, 56 feasibility accuracy, 54, 59 affordability, 53–54 confidentiality, 54–55 data availability, 53 reliability, 55 meaningfulness, 50 addressing stakeholder needs, 52, 60 clinical importance, 51–52 evidence basis, 52 problem area, 53 validity, 52–53

660

❚

IMPROVING MENTAL HEALTHCARE

Selection of quality measures (continud) trade-offs in, 59–60 Severity assessment instruments, 18, 80–81 SMHAs. See State mental health authorities Specifications, 139 Stakeholder needs, addressing, 52, 60 Stakeholders/stakeholder groups, 60, 139. See also under Core measure sets, initiatives to develop outcomes of interest to, 19 Standards, 86–87, 140 State block grants, core performance indicators for, 68–69 State mental health authorities (SMHAs), federal partnerships with, 61–62 State mental health systems, SAMHSA core performance indicators for, 68, 69 Statistical benchmarks. See Benchmarks Structures and structural measures, 14, 15 Subgroup-planning methods, 119 Substance Abuse and Mental Health Services Administration (SAMHSA), 65, 70, 71

core performance indicators for state mental health systems, 68, 69 Substance-related care, quality of, 6–8, 70, 71 Symptoms, instruments assessing, 17–18 Technical factors and measurementbased QI, 111 Technical processes of care, 16, 27 Template for Risk Adjustment Information Transfer (TRAIT), 84–85 Treatment, xi measures of, 35–36 Treatment modalities, 58 Treatment settings. See Clinical settings Treatments, lack of professional consensus regarding optimal, 6 Users, 139 Utilization management data, 39 Validity, 52–53, 140 Vulnerable populations, 57–58 Washington Circle Group core measures for alcohol and other drug services, 70, 71

Measures Subject Index All page numbers refer to tables in Chapters 7–13.

ACT. See Assertive community treatment ADHD. See Attention-deficit/ hyperactivity disorder Adolescent inpatients physical assaults among, 614–615 self-injuries among, 616–617 Adolescent restraint, injuries during, 618–619, 630–631 Aftercare. See also Discharge; Follow-up care; Substance abuse treatment intensity of, 528–533 timeliness of ambulatory, 518–519 Aftercare visit, first attendance at, 494–495 days to, 496–497 Akathisia, treatment of, 360–361 Alcohol abuse in primary care, screening for, 228–229 Alcohol counseling and education, availability of, 144–145 patient experience of, 382–383 Annual physical examination for persons with mental illness, 232–233 Antidepressant medication. See also Depression treatment for acute depression, 288–291 for childhood psychosis, 386–387 for comorbid depression, 348–349

for depressed elderly, 268–269, 278–279, 282–283 dosage of, 270–275, 326–327 duration of, 272–273, 288–289 follow-up visits for, 294–295, 306–307, 508–509 initiation shortly before discharge, 276–277 management of, effective acute-phase treatment, 286–287 effective continuation-phase treatment, 292–293 optimal practitioner contacts, 296–297 treatment plans for, 320–321 Antipsychotic medication atypical, 368–371, 394–395 dosage of, 328–337, 398–399 maintenance duration, 342–343 in nursing homes, 398–399, 402–403 tardive dyskinesia assessment with, 224–225 use for nonpsychotic conditions, 400–401 Anxiety, medication treatment of comorbid, 346–347 Appeal procedures, access to, 204–205 Appeals (health plans), 203 upheld, 208–209

661

662

❚

IMPROVING MENTAL HEALTHCARE

Appointment times, convenience of, 166–167 Assertive community treatment (ACT), 350–351, 396–397 Attention-deficit/hyperactivity disorder (ADHD) family involvement in, 256–257 stimulant medication treatment for, 258–259 treatment engagement of children with, 520–521 Benefit termination, treatment plan for, 486–487 Benzodiazepine use. See also Tranquilizer use in nursing homes, 426–427, 436–437 Bipolar disorder, mood stabilizers for, 266–267 Borderline personality disorder (BPD) psychotherapy for, 388–389 Care planning for dual diagnosis, 480–481 Case management consumer assessments of, 458–459 for dual diagnosis, 452–453 inpatient enrollment in, 460–461 of medical comorbidity, 454–455 for schizophrenic patients, 462–463 Case management services, waiting time for, 186–189 Case manager involvement in discharge planning, 456–457 Child/adolescent restraint, injuries during, 618–619, 630–631 Child case management services, waiting time for, 188–189 Child mental healthcare, family visits in, 449 Child residential programs medication in administration of, 632–633 delayed doses, 634–635 medication errors, 638–639

missed doses, 642–643 physical management in, 578–579 duration of restraint, 574–575 therapeutic holds, 592–593 planned discharge from, 560–561 seclusion events per day in, 612–613 Child specialty care, access to, 158–159 Childhood psychosis, antidepressant medication for, 386–387 Children. See also Attention-deficit/ hyperactivity disorder informed consent for medication treatment of, 422–423 Chronic mental illness. See Severe and persistent mental illness Cognitive impairment, diagnostic evaluation of, 236–239 Community tenure, 406–407 Comorbidity, 346–349. See also under Schizophrenia treatment case management of medical, 454–455 Consumer participation. See also Patient participation in preventive services, 146 in treatment decisions, 408–409 Consumer perception of coercion in treatment choices, 410–411 Continuity of care, for dual diagnosis, 554–555 of outpatient visits post-discharge, 558–559 of rehabilitation visits, 556–557 Coordination of care, 464–465 Cost of care, prohibitive, 172–173 Crisis intervention teams, response time for, 178–179 Critical incident rates, inpatient, 644–645 Cultural appropriateness of mental health services, 414–415 Depressed patients assessment of suicide status and risk in, 220–221

Measures Subject Index elderly, 322–323 antidepressant medication for, 268–269, 282–283 inpatient rehabilitative therapy for, 302–303 treatment engagement of, 524–525 Depression access to child specialty care for, 158–159 follow-up assessment of, 222–223 mild, 314–315 moderate, 316–317 nonresponsive, 312–313 psychotic, 216–217, 310–311 screening for, 148–149 severe, 308–309 untreated, in nursing homes, 322–323 Depression counseling at index visit, 284–285 Depression treatment, 312–317. See also Antidepressant medication assessment of psychiatric history in, 214–215 assessment of psychosis in, 216–217 continuation of, 280–281 doctor visits in inpatient care, 300–301 examination of cognitive functioning for, 238–239 initiation of, 298–299, 318–319 neurological examination in, 244–245 patient termination in, 304–305 somatic treatment, 308–311 visit frequency for, 324–325 Depressive symptoms, assessment of major, 212–213 Detoxification (substance abuse), treatment after, 478–479, 566–567 Discharge. See also Aftercare; Follow-up; Substance abuse treatment antidepressants initiated shortly before, 276–277

❚ 663 criteria for, documented at admission, 474–475 to less restrictive placement, 418–419 medication visit after, 512–513 outpatient visit within 3 days of, 516–517 Discharge planning, case manager involvement in, 456–457 Dual diagnosis, 452–453, 480–481, 502–503, 554–555. See also Comorbidity EAP. See Employee assistance program (EAP) referrals Education, 144–145, 152–153, 344–345, 412–413 Elderly patients. See also Depressed patients, elderly polypharmacy in, 434–435 Emergency visit, ambulatory follow-up after, 492–493 Employee assistance program (EAP) referrals, 170–171 Employment, supported for individuals with severe and persistent mental illness (SPMI), 390–391 Extrapyramidal symptoms (EPS). See under Schizophrenic patients Family, timely inpatient contact with, 484–485 Family involvement in treatment, 256–257, 338–341, 378–379 Financial barriers to care, 172–173 Follow-up care, 490–491. See also Aftercare; Discharge; Substance abuse treatment after emergency visit, 492–493 days to, 498–499 for medication management postdischarge, 294–295, 506–509 for PTSD patients, 502–505

664

❚

IMPROVING MENTAL HEALTHCARE

Follow-up visits. See also Aftercare visit appointment offered after hospitalization, 500–501 continuity of outpatient visits postdischarge, 558–559 Healthcare-related rights, informing consumers about, 412–413 Heart sound examination for depressed inpatients, 240–241 Holds, therapeutic, 592–593 Hospital readmission, 404–407, 446–448 Hospitalization. See Inpatient psychiatric care; see also specific topics Housing for individuals for severe and persistent mental illness (SPMI), 246–247, 392–393 Independent living skills assessment for schizophrenic patients, 248 Injuries. See also Physical assaults; Selfinjuries during physical restraint/seclusion, 618–619, 630–631 Inpatient psychiatric care. See also specific topics unplanned departures from, 646 Involuntary admissions for inpatient mental healthcare, 424–425 Involuntary seclusion, 604–607 Lithium level testing, inpatient, 262–263 Location of services, convenience of, 168–169 Managed behavioral healthcare organizations (MBHOs). See also Service denials emergent phone access to MBHO clinicians, 194–195 rapidity of call answering in, 198–199 rate of live response from, 196–197

Medical problems, assessment for, 234–235 Medical transfer within 72 hours of admission, 243 Medication appointment, attendance at, 550–553 Medication errors, 636–641 Medication management. See also specific drug classes; specific topics access to, 160 Medications documentation of current, 242 informing primary care clinicians of, 468–469 Mental health services denials, review of, 206–207 incomplete referrals for, 542–543 utilization of, 174–175 waiting time for, 190–191 Mental healthcare access to emergent, 183 access to routine, 184–185 urgent, 180–182. See also Crisis intervention teams Mental retardation, 186–187 Missed appointments, 476–477, 544–545, 550–553 Mood stabilizers for bipolar disorder, 266–267 blood level monitoring with, 260–263 side effect monitoring with, 264–265 Neurological examination in depression treatment, 244–245 Nursing homes, 322–323 antipsychotic medication in, 398–399, 402–403 benzodiazepine use in, 426–427, 436–437 Patient participation. See also Consumer participation in treatment planning, 430–431

Measures Subject Index Phone access to MBHO clinicians, emergent, 194–195 Phone call answering, rapidity of, 198–199 Phone contact, clinician response to, 192–193 Physical assaults among inpatients, 614–615, 622–625 Physical management. See also Physical restraint(s); Seclusion; Therapeutic holds of children in residential programs, 578–579 Physical restraint(s), 572–573, 586–587 duration in child residential program, 574–575 frequency among inpatients, 576–577 inpatient days in, 570–571 in nursing homes, 580–581 patient injury during, 618–621 per discharge, 584–585 per inpatient day, 582–583 proportion of inpatient hours in, 588–589 proportion of inpatients in, 590–591 Posttraumatic stress disorder (PTSD), 498–499 Pregnant women, substance abuse treatment for, 164–165 Preventive services, consumer participation in, 146 Primary care, 470–473. See also specific topics communication between mental health and, 464–469 Provider, primary mental health change in, 538–539 Psychological testing, access to, 161 Psychosis, 310–311 antidepressant medication for childhood, 386–387 assessment of, in depression treatment, 216–217

❚ 665 Psychosocial assessments, 154–155, 249 comprehensiveness of, 250–251 timely, 252–253 Psychotherapy, 354–355, 358–359, 388–389 PTSD. See Posttraumatic stress disorder Race/ethnicity, treatment engagement of consumers by, 522–523 Readmission, hospital, 404–407, 446–448 Rehabilitation, vocational for schizophrenic patients, 372–373 Rehabilitation visits, continuity of, 556–557 Rehabilitative therapy for depressed elderly patients, inpatient, 302–303 Relapse monitoring, 147 Restraint. See Physical restraint(s) Retardation, mental, 186–187 Risk to self and others, assessment of, 218–219 Schizophrenia treatment. See also Antipsychotic medication family involvement in, 338–341 medication treatment of comorbid anxiety, 346–347 medication treatment of comorbid depression, 348–349 polypharmacy in, 352–353 psychotherapy, 354–355 availability of medication management and, 358–359 rationale for outlier dosages in, 356–357 for residual symptoms, 364–365 termination of, 546–547 Schizophrenic patients, 147 aftercare intensity for, 528–529 antidepressant dosages for, 326–327

666

❚

IMPROVING MENTAL HEALTHCARE

Schizophrenic patients (continued) assertive community treatment (ACT) program utilization for, 350–351 case management for, 462–463 change of primary therapist for, 540–541 education about medications, 344–345 extrapyramidal symptoms (EPS) in. See also Tardive dyskinesia treatment of akathisia and, 360–361 treatment of drug-related, 362–363 housing assessment for, 246–247 independent living skills assessment for, 248 primary care physicians assigned to, 472–473 treatment engagement of, 526–527 vocational rehabilitation for, 372–373 Seclusion duration of, 598–601 frequency among inpatients, 596–597, 602–603, 610–613 inpatient days in, 594–595 inpatient hours in, 608–609 involuntary, 604–607 patient injury during, 620–621 Self-injuries. See also Injuries among adolescent inpatients, 616–617 during child/adolescent restraint, 630–631 per discharge among inpatients, 628–629 per inpatient day, 626–627 Service denials appeals of, 203–205, 208–209 review of mental health, 206–207 for substance abuse treatment, 203

Severe and persistent mental illness (SPMI), 390–397. See also specific disorders Staff attention to recovery potential, 440–441 sensitivity to cultural/ethnic background, 442–443 Stimulant medication treatment for ADHD, 258–259 Substance abuse assessment in schizophrenia, 230–231 detection, 150–151, 228–229 education, 144–145, 152–153 problems of psychiatric patients, assessment for, 226–227 Substance abuse treatment. See also Alcohol counseling access to, 162–165 after detoxification, 566–567 aftercare/follow-up 14-day follow-up, 510–511 for co-occurring PTSD and substance abuse, 502–503 intensity of aftercare, 530–531 multiple outpatient visits, 514–515 outpatient follow-up after first visit, 534–537 outpatient visit within 3 days of discharge, 516–517 completion of, 376–377, 384–385 continuation of, 548–549, 562–563 family involvement in, 378–379 maintenance pharmacotherapy, 380–381 maintenance treatment, 564–565 rate of appeals and denials for, 203 referral for, 482–483 referral to post-detoxification services, 478–479 retention rate for, 374–375 utilization of, 176–177 Suicide status, assessment of, 220–221

Measures Subject Index Tardive dyskinesia. See also Schizophrenic patients, extrapyramidal symptoms (EPS) in assessment of, 224–225 treatment of, 366–367 Termination of treatment, 304–305, 546–547. See also under Inpatient psychiatric care Therapeutic holds in child residential programs, 592–593. See also Physical restraint(s). Tranquilizer use, 420–421, 428–429, 438–439, 444–445. See also Benzodiazepine use Transfer, medical, 243

❚ 667 Treatment engagement, 520–527 Treatment planning. See also Care planning for dual diagnosis patient participation in, 430–431 Treatment plan(s), 416–417, 444–445 for benefit termination, 486–487 congruence of clinical visit with goals of, 432–433 Utilization management response, timeliness of, 202 Utilization review calls, unanswered, 200–201 Violence. See Injuries; Physical assaults; Self-injuries

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Index of Measures by Domain of Quality All page numbers refer to tables in Chapters 7–13.

Access measures Access to appeal procedures, 204–205 Access to child specialty care for depression, 158–159 Access to emergent mental healthcare, 183 Access to medication management by a psychiatrist, 160 Access to psychological testing, 161 Access to routine mental healthcare, 184 Access to substance abuse treatment, 162–163 Access to substance abuse treatment for pregnant women, 164–165 Chemical dependency utilization: percentage of members receiving inpatient, day/night care, and ambulatory services, 176–177 Clinician response to phone contact, 192–193 Convenience of appointment times, 166–167 Convenience of location of services, 168–169 Emergent phone access to managed behavioral healthcare organization (MBHO) clinicians, 194–195 Employee assistance program (EAP) referrals for mental health and substance abuse, 170–171 Financial barriers to care, 172–173 Managed behavioral healthcare organization (MBHO) rate of live response, 196–197 Mental health utilization: percentage of members receiving inpatient, day/night care, and ambulatory services, 174–175 Rapidity of managed behavioral healthcare organization (MBHO) call answering, 198–199 Rate of appeals and denials for substance abuse treatment, 203 Response time for crisis intervention teams, 178–179 Review of mental health service denials, 206–207 Timeliness of utilization management response, 202

669

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IMPROVING MENTAL HEALTHCARE

Access measures (continued) Unanswered utilization review calls, 200–201 Upheld appeals of managed behavioral healthcare organization (MBHO) service denials, 208–209 Urgent mental healthcare offered within 48 hours, 180–181 Urgent mental healthcare received within 24 hours, 182 Waiting time for case management services (mental retardation), 186–187 Waiting time for child case management services, 188–189 Waiting time for mental health services, 190–191 Assessment measures Annual physical examination for persons with mental illness, 232–233 Assessment of major depressive symptoms, 212–213 Assessment for medical problems of psychiatric patients, 234–235 Assessment of psychiatric history in treating depression, 214–215 Assessment of psychosis in depression treatment, 216–217 Assessment for psychosocial issues of psychiatric patients, 249 Assessment of risk to self/others, 218–219 Assessment for substance abuse problems of psychiatric patients, 226–227 Assessment of suicide status and risk in depression, 220–221 Comprehensiveness of inpatient psychosocial assessments, 250–251 Diagnostic evaluation of new cognitive impairment, 236–237 Documentation of current medications at assessment, 242 Examination of cognitive functioning for depression treatment, 238–239 Follow-up assessment of depression, 222–223 Heart sound examination for depressed inpatients, 240–241 Housing assessment for individuals with schizophrenia, 246–247 Independent living skills assessment for individuals with schizophrenia, 248 Medical transfer within 72 hours of admission, 243 Neurological examination in depression treatment, 244–245 Screening for alcohol abuse in primary care, 228–229 Substance abuse assessment in schizophrenia, 230–231 Tardive dyskinesia assessment with antipsychotic use, 224–225 Timely inpatient psychosocial assessment, 252–253 Continuity 60-Day continuation of substance abuse treatment, 548–549 14-Day follow-up after initiating substance-related treatment, 510–511 Ambulatory follow-up after emergency visit, 492–493 Attendance at first post-discharge appointment, 494–495 Attendance at initial medication appointment, 550–551 Attendance at rescheduled medication appointments, 552–553 Change in primary mental health provider, 538–539 Change of primary therapist for schizophrenia, 540 Continuation after substance-related treatment initiation, 562–563

Index of Measures by Domain of Quality

❚ 671

Continuity of care for dual diagnoses, 554–555 Continuity of outpatient rehabilitation visits, 556–557 Continuity of outpatient visits post-discharge, 558–559 Days to first aftercare visit, 496–497 Days to follow-up care within 6 months of discharge for posttraumatic stress disorder (PTSD), 498–499 Follow-up after hospitalization for mental illness, 490–491 Follow-up appointment offered after hospitalization, 500–501 Follow-up care for co-occurring posttraumatic stress disorder (PTSD) and substance abuse, 502–503 Follow-up care within 6 months of discharge for posttraumatic stress disorder (PTSD), 504–505 Follow-up contact in antidepressant treatment, 508–509 Follow-up for medication management post-discharge, 506–507 Incomplete referrals for mental health services, 542–543 Intensity of aftercare for schizophrenia, 528–529 Intensity of aftercare within 180 days of discharge (psychiatric/substance abuse), 530–531 Intensity of post-discharge ambulatory care (psychiatric), 532–533 Medication visit attended 14 days after hospital discharge, 512–513 Mental health appointment no-show rate, 544–545 Multiple outpatient visits after substance-related hospitalization, 514–515 Outpatient follow-up after first substance abuse visit, 536–537 Outpatient follow-up after initial substance-related visit (two or more visits), 534–535 Outpatient visit within 3 days of discharge (substance abuse), 516–517 Planned discharge from child residential programs, 560–561 Substance abuse maintenance treatment, 564–565 Substance abuse treatment after detoxification, 566–567 Termination of treatment for schizophrenia, 546–547 Timeliness of ambulatory aftercare, 518–519 Treatment absence greater than 90 days, 541 Treatment engagement of children with attention-deficit/hyperactivity disorder (ADHD), 520–521 Treatment engagement of consumers by race/ethnicity, 522–523 Treatment engagement of individuals with depression, 524–525 Treatment engagement of individuals with schizophrenia, 526–527 Coordination Assignment of primary care physician to individuals with schizophrenia, 472–473 Care planning for dual diagnosis, 480–481 Case management for dual diagnosis, 452–453 Case management of medical comorbidity, 454–455 Case management use for disabling schizophrenia, 462–463 Case manager involvement in discharge planning, 456–457 Communication between mental health and primary care, 464–465

672

❚

IMPROVING MENTAL HEALTHCARE

Coordination (continued) Consumer assessments of case management, 458–459 Criteria for discharge documented at admission, 474–475 Detailed communication between mental health and primary care for inpatients, 466–467 Informing primary care clinicians of psychiatric medications, 468–469 Inpatient enrollment in case management, 460–461 Provider contact after missed appointment, 476–477 Referral to post-detoxification services, 478–479 Referral for substance abuse treatment among patients with positive assessment, 482–483 Timely inpatient contact with family, 484–485 Treatment plan for benefit termination, 486–487 Use of primary care by individuals with mental illness, 470–471 Patient safety Inpatient days in restraint, 570–571 Inpatient days in seclusion, 594–595 Inpatients restrained per patient day, 572–573 Inpatients secluded per patient day, 596–597 Correct medication administration in child residential programs, 632–633 Delayed medication doses in child residential programs, 634–635 Distribution of seclusion events by duration, 598–599 Duration of restraint in a child residential program, 574–575 Duration of seclusion in a child residential program, 600–601 Frequency of restraints among inpatients, 576–577 Frequency of seclusion among inpatients, 602–603 Inpatient critical incident rates, 644–645 Involuntary seclusions per discharge, 604–605 Involuntary seclusions per inpatient day, 606–607 Medication errors in child residential programs, 638–639 Medication errors of commission, omission, and incorrect dosing, 636–637 Medication errors per inpatient, 640–641 Missed medication doses in child residential programs, 642–643 Patient days with physical assaults among adolescent inpatients, 614–615 Patient days with self-injuries among adolescent inpatients, 616–617 Patient injury during child/adolescent restraint, 618–619 Patient injury during restraint or seclusion, 620–621 Physical assaults per discharge among inpatients, 624–625 Physical assaults per inpatient day, 622–623 Physical management of children in residential programs, 578–579 Physical restraint use in nursing homes, 580–581 Physical restraints per discharge, 584–585 Physical restraints per inpatient day, 582–583 Proportion of inpatient hours in restraint, 588–589

Index of Measures by Domain of Quality

❚ 673

Proportion of inpatient hours in seclusion, 608–609 Proportion of inpatients in physical restraints, 590–591 Proportion of inpatients in seclusion, 610–611 Proportion of inpatients restrained, 586–587 Seclusion events per day in a child residential program, 612–613 Self-injuries per discharge among inpatients, 628–629 Self-injuries per inpatient day, 626–627 Staff injury during child/adolescent restraint, 630–631 Therapeutic holds in child residential programs, 592–593 Unplanned departures from inpatient psychiatric care, 646 Prevention measures Availability of alcohol counseling and education, 144–145 Consumer participation in preventive services, 146 Relapse monitoring plan for stable-phase schizophrenia, 147 Screening for depression, 148–149 Substance abuse detection, 150–151 Substance abuse education in primary care, 152–153 Timely psychosocial screening, 154–155 Treatment measures Adequacy of antidepressant dosage, 270–271 Adequacy of antidepressant dosage for depressed elderly, 268–269 Adequacy of antidepressant dosing and duration, 272–273 Adequacy of antidepressant drug dosing, 274–275 Antidepressant dosages for depression with schizophrenia, 326–327 Antidepressant initiation shortly before discharge, 276–277 Antidepressant medication management: effective acute-phase treatment, 286–287 Antidepressant medication management: effective continuation-phase treatment, 292–293 Antidepressant medication management: optimal practitioner contacts, 296–297 Antipsychotic drug dosing for inpatients with schizophrenia, 328–329 Antipsychotic drug dosing in nursing homes, 398–399 Antipsychotic drug use for inpatients with schizophrenia, 334–335 Antipsychotic treatment for childhood psychosis, 386–387 Antipsychotic use for nonpsychotic conditions, 400–401 Antipsychotic use in nursing homes, 402–403 Assertive community treatment (ACT) program utilization for individuals with schizophrenia, 350–351 Availability of medication management and psychotherapy for patients with schizophrenia, 358–359 Average length of inpatient stay prior to readmission, 404–405 Benzodiazepine use in nursing homes, 436–437 Blood level monitoring with mood stabilizers, 260–261 Community tenure, 406–407

674

❚

IMPROVING MENTAL HEALTHCARE

Treatment measures (continued) Completion of treatment for substance abuse, 376–377 Congruence of clinical visit with treatment plan goals, 432–433 Consumer participation in treatment decisions, 408–409 Consumer perception of coercion in treatment choices, 410–411 Continuation of depression treatment, 280–281 Cultural appropriateness of mental health services, 414–415 Current treatment plan for psychiatric outpatients, 416–417 Depot antipsychotic medication for schizophrenia, 336–337 Depressed elderly patients discharged on antidepressants, 282–283 Depression counseling at index visit, 284–285 Discharge to less restrictive placement, 418–419 Doctor visits in inpatient care for depression, 300–301 Duration of daily minor tranquilizer use, 420–421 Duration of drug treatment for acute depression (first refill), 288–289 Duration of drug treatment for continuation-phase depression (three prescriptions), 290–291 Educating individuals with schizophrenia about medications, 344–345 Family involvement in attention-deficit/hyperactivity disorder (ADHD), 256–257 Family involvement in schizophrenia treatment, 338–339 Family involvement in substance abuse treatment, 378–379 Family treatment for schizophrenia, 340–341 Family visits in child mental health care, 449 Follow-up visits in antidepressant treatment, 294–295 Hospital readmission rate, 446–448 Informed consent for children’s medication treatment, 422–423 Informing consumers about healthcare-related rights, 412–413 Initiation of depression treatment, 298–299 Inpatient lithium level testing, 262–263 Inpatient rehabilitative therapy for depressed elderly, 302–303 Involuntary admissions for inpatient mental healthcare, 424–425 Long-acting benzodiazepine use in nursing homes, 426–427 Maintenance antipsychotic drug dosing for schizophrenia, 330–331 Maintenance antipsychotic drug duration for schizophrenia, 342–343 Maintenance pharmacotherapy for substance abuse, 380–381 Medication treatment of comorbid anxiety in schizophrenia, 346–347 Medication treatment of comorbid depression in schizophrenia, 348–349 Minor tranquilizer monotherapy, 428–429 Patient experience of alcohol counseling, 382–383 Patient participation in treatment planning, 430–431 Patient termination of treatment in depression, 304–305 Polypharmacy in elderly patients, 434–435 Polypharmacy in schizophrenia, 352–353 Program completion for chemical dependency treatment, 384–385 Psychotherapy treatment for schizophrenia, 354–355

Index of Measures by Domain of Quality

❚ 675

Rationale for outlier dosages for schizophrenia, 356–357 Retention rate for chemical dependency treatment, 374–375 Scheduled follow-up for antidepressant therapy, 306–307 Scheduled follow-up for minor tranquilizer therapy, 438–439 Sedating antidepressants in the elderly, 278–279 Side effect monitoring with mood stabilizers, 264–265 Somatic treatment for psychotic depression, 310–311 Somatic treatment for severe depression, 308–309 Staff attention to recovery potential, 440–441 Staff sensitivity to cultural/ethnic background, 442–443 Stimulant medication treatment for attention-deficit/hyperactivity disorder (ADHD), 258–259 Subtherapeutic antipsychotic dosages for schizophrenia, 332–333 Supported employment for individuals with severe and persistent mental illness (SPMI), 390–391 Supported housing for individuals with severe and persistent mental illness (SPMI), 392–393 Treatment of akathisia and extrapyramidal symptoms (EPS) in schizophrenia, 360–361 Treatment changes for nonresponsive depression, 312–313 Treatment of drug-related extrapyramidal symptoms (EPS) in schizophrenia, 362–363 Treatment initiation for individuals with depressive symptoms, 318–319 Treatment for mild depression, 314–315 Treatment for moderate depression, 316–317 Treatment plans for antidepressant use, 320–321 Treatment plans for minor tranquilizer use, 444–445 Treatment of residual symptoms in schizophrenia, 364–365 Treatment of tardive dyskinesia (TD) in schizophrenia, 366–367 Untreated depression in nursing homes, 322–323 Use of assertive community treatment (ACT) programs for individuals with severe and persistent mental illness (SPMI), 396–397 Use of atypical antipsychotic drugs for schizophrenia, 368–369 Use of atypical antipsychotic drugs for severe and persistent mental illness (SPMI), 394–395 Use of atypical antipsychotics for schizophrenia, 370–371 Use of mood stabilizers for bipolar disorder, 266–267 Use of psychotherapy for borderline personality disorder (BPD), 388–389 Visit frequency for depression treatment (four visits), 324–325 Vocational rehabilitation for schizophrenia, 372–373

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Index of Measures by Diagnosis All page numbers refer to tables in Chapters 7–13.

Anxiety disorders Days to follow-up care within 6 months of discharge for posttraumatic stress disorder (PTSD), 498–499 Follow-up care for co-occurring posttraumatic stress disorder (PTSD)and substance abuse, 502–503 Follow-up care within 6 months of discharge for posttraumatic stress disorder (PTSD), 504–505 Medication treatment of comorbid anxiety in schizophrenia, 346–347 Attention-deficit/hyperactivity disorder (ADHD) Family involvement in attention-deficit/hyperactivity disorder (ADHD), 256–257 Stimulant medication treatment for attention-deficit/hyperactivity disorder (ADHD), 258–259 Treatment engagement of children with attention-deficit/hyperactivity disorder (ADHD), 520–521 Bipolar disorder Blood level monitoring with mood stabilizers, 260–261 Inpatient lithium level testing, 262–263 Side effect monitoring with mood stabilizers, 264–265 Use of mood stabilizers for bipolar disorder, 266–267 Depression Access to child specialty care for depression, 158–159 Adequacy of antidepressant dosage, 270–271 Adequacy of antidepressant dosage for depressed elderly, 268–269 Adequacy of antidepressant dosing and duration, 272–273 Adequacy of antidepressant drug dosing, 274–275 Antidepressant initiation shortly before discharge, 276–277 Antidepressant medication management: effective acute-phase treatment, 286–287

677

678

❚

IMPROVING MENTAL HEALTHCARE

Depression (continued) Antidepressant medication management: effective continuation-phase treatment, 292–293 Antidepressant medication management: optimal practitioner contacts, 296–297 Assessment of psychiatric history in treating depression, 214–215 Assessment of psychosis in depression treatment, 216–217 Assessment of suicide status and risk in depression, 220–221 Continuation of depression treatment, 280–281 Depressed elderly patients discharged on antidepressants, 282–283 Depression counseling at index visit, 284–285 Doctor visits in inpatient care for depression, 300–301 Duration of drug treatment for acute depression (first refill), 288–289 Duration of drug treatment for continuation-phase depression (three prescriptions), 290–291 Examination of cognitive functioning for depression treatment, 238–239 Follow-up assessment of depression, 222–223 Follow-up visits in antidepressant treatment, 294–295 Heart sound examination for depressed inpatients, 240–241 Initiation of depression treatment, 298–299 Inpatient rehabilitative therapy for depressed elderly, 302–303 Medication treatment of comorbid depression in schizophrenia, 348–349 Neurological examination in depression treatment, 244–245 Patient termination of treatment in depression, 304–305 Scheduled follow-up for antidepressant therapy, 306–307 Sedating antidepressants in the elderly, 278–279 Somatic treatment for psychotic depression, 310–311 Somatic treatment for severe depression, 308–309 Treatment changes for nonresponsive depression, 312–313 Treatment engagement of individuals with depression, 524–525 Treatment initiation for individuals with depressive symptoms, 318–319 Treatment for mild depression, 314–315 Treatment for moderate depression, 316–317 Treatment plans for antidepressant use, 320–321 Untreated depression in nursing homes, 322–323 Visit frequency for depression treatment (four visits), 324–325 Dual diagnosis Care planning for dual diagnosis, 480–481 Case management for dual diagnosis, 452–453 Continuity of care for dual diagnoses, 554–555 Referrals for substance abuse treatment for the dually diagnosed, 482–483 Schizophrenia and other psychotic disorders Antidepressant dosages for depression with schizophrenia, 326–327 Antipsychotic drug dosing for inpatients with schizophrenia, 328–329

Index of Measures by Diagnosis

❚ 679

Antipsychotic drug use for inpatients with schizophrenia, 334–335 Antipsychotic treatment for childhood psychosis, 386–387 Assertive community treatment (ACT) program utilization for individuals with schizophrenia, 350–351 Assignment of primary care physician to individuals with schizophrenia, 472–473 Availability of medication management and psychotherapy for patients with schizophrenia, 358–359 Case management use for disabling schizophrenia, 462–463 Change of primary therapist for schizophrenia, 540 Depot antipsychotic medication for schizophrenia, 336–337 Educating individuals with schizophrenia about medications, 344–345 Family involvement in schizophrenia treatment, 338–339 Family treatment for schizophrenia, 340–341 Housing assessment for individuals with schizophrenia, 246–247 Independent living skills assessment for individuals with schizophrenia, 247 Intensity of aftercare for schizophrenia, 528–529 Maintenance antipsychotic drug dosing for schizophrenia, 330–331 Maintenance antipsychotic drug duration for schizophrenia, 342–343 Medication treatment of comorbid anxiety in schizophrenia, 346–347 Medication treatment of comorbid depression in schizophrenia, 348–349 Polypharmacy in schizophrenia, 352–353 Psychotherapy treatment for schizophrenia, 354–355 Rationale for outlier dosages for schizophrenia, 356–357 Relapse monitoring plan for stable-phase schizophrenia, 147 Substance abuse assessment in schizophrenia, 230–231 Subtherapeutic antipsychotic dosages for schizophrenia, 332–333 Termination of treatment for schizophrenia, 546–547 Treatment of akathisia and extrapyramidal symptoms (EPS) in schizophrenia, 360–361 Treatment of drug-related extrapyramidal symptoms (EPS) in schizophrenia, 362–363 Treatment engagement of individuals with schizophrenia, 526–527 Treatment of residual symptoms in schizophrenia, 364–365 Treatment of tardive dyskinesia in schizophrenia, 366–367 Use of atypical antipsychotic drugs for schizophrenia, 368–369 Use of atypical antipsychotics for schizophrenia, 370–371 Vocational rehabilitation for schizophrenia, 372–373 Substance use disorders 14-Day follow-up after initiating substance-related treatment, 510–511 60-Day continuation of substance abuse treatment, 548–549 Completion of treatment for substance abuse, 376–377 Continuation after substance-related treatment initiation, 562–563 Family involvement in substance abuse treatment, 378–379

680

❚

IMPROVING MENTAL HEALTHCARE

Substance use disorders (continued) Follow-up care for co-occurring posttraumatic stress disorder (PTSD) and substance abuse, 502–503 Maintenance pharmacotherapy for substance abuse, 380–381 Multiple outpatient visits after substance-related hospitalization, 514–515 Outpatient follow-up after first substance abuse visit, 536–537 Outpatient follow-up after initial substance-related visit (two or more visits), 534–535 Outpatient visit within 3 days of discharge (substance abuse), 516–517 Patient experience of alcohol counseling, 382–383 Program completion for chemical dependency treatment, 384–385 Rate of appeals and denials for substance abuse treatment, 203 Referral to post-detoxification services, 478–479 Retention rate for chemical dependency treatment, 374–375 Substance abuse maintenance treatment, 564–565 Substance abuse treatment after detoxification, 566–567 Other disorders Case management of medical comorbidity, 454–455 Supported employment for individuals with severe and persistent mental illness (SPMI), 390–391 Supported housing for individuals with severe and persistent mental illness (SPMI), 392–393 Use of assertive community treatment (ACT) program for individuals with SPMI, 396–397 Use of atypical antipsychotic drugs for severe and persistent mental illness (SPMI), 368–369 Use of psychotherapy for borderline personality disorder (BPD), 388–389

Index of Measures by Treatment Modality All page numbers refer to tables in Chapters 7–13.

Assertive community treatment Assertive community treatment (ACT) program utilization for individuals with schizophrenia, 350–351 Use of assertive community treatment (ACT) program for individuals with severe and persistent mental illness (SPMI), 396–397 Case management Case management for dual diagnosis, 252–253 Case management of medical comorbidity, 454–455 Case management use for disabling schizophrenia, 462–463 Case manager involvement in discharge planning, 456–457 Consumer assessments of case management, 458–459 Inpatient enrollment in case management, 460–461 Waiting time for case management services (mental retardation), 186–187 Waiting time for child case management services, 188–189 Electroconvulsive therapy Somatic treatment for psychotic depression, 310–311 Somatic treatment for severe depression, 308–309 Medical care Annual physical exam for persons with mental illness, 232–233 Assessment for medical problems of psychiatric patients, 234–235 Assignment of primary care physician to individuals with schizophrenia, 472–473 Diagnostic evaluation of new cognitive impairment, 236–237 Examination of cognitive functioning for depression treatment, 238–239 Heart sound examination for depressed inpatients, 240–241 Medical transfer within 72 hours of admission, 243 Neurological examination in depression treatment, 244–245 Use of primary care by individuals with mental illness, 470–471

681

682

❚

IMPROVING MENTAL HEALTHCARE

Medication Access to medication management by a psychiatrist, 160 Adequacy of antidepressant dosage, 270–271 Adequacy of antidepressant dosage for depressed elderly, 268–269 Adequacy of antidepressant dosing and duration, 272–273 Adequacy of antidepressant drug dosing, 274–275 Antidepressant dosages for depression with schizophrenia, 326–327 Antidepressant initiation shortly before discharge, 276–277 Antidepressant medication management: affective acute-phase treatment, 286–287 Antidepressant medication management: effective continuation-phase treatment, 292–293 Antidepressant medication management: optimal practitioner contacts, 296–297 Antipsychotic drug dosing for inpatients with schizophrenia, 328–329 Antipsychotic drug dosing in nursing homes, 398–399 Antipsychotic drug use for inpatients with schizophrenia, 334–335 Antipsychotic treatment for childhood psychosis, 386–387 Antipsychotic use for nonpsychotic conditions, 400–401 Antipsychotic use in nursing homes, 402–403 Attendance at initial medication appointment, 550–551 Attendance at rescheduled medication appointments, 552–553 Availability of medication management and psychotherapy for patients with schizophrenia, 358–359 Benzodiazepine use in nursing homes, 436–437 Blood level monitoring with mood stabilizers, 260–261 Correct medication administration in child residential programs, 632–633 Delayed medication doses in child residential programs, 634–635 Depot antipsychotic medication for schizophrenia, 336–337 Depressed elderly patients discharged on antidepressants, 282–283 Documentation of current medications at assessment, 242 Duration of daily minor tranquilizer use, 420–421 Duration of drug treatment for acute depression (first refill), 288–289 Duration of drug treatment for continuation-phase depression (three prescriptions), 290–291 Educating individuals with schizophrenia about medications, 344–345 Follow-up contact in antidepressant treatment, 508–509 Follow-up for medication management post-discharge, 506–507 Follow-up visits in antidepressant treatment, 294–295 Informed consent for children’s medication treatment, 422–423 Informing primary care clinicians of psychiatric medications, 468–469 Inpatient lithium level testing, 262–263 Long-acting benzodiazepine use in nursing homes, 426–427 Maintenance antipsychotic drug dosing for schizophrenia, 330–331 Maintenance antipsychotic drug duration for schizophrenia, 342–343 Medication errors in child residential programs, 638–639 Medication errors of commission, omission and incorrect dosing, 636–637

Index of Measures by Treatment Modality

❚ 683

Medication errors per inpatient, 640–641 Medication treatment of comorbid anxiety in schizophrenia, 346–347 Medication treatment of comorbid depression in schizophrenia, 348–349 Medication visit attended 14-days after hospital discharge, 512–513 Minor tranquilizer monotherapy, 428–429 Missed medication doses in child residential programs, 642–643 Polypharmacy in elderly patients, 434–435 Polypharmacy in schizophrenia, 352–353 Rationale for outlier dosages for schizophrenia, 356–357 Scheduled follow-up for antidepressant therapy, 306–307 Scheduled follow-up for minor tranquilizer therapy, 438–439 Sedating antidepressants in the elderly, 278–279 Side effect monitoring with mood stabilizers, 264–265 Somatic treatment for psychotic depression, 310–311 Somatic treatment for severe depression, 308–309 Stimulant medication treatment for attention-deficit/hyperactivity disorder (ADHD), 258–259 Subtherapeutic antipsychotic dosages for schizophrenia, 332–333 Tardive dyskinesia assessment with antipsychotic use, 224–225 Treatment of akathisia and extrapyramidal symptoms (EPS) in schizophrenia, 360–361 Treatment of drug-related extrapyramidal symptoms (EPS) in schizophrenia, 362–363 Treatment for mild depression, 314–315 Treatment for moderate depression, 316–317 Treatment plans for antidepressant use, 320–321 Treatment plans for minor tranquilizer use, 444–445 Treatment of residual symptoms in schizophrenia, 364–365 Treatment of tardive dyskinesia in schizophrenia, 366–367 Use of atypical antipsychotic drugs for schizophrenia, 368–369 Use of atypical antipsychotic drugs for severe and persistent mental illness (SPMI), 394–395 Use of atypical antipsychotics for schizophrenia, 370–371 Use of mood stabilizers for bipolar disorder, 266–267 Psychotherapy and other psychosocial treatments Assessment for psychosocial issues of psychiatric patients, 249 Comprehensiveness of inpatient psychosocial assessments, 250–251 Depression counseling at index visit, 284–285 Family involvement in attention-deficit/hyperactivity disorder (ADHD), 256–257 Family involvement in schizophrenia treatment, 338–339 Family treatment for schizophrenia, 340–341 Family visits in child mental healthcare, 449 Housing assessment for individuals with schizophrenia, 246–247 Independent living skills assessment for individuals with schizophrenia, 248

684

❚

IMPROVING MENTAL HEALTHCARE

Psychotherapy other psychosocial treatments (continued) Psychotherapy treatment for schizophrenia, 354–355 Supported employment for individuals with severe and persistent mental illness (SPMI), 390–391 Supported housing for individuals with severe and persistent mental illness (SPMI), 392–393 Timely inpatient contact with family, 484–485 Timely inpatient psychosocial assessment, 252–253 Timely psychosocial screening, 154–155 Treatment for mild depression, 314–315 Treatment for moderate depression, 316–317 Use of psychotherapy for borderline personality disorder (BPD), 388–389 Vocational rehabilitation for schizophrenia, 372–373 Substance abuse treatment 14-Day follow-up after initiating substance-related treatment, 510–511 60-Day continuation of substance abuse treatment, 548–549 Access to substance abuse treatment, 162–163 Access to substance abuse treatment for pregnant women, 164–165 Assessment for substance abuse problems of psychiatric patients, 226–227 Availability of alcohol counseling and education, 144–145 Chemical dependency utilization: percentage of members receiving inpatient, day/night care, and ambulatory services, 176–177 Completion of treatment for substance abuse, 376–377 Continuation after substance-related treatment initiation, 562–563 Family involvement in substance abuse treatment, 378–379 Maintenance pharmacotherapy for substance abuse, 380–381 Multiple outpatient visits after substance-related hospitalization, 514–515 Outpatient follow-up after first substance abuse visit, 536–537 Outpatient follow-up after initial substance-related visit (two or more visits), 534–535 Outpatient visit within 3 days of discharge (substance abuse), 516–517 Patient experience of alcohol counseling, 382–383 Program completion for chemical dependency treatment, 384–385 Rate of appeals and denials for substance abuse treatment, 203 Referral to post-detoxification services, 478–479 Retention rate for chemical dependency treatment, 374–375 Screening for alcohol abuse in primary care, 228–229 Substance abuse assessment in schizophrenia, 230–231 Substance abuse detection, 150–151 Substance abuse education in primary care, 152–153 Substance abuse maintenance treatment, 564–565 Substance abuse treatment after detoxification, 566–567 Other treatment modalities Access to child specialty care for depression, 158–159

Index of Measures by Treatment Modality Access to psychological testing, 161 Consumer participation in preventive services, 146 Continuation of depression treatment, 280–281 Continuity of outpatient rehabilitation visits, 556–557 Hospital readmission rate, 446–448 Initiation of depression treatment, 298–299 Inpatient rehabilitative therapy for depressed elderly, 302–303 Somatic treatment for psychotic depression, 310–311 Somatic treatment for severe depression, 308–309 Treatment for mild depression, 314–315 Treatment for moderate depression, 316–317

❚ 685

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Index of Measures by Population Characteristics All page numbers refer to tables in Chapters 7–13.

Children and adolescents Access to child specialty care for depression, 158–159 Antipsychotic treatment for childhood psychosis, 386–387 Correct medication administration in child residential programs, 632–633 Delayed medication doses in child residential programs, 634–635 Duration of restraint in a child residential program, 574–575 Duration of seclusion in a child pesidential program, 600–601 Family visits in child mental healthcare, 449 Informed consent for children’s medication treatment, 422–423 Medication errors in child residential programs, 638–639 Missed medication doses in child residential programs, 642–643 Patient days with physical assaults among adolescent inpatients, 614–615 Patient days with self-injuries among adolescent inpatients, 616–617 Patient injury during child/adolescent restraint, 618–619 Physical management of children in residential programs, 578–579 Planned discharge from child residential programs, 560–561 Seclusion events per day in a child residential program, 612–613 Staff injury during child/adolescent restraint, 630–631 Therapeutic holds in child residential programs, 592–593 Treatment engagement of children with attention-deficit/hyperactivity disorder (ADHD), 520–521 Elderly patients Adequacy of antidepressant dosage for depressed elderly, 268–269 Antipsychotic drug dosing in nursing homes, 398–399 Antipsychotic use in nursing homes, 402–403 Benzodiazepine use in nursing homes, 437–438 Depressed elderly patients discharged on antidepressants, 282–283

687

688

❚

IMPROVING MENTAL HEALTHCARE

Elderly patients (continued) Inpatient rehabilitative therapy for depressed elderly, 302–303 Long-acting benzodiazepine use in nursing homes, 426–427 Physical restraint use in nursing homes, 580–581 Polypharmacy in elderly patients, 434–435 Sedating antidepressants in the elderly, 278–279 Untreated depression in nursing homes, 322–333 Racial/ethnic minorities Cultural appropriateness of mental health services, 414–415 Staff attention to recovery potential, 440–441 Staff sensitivity to cultural/ethnic background, 442–443 Treatment engagement of consumers by race/ethnicity, 522–523

Index of Measures by Data Source All page numbers refer to tables in Chapters 7–13.

Administrative data 14-Day follow-up after initiating substance-related treatment, 510–511 60-Day continuation of substance abuse treatment, 548–549 Ambulatory follow-up after emergency visit, 492–493 Attendance at rescheduled medication appointments, 552–553 Availability of medication management and psychotherapy for patients with schizophrenia, 358–359 Average length of inpatient stay prior to readmission, 404–405 Change in primary mental health provider, 538–539 Chemical dependency utilization: percentage of members receiving inpatient, day/night care, and ambulatory services, 176–177 Community tenure, 406–407 Continuation after substance-related treatment initiation, 562–563 Continuity of care for dual diagnoses, 554–555 Continuity of outpatient visits post-discharge, 558–559 Days to first aftercare visit, 496–497 Days to follow-up care within 6 months of discharge for posttraumatic stress disorder (PTSD), 498–499 Employee assistance program (EAP) referrals for mental health and substance abuse, 170–171 Family visits in child mental healthcare, 449 Follow-up after hospitalization for mental illness, 490–491 Follow-up care for co-occurring posttraumatic stress disorder (PTSD) and substance abuse, 502–503 Follow-up care within 6 months of discharge for posttraumatic stress disorder (PTSD), 504–505 Hospital readmission rate, 446–448 Intensity of aftercare for schizophrenia, 528–529 Intensity of aftercare within 180 days of discharge (psychiatric/substance abuse), 530–531

689

690

❚

IMPROVING MENTAL HEALTHCARE

Administrative data (continued) Intensity of post-discharge ambulatory care (psychiatric), 532–533 Medical transfer within 72 hours of admission, 243 Medication visit attended 14 days after hospital discharge, 512–513 Mental health utilization: percentage of members receiving inpatient, day/night care, and ambulatory services, 174–175 Multiple outpatient visits after substance-related hospitalization, 514–515 Outpatient follow-up after first substance abuse visit, 536–537 Outpatient follow-up after initial substance-related visit (two or more visits), 534–535 Outpatient visit within 3 days of discharge (substance abuse), 516–517 Review of mental health service denials, 206–207 Substance abuse detection, 150–151 Substance abuse treatment after detoxification, 566–567 Timeliness of ambulatory aftercare, 518–519 Treatment absence longer than 90 days, 541 Treatment engagement of children with attention-deficit/hyperactivity disorder (ADHD), 520–521 Treatment engagement of individuals with depression, 524–525 Treatment engagement of individuals with schizophrenia, 526–527 Upheld appeals of managed behavioral healthcare organization (MBHO) service denials, 208–209 Use of psychotherapy for borderline personality disorder (BPD), 388–389 Visit frequency for depression treatment (four visits), 324–325 Case management assignment/contact data Waiting time for case management services (mental retardation), 186–187 Waiting time for child case management services, 188–189 Case management enrollment data Inpatient enrollment in case management, 460–461 Clinician administered instrument Case management use for disabling schizophrenia, 462–463 Treatment of tardive dyskinesia (TD) in schizophrenia, 366–367 Clinician survey/instruments Depression counseling at index visit, 284–285 Discharge to less restrictive placement, 418–419 Clinician training/certification records Access to child specialty care for depression, 158–159 Laboratory data/results Blood level monitoring with mood stabilizers, 260–261

Index of Measures by Data Source

❚ 691

Diagnostic evaluation of new cognitive impairment, 236–237 Side effect monitoring with mood stabilizers, 264–265 Medical record Adequacy of antidepressant dosage for depressed elderly, 268–269 Adequacy of antidepressant dosage, 270–271 Adequacy of antidepressant dosing and duration, 272–273 Annual physical examination for persons with mental illness, 232–233 Antidepressant dosages for depression with schizophrenia, 326–327 Antidepressant dosages for depression with schizophrenia, 328–329 Antidepressant initiation shortly before discharge, 276–277 Antipsychotic drug use for inpatients with schizophrenia, 334–335 Antipsychotic treatment for childhood psychosis, 386–387 Assertive community treatment (ACT) program utilization for individuals with schizophrenia, 350–351 Assessment for medical problems of psychiatric patients, 234–235 Assessment for psychosocial issues of psychiatric patients, 249 Assessment for substance abuse problems of psychiatric patients, 226–227 Assessment of major depressive symptoms, 212–213 Assessment of psychiatric history in treating depression, 214–215 Assessment of psychosis in depression treatment, 216–217 Assessment of risk to self/others, 218–219 Assessment of suicide status and risk in depression, 220–221 Assignment of primary care physician to individuals with schizophrenia, 472–473 Care planning for dual diagnosis, 480–481 Case management use for disabling schizophrenia, 462–463 Case manager involvement in discharge planning, 456–457 Change of primary therapist for schizophrenia, 540 Communication between mental health and primary care, 464–465 Completion of treatment for substance abuse, 376–377 Comprehensiveness of inpatient psychosocial assessments, 250–251 Congruence of clinical visit with treatment plan goals, 432–433 Criteria for discharge documented at admission, 474–475 Current treatment plan for psychiatric outpatients, 416–417 Depot antipsychotic medication for schizophrenia, 336–337 Depressed elderly patients discharged on antidepressants, 282–283 Detailed communication between mental health and primary care for inpatients, 466–467 Diagnostic evaluation of new cognitive impairment, 236–237 Discharge to less restrictive placement, 418–419 Distribution of seclusion events by duration, 598–599 Doctor visits in inpatient care for depression, 300–301 Documentation of current medications at assessment, 242 Duration of daily minor tranquilizer use, 420–421

692

❚

IMPROVING MENTAL HEALTHCARE

Medical record (continued) Duration of drug treatment for continuation-phase depression (three prescriptions), 290–291 Duration of restraint in a child residential program, 574–575 Duration of seclusion in a child residential program, 600–601 Educating individuals with schizophrenia about medications, 334–335 Examination of cognitive functioning for depression treatment, 238–239 Family involvement in attention-deficit/ hyperactivity disorder (ADHD), 256–257 Family involvement in schizophrenia treatment, 338–339 Family treatment for schizophrenia, 340–341 Follow-up assessment of depression, 222–223 Follow-up contact in antidepressant treatment, 508–509 Frequency of restraints among inpatients, 576–577 Frequency of seclusion among inpatients, 602–603 Heart sound examination for depressed inpatients, 240–241 Housing assessment for individuals with schizophrenia, 246–247 Independent living skills assessment for individuals with schizophrenia, 248 Informed consent for children’s medication treatment, 422–423 Informing primary care clinicians of psychiatric medications, 468–469 Inpatient days in restraint, 570–571 Inpatient days in seclusion, 594–595 Inpatient enrollment in case management, 460–461 Inpatient lithium level testing, 262–263 Inpatient rehabilitative therapy for depressed elderly, 302–303 Inpatients restrained per patient day, 572–573 Inpatients secluded per patient day, 596–597 Involuntary admissions for inpatient mental healthcare, 424–425 Involuntary seclusions per discharge, 604–605 Involuntary seclusions per inpatient day, 606–607 Maintenance antipsychotic drug dosing for schizophrenia, 330–331 Maintenance antipsychotic drug duration for schizophrenia, 342–343 Medication treatment of comorbid anxiety in schizophrenia, 346–347 Medication treatment of comorbid depression in schizophrenia, 348–349 Neurological examination in depression treatment, 244–245 Patient days with physical assaults among adolescent inpatients, 614–615 Patient days with self-injuries among adolescent inpatients, 616–617 Patient injury during child/adolescent restraint, 618–619 Patient injury during restraint or seclusion, 620–621 Physical assaults per discharge among inpatients, 624–625 Physical assaults per inpatient day, 622–623 Physical management of children in residential programs, 578–579 Physical restraints per discharge, 584–585 Physical restraints per inpatient day, 582–583 Planned discharge from child residential programs, 560–561 Polypharmacy in schizophrenia, 352–353

Index of Measures by Data Source

❚ 693

Proportion of inpatient hours in restraint, 588–589 Proportion of inpatient hours in seclusion, 608–609 Proportion of inpatients in physical restraints, 590–591 Proportion of inpatients in seclusion, 610–611 Proportion of inpatients restrained, 586–587 Psychotherapy treatment for schizophrenia, 354–355 Rationale for outlier dosages for schizophrenia, 356–357 Referral to post-detoxification services, 478–479 Referral for substance abuse treatment among patients with positive assessment, 482–483 Scheduled follow-up for antidepressant therapy, 306–307 Scheduled follow-up for minor tranquilizer therapy, 438–439 Screening for depression, 148–149 Seclusion events per day in a child residential program, 612–613 Sedating antidepressants in the elderly, 278 Self-injuries per discharge among inpatients, 628–629 Self-injuries per inpatient day, 626–627 Somatic treatment for psychotic depression, 310–311 Somatic treatment for severe depression, 308–309 Staff injury during child/adolescent restraint, 630–631 Stimulant medication treatment for attention-deficit/hyperactivity disorder (ADHD), 258–259 Substance abuse assessment in schizophrenia, 230–231 Subtherapeutic antipsychotic dosages for schizophrenia, 332–333 Tardive dyskinesia assessment with antipsychotic use, 224–225 Termination of treatment for schizophrenia, 546–547 Therapeutic holds in child residential programs, 592–593 Timely inpatient contact with family, 484–485 Timely inpatient psychosocial assessment, 252–253 Timely psychosocial screening, 154–155 Treatment changes for nonresponsive depression, 312–313 Treatment for moderate depression, 316–317 Treatment of akathisia and extrapyramidal symptoms (EPS) in schizophrenia, 360–361 Treatment of drug-related extrapyramidal symptoms (EPS) in schizophrenia, 362–363 Treatment of residual symptoms in schizophrenia, 364–365 Treatment of tardive dyskinesia (TD) in schizophrenia, 366–367 Treatment plan for benefit termination, 486–487 Treatment plans for antidepressant use, 320–321 Treatment plans for minor tranquilizer use, 444–445 Unplanned departures from inpatient psychiatric care, 646 Vocational rehabilitation for schizophrenia, 372–373 Waiting time for child case management services, 188–189

694

❚

IMPROVING MENTAL HEALTHCARE

Minimal Data Set 2.0 Resident Assessment Instrument Antipsychotic use in nursing homes, 402–403 Benzodiazepine use in nursing homes, 436–437 Long-acting benzodiazepine use in nursing homes, 426–427 Physical restraint use in nursing homes, 580–581 Untreated depression in nursing homes, 322–323 Occurrence report Correct medication administration in child residential programs, 632–633 Delayed medication doses in child residential programs, 634–635 Distribution of seclusion events by duration, 598–599 Duration of restraint in a child residential program, 574–575 Duration of seclusion in a child residential program, 600–601 Frequency of restraints among inpatients, 576–577 Frequency of seclusion among inpatients, 602–603 Inpatient critical incident rates, 644–645 Inpatient days in restraint, 570–571 Inpatient days in seclusion, 594–595 Inpatients restrained per patient day, 572–573 Inpatients secluded per patient day, 596–597 Involuntary seclusions per discharge, 604–605 Involuntary seclusions per inpatient day, 606–607 Medication errors in child residential programs, 638–639 Medication errors of commission, omission, and incorrect dosing, 636–637 Medication errors per inpatient, 640–641 Missed medication doses in child residential programs, 642–643 Patient days with physical assaults among adolescent inpatients, 614–615 Patient days with self-injuries among adolescent inpatients, 616–617 Patient injury during child/adolescent restraint, 618–619 Patient injury during restraint or seclusion, 620–621 Physical assaults per discharge among inpatients, 624–625 Physical assaults per inpatient day, 622–623 Physical restraints per discharge, 584–585 Physical restraints per inpatient day, 582–583 Proportion of inpatient hours in restraint, 588–589 Proportion of inpatient hours in seclusion, 608–609 Proportion of inpatients in physical restraints, 590–591 Proportion of inpatients in seclusion, 610–611 Proportion of inpatients restrained, 586–587 Seclusion events per day in a child residential program, 612–613 Self-injuries per discharge among inpatients, 628–629 Self-injuries per inpatient day, 626–627 Staff injury during child/adolescent restraint, 630–631 Therapeutic holds in child residential programs, 592–593

Index of Measures by Data Source Patient contact/appointment data Access to medication management by a psychiatrist, 160 Access to substance abuse treatment for pregnant women, 164–165 Access to routine mental healthcare, 184–185 Attendance at first post-discharge appointment, 494–495 Attendance at initial medication appointment, 550–551 Continuity of outpatient rehabilitation visits, 556–557 Follow-up appointment offered after hospitalization, 500–501 Mental health appointment no-show rate, 544–545 Provider contact after missed appointment, 476–477 Response time for crisis intervention teams, 178–179 Scheduled follow-up for antidepressant therapy, 306–307 Scheduled follow-up for minor tranquilizer therapy, 438–439 Urgent mental healthcare offered within 48 hours, 180–181 Urgent mental healthcare received within 24 hours, 182–183 Waiting time for mental health services, 190–191 Patient survey/assessment Access to appeal procedures, 204–205 Access to substance abuse treatment, 162–163 Availability of alcohol counseling and education, 144–145 Case management for dual diagnosis, 452–453 Case management of medical comorbidity, 454–455 Clinician response to phone contact, 192–193 Consumer assessments of case management, 458–459 Consumer participation in preventive services, 146 Consumer participation in treatment decisions, 408–409 Consumer perception of coercion in treatment choices, 410–411 Convenience of appointment times, 166–167 Convenience of location of services, 168–169 Cultural appropriateness of mental health services, 414–415 Depot antipsychotic medication for schizophrenia, 336–337 Depression counseling at index visit, 284–285 Family involvement in schizophrenia treatment, 338–339 Family involvement in substance abuse treatment, 378–379 Family treatment for schizophrenia, 340–341 Financial barriers to care, 172–173 Incomplete referrals for mental health services, 542–543 Informing consumers about healthcare-related rights, 412–413 Initiation of depression treatment, 298–299 Medication treatment of comorbid anxiety in schizophrenia, 346–347 Medication treatment of comorbid depression in schizophrenia, 348–349 Patient experience of alcohol counseling, 382–383 Patient participation in treatment planning, 430–431 Patient termination of treatment in depression, 304–305

❚ 695

696

❚

IMPROVING MENTAL HEALTHCARE

Patient survey/assessment (continued) Screening for alcohol abuse in primary care, 228–229 Staff attention to recovery potential, 440–441 Staff sensitivity to cultural/ethnic background, 442–443 Substance abuse education in primary care, 152–153 Substance abuse maintenance treatment, 564–565 Treatment initiation for individuals with depressive symptoms, 318–319 Treatment of akathisia and extrapyramidal symptoms (EPS) in schizophrenia, 360–361 Treatment of drug-related extrapyramidal symptoms (EPS) in schizophrenia, 362–363 Treatment of residual symptoms in schizophrenia, 364–365 Treatment of tardive dyskinesia (TD) in schizophrenia, 366–367 Use of primary care by individuals with mental illness, 470–471 Vocational rehabilitation for schizophrenia, 372–373 Pharmacy data Program enrollment data Adequacy of antidepressant dosage, 270–271 Adequacy of antidepressant dosing and duration, 272–273 Adequacy of antidepressant drug dosing, 274–275 Antidepressant medication management: effective acute-phase treatment, 286–287 Antidepressant medication management: effective continuation-phase treatment, 292–293 Antidepressant medication management: optimal practitioner contacts, 296–297 Antipsychotic drug dosing in nursing homes, 398–399 Antipsychotic treatment for childhood psychosis, 386–387 Antipsychotic use for nonpsychotic conditions, 400–401 Blood level monitoring with mood stabilizers, 260–261 Case manager involvement in discharge planning, 456–457 Continuation of depression treatment, 280–281 Correct medication administration in child residential programs, 632–633 Delayed medication doses in child residential programs, 634–635 Duration of drug treatment for acute depression (first refill), 288–289 Duration of drug treatment for continuation-phase depression (three prescriptions), 290–291 Follow-up contact in antidepressant treatment, 508–509 Follow-up for medication management post-discharge, 506–507 Follow-up visits in antidepressant treatment, 294–295 Informing primary care clinicians of psychiatric medications, 468–469 Inpatient lithium level testing, 262–263 Maintenance pharmacotherapy for substance abuse, 380–381 Medication errors in child residential programs, 638–639 Medication errors of commission, omission, and incorrect dosing, 636–637 Minor tranquilizer monotherapy, 428–429 Missed medication doses in child residential programs, 642–643

Index of Measures by Data Source

❚ 697

Polypharmacy in elderly patients, 434–435 Rationale for outlier dosages for schizophrenia, 356–357 Scheduled follow-up for antidepressant therapy, 306–307 Scheduled follow-up for minor tranquilizer therapy, 438–439 Side effect monitoring with mood stabilizers, 264–265 Supported employment for individuals with severe and persistent mental illness (SPMI), 390–391 Supported housing for individuals with severe and persistent mental illness (SPMI), 392–393 Treatment engagement of consumers by race/ethnicity, 522–523 Treatment for mild depression, 314–315 Treatment initiation for individuals with depressive symptoms, 318–319 Treatment plans for antidepressant use, 320–321 Use of assertive community treatment (ACT) programs for individuals with severe and persistent mental illness (SPMI), 396–397 Use of atypical antipsychotic drugs for schizophrenia, 368–369 Use of atypical antipsychotic drugs for severe and persistent mental illness (SPMI), 394–395 Use of atypical antipsychotics for schizophrenia, 370–371 Use of mood stabilizers for bipolar disorder, 266–267 Proprietary data system Completion of treatment for substance abuse, 376–377 Program completion for chemical dependency treatment, 384–385 Referral to post-detoxification services, 478–479 Retention rate for chemical dependency treatment, 374–375 Utilization Management Data Emergent phone access to managed behavioral healthcare organization (MBHO) clinicians, 194–195 Managed behavioral healthcare organization (MBHO) rate of live response, 196–197 Rapidity of managed behavioral healthcare organization (MBHO) call answering, 198–199 Timeliness of utilization management response, 202–203 Unanswered utilization review calls, 200–201