openEHR a primer

openEHR a primer Thomas Beale Utrecht 2007

Introductions Thomas Beale  Chief Technology Officer Ocean Informatics (Aus, UK)  Senior Researcher, Centre for Health Informatics, UCL (UK)  Chair ARB openEHR Foundation  5 years’ int’l standards work  20 years’ in software engineering  13 years working with clinical people © Ocean Informatics 2007

What is openEHR Today?

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1992

Good European Health Record: requirements and EHR architecture

EHCR SupA: revised requirements and architecture

Good Electronic Health Record

Synapses: FHR and Clinical Object Dictionary

Formal Archetype approach

Medicate: remote asthma monitoring and alerts

GPGC projects (1) EHR kernel services (2) legacy data transformation (3) diabetes extraction and merge

6WINIT: wireless IPv6

mNET: wireless demonstrator

SynEx: middleware component architecture

2004

Release 1 Feb 2006

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Release 1.0.1 15 Apr 2007

The openEHR Foundation 

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Non-profit organisation based at University College, London (UCL) Established by UCL and Ocean nformatics in 2000 to own the IP 800+ Members from 71 countries All specifications & schemas publicly available Software open source (GPL, LGPL, MPL)

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openEHR Deliverables Health Integration Platform

Health Information Platform

EQL

Archetypes Reference Model

TOM

(data types, … secure EHR)

AOM

ADL

Application Development Platform

Knowledge Management Platform © Ocean Informatics 2007

Activities openEHR Board Technical

Clinical

Architecture Review Board

Project Group

Clinical Review Board

Project Group

Project Group Project Group

Project Group Project Group

Computing architecture specification & implementations

Computable Single-source domain content and process models

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History of openEHR Sep 2001 Specification development starts Feb 2003 Formal Change Request system 

…196 CRs…initial schemas, implementations

10 Feb 2006 Release 1.0  

…51 CRs…heavy testing… Implementation in Java, C#, XML-schema…

15 Apr 2007 Release 1.0.1 

Stabilised; 4 Archetype parsers; 5+ implementations emerging, some commercial

ADL spec  CEN EN13606-2  ISO © Ocean Informatics 2007

What is openEHR for?

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Challenges in e-Health Today Semantic interoperability: how do computers know what our data mean?

Patient-centric view: how to build a patientcentric longitudinal EHR across enterprises? 

For decision support, Care pathways, Medical research

Continual change and complexity: how to build systems that keep up with reality? © Ocean Informatics 2007

Semantic Interoperability An e-health environment needs to establish common meaning of data everywhere It’s no use knowing what the meaning is in one place; it must be known from data capture to all uses, and all the plumbing in between… We need end-to-end semantic coherence Meaning = structure + context + semantics

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… within systems… User i/f Application Logic Middleware & Business Logic

Persistence © Ocean Informatics 2007

…and the distributed environment LSP NW&WM

LSP NE

LSP Eastern

Spine

LSP Southern

LSP London •Record location •Record update •Cache •Authorisation

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…at various levels… LSP NW&WM

LSP NE

LSP Eastern

LSP London Whittington Shared EHR Hospitals LSP Southern

Royal Marsden

Mental health Lawson Practice

General practice

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…as well as across functions…. local hospital

social workers

large hospital

aged care

Knowledge Discovery Care Pathways

home

specialist

imaging lab

Decision Support

GP

nursing

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path lab

Patient-centric View – what happens ACTION start

Patient

GP

ORDER celebrex

ACTION start ACTION  dose

ACTION resume

ACTION  freq

ORDER ACE inhib

Specialist

Hospital

ORDER Cor bypass

ACTION schedule ADMIN admission

ACTION suspend

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ACTION perform

ADMIN discharge

Patient-centric View – what we need ACTION Start (patient) ORDER Celebrex (GP)

ACTION Start (patient) ACTION  dose (GP)

ORDER ACE inhib (GP)

ORDER Cor bypass (specialist)

ACTION Resume (GP) ACTION  freq (GP)

ACTION Schedule (specialist) ADMIN ACTION ACTION Admission Suspend Perform (hospital) (hospital) (hospital)

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ADMIN Discharge (hospital)

Change and Complexity 

Snomed-ct has 500,000 concepts & 1,000,000 relationships….and is under

continual heavy revision    

ICD10 has 75,000 conditions… and ICD11 is on the way… There are no standards for questions on most hospital forms There are 500 common lab tests, many changing, new ones emerging Hospital business processes changing… © Ocean Informatics 2007

Information complexity: timing Dose frequency

Examples

every time period

…every 4 hours

n times per time period

…three times per day

n per time period

…2 per day …6 per week

every time period range

…every 4-6 hours, …2-3 times per day

Maximum interval

…not less than every 8 hours

Maximum per time period

…to a maximum of 4 times per day

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Information complexity: timing Time specific

Examples

Morning and/or lunch and/or evening

…take after breakfast and lunch

Specific times of day

06:00, 12:00, 20:00

Dose duration Time period

…via a syringe driver over 4 hours

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Information complexity: timing Event related

Examples

After/Before event

…after meals …before lying down …after each loose stool …after each nappy change

n time period before/after

…3 days before travel

event Duration n time period before/after event

…on days 5-10 after menstruation begins

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Information complexity: timing Treatment duration Examples Date/time to date/time

1-7 January 2005

Now and then repeat after n time period/s

…stat, repeat in 14 days

n time period/s

…for 5 days

n doses

…Take every 2 hours for 5 doses

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Information complexity: timing Triggers/Outcomes Examples If condition is true

…if pulse is greater than 80 …until bleeding stops

Start event

…Start 3 days before travel

Finish event

…Apply daily until day 21 of menstrual cycle

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openEHR Health Computing Platform

Health Integration Platform

Health Information Platform Application Development Platform

Knowledge Management Platform Knowledge Discovery

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openEHR Health Information Platform

Data Entry & validation

Health Integration Archetypes Platform

EQL

Reference Health Information Platform Model

Application AOM Development Platform

TOM

Knowledge

ADL Management Platform

Data Retrieval

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Data Viewing

Key Innovations “Two-level Modelling” – separation of models of information into 2 layers: 

 

Hard-coded information model (domaininvariant) Archetypes (domain-specific) Software is only built from the first layer

Scientific process model of basic information Distributed Semantics

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The Reference Model

Archetypes Reference Model

EQL AOM

ADL

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TOM

Reference Model virtual EHR SM

{

terminology service

{ {

domain

{

RM patterns

core

demographic service

EHR service

archetype service

EHR Extract EHR

Demographic Integration Composition

Security

Template OM openEHR Archetype Profile

Common

?

Archetype OM

Data Structures Data Types

CDA Rel 2 EN13606 Support (identifiers, terminology access)

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}

AM

Analytical Paradigm for clinical recording observations goals evaluation (desired observations) interventions

patient system

clinical investigator system administrative context

a) problem-solving metaphor

goals +



(desired observations)

interventions

f()

evaluation

patient system

-

observations clinical investigator system administrative context

b) control system metaphor © Ocean Informatics 2007

Entry types based on process measurable or observable Published evidence base Personal knowledge base

clinically interpreted findings

Observations

Investigator system

1 Patient system

4 Actions

2 Evaluation - assessment - opinion - goals

Define intervention

3

Instructions © Ocean Informatics 2007

recording clinical activities Investigator agents

Ontology of Entry data

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Core clinical Entry semantics

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Standard state machine

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Security Features

Separation

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Distributed versioning EHR System A (cache)

v3

v1

EHR Centre 2

v2

v1

EHR Centre 1 EHR System A (cache)

v1

v3

v2

v1

v1

v3

v3

v2

v2

EHR System C (cache)

Logical EHR © Ocean Informatics 2007

v3

v2

Archetypes

Archetypes Reference Model

EQL AOM

ADL

© Ocean Informatics 2007

TOM

Principle The components of the Reference Model are like LEGO brick specifications Archetypes = instructions/designs constraining the use of LEGO pieces to create meaningful structures Information model Instances

Archetype A

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Archetype B

Language (ADL)

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© Ocean Informatics 2007

© Ocean Informatics 2007

© Ocean Informatics 2007

© Ocean Informatics 2007

© Ocean Informatics 2007

Queries

Archetypes Reference Model

EQL AOM

ADL

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TOM

Queries from Archetypes

Archetype-path Based Queries

openEHR EHR

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EHR Query Language (EQL) SELECT o/data[at0001]/events[at0002]/time, o/data[at0001]/events[at0002]/data[at0003]/items [at0013.1]/value FROM Ehr[uid=@EhrUid] CONTAINS Composition c[openEHR-EHR-COMPOSITION.encounter.v1] CONTAINS Observation o[openEHR-EHROBSERVATION.laboratory-lipids.v1]

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Archetype-based Queries We can now write portable queries in terms of semantic elements rather than only in terms of underlying information model Queries can be built by domain users, not IT people

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Templates

Archetypes Reference Model

EQL AOM

ADL

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TOM

Archetypes and Templates Diabetic checkup Tingling feet Feeling tired

Archetypes FH Weight

Antenatal visit Back pain 66 kg

76 kg BP

102/64 mmHg

124/92 HbA1c

142/min

7.5% Issues

NAD, see 4/52

Excellent control Assess Template

Template

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© Ocean Informatics 2007

Archetypes are semantic single-source models

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The openEHR EHR

Archetypes Templates Queries

Comprehensive Entry model LINKing openEHR Distributed Versioning EHR & Actions State model of Instruction Archetype-based Querying Formal Terminology integration openPGP digital signing

Virtual EHR web service

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A Universal EHR

CDAr2 (text)

Integration Archetypes

CDAr2 (struct)

Clinical Archetypes

mappings

Clinical Archetypes

openEHR EHR Clinical Archetypes © Ocean Informatics 2007

CDAr2 (copied) CDAr2 (generated)

Conclusions 

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Methodology of 2-level modelling works; 3 years experience; now in use in NHS Archetypes and templates provide control over data entry, persistence, querying and terminology binding For the first time, clinical professionals can substantially define the semantics of their own information systems: archetypes, templates and queries © Ocean Informatics 2007

Questions www.OceanInformatics.biz

www.openEHR.org

Release 1.0.1 – 15 April 2007 © Ocean Informatics 2007