Clinician-led eHealth records

Clinician-led eHealth records
A knowledge-enabled approach to the sharing of health information
Dr Heather Leslie

An ongoing issue
“ In attempting to arrive at the truth, I have applied everywhere for information but in scarcely an instance have I been able to obtain hospital records fit for any purpose of comparison.”
“If they could be obtained, they would enable us to decide many other questions besides the one alluded to. They would show subscribers how their money was being spent, what amount of good was really being done with it or whether the money was not doing mischief rather than good.”
Florence Nightingale, 1863

Why is sharing health information so difficult?
Complex & dynamic clinical domain
Lifelong records
Requirements for clinical diversity
Privacy & Security
Increasing health costs
Safety & Prevention
Mobile population
Mobile providers
...
“If the banks can do it, why can’t health?”
CLINICAL DATA is key

Health Knowledge Complexity
Both the total number of concepts and the rate of change is high
SNOMED medical terminology >400,000 atomic concepts and over 1 million relationships
Not only is health care big, it is open-ended:
In breadth, because new information is always being discovered or becoming relevant
In depth, because finer-grained detail is always being discovered or becoming relevant
In complexity, because new relationships are always being discovered or becoming relevant

Complexity: Medication timing

Clinical diversity
Variety of data represented
Free-text vs Structured
Normal statements
“Nil significant”, “NAD”
Graphical
Fractal nature of medicine
Different clinicians:
Prefer different approaches
Need different levels of detail
Need to record/exchange information on a per patient basis
MYTH: “One size fits all”
Image – eg homunculus
Multimedia
eg video, ECG wave format
Questionnaires, checklists etc

Dynamic knowledge & traditional software
CLINICAL
(dynamic)
TECHNICAL

Lifelong health records?
© Ocean Informatics 2008

EHR ‘bubbles’  message ‘patches’

EHR ‘bubbles’  message ‘patches’
INCREMENTAL EVOLUTION
 How far can we push it?

‘Tail wagging the dog’?

Ideal solution...
Data independentof technology & applications
“Universal health record” – data driven EHR
Lifelong health information
Caters for clinical diversity
Caters for dynamic knowledge
Supports data liquidity/exchange
Enables re-use of health information
Multilingual solution
Terminology agnostic

Knowledge-driven EHRs
ORTHOGONAL APPROACH
 Longer-term viewpoint
Standardised clinical content definitions

Computable, standardised clinical data definitions/models
Reference Model

Code Skeletons
UI Forms
Decision-Support
Data Sets
Computable, standardised clinical data definitions/models
Reference Model
XML Schemas
Messages
Semantic Queries
Terminology Mappings/ Subsets
HTML Display

Knowledge-based clinical models
Are ‘agents for change’
Require a change of mindset
Require upfront planning & coordination
Not more time
REQUIRE CLINICIAN LEADERSHIP & ENGAGEMENT
Ensure quality of clinical data
Warrant data is safe & ‘fit for purpose’
Fulfils quality remit for professional clinical colleges

Semantic interoperability
Walker et al, 2005
Level 1: Non-electronic data. Examples include paper, mail, and phone call.
Level 2: Machine transportable data. Examples include fax, email, and unindexed documents.
Level 3: Machine organisable dataie structured messages, unstructured content Examples include indexed (labeled) documents, images, and objects.
Level 4:Machine interpretable data (structured messages, standardised content)Examples include the automated transfer from an external lab of coded results into a provider’s EHR. Data can be transmitted (or accessed without transmission) by health IT systems without need for further semantic interpretation or translation.
Walker et al, 2005

openEHR artefact ecosystem
Code Skeletons
UI Forms
Decision-Support
openEHR Clinical content models
Data Sets
Archetypes
Templates
Reference Model
XML Schemas
Messages
Semantic Queries
Terminology Mappings/ Subsets
HTML Display

What is openEHR?
The openEHR Foundation is a non-profit established in 2001 – www.openEHR.org
Open source specifications for a logical EHR architecture
Based on 18+ years of international implementation experience including Good European Health Record Project
Superset of ISO/CEN 13606 EHR standard
Engineering paradigm
Separation of clinical and technical concerns
International Community

openEHR knowledge artefacts
Archetype
Template
Foundation building blocks for semantic interoperability
= Structured, computable specification for one single clinical concept
Fix the absolute limits of what can be recorded
Maximal data set
Universal use-case
Design once, re-use over & over
The broader the agreement & governance, the greater the potential for interoperability
Terminology: usually universal bindings to data elements
Computable specification for a specific purpose:
Message, Document, Clinical consultation or Report
Aggregate archetypes; multiple concepts
Constrain to express what is sensible for the specific use-case
Can be governed & shared OR
Can be unique & use-case driven
Terminology: usually expresses context-appropriate value sets

openEHR Reference Model
Underpins the archetypes & templates
Handles all the generic processes associated with operation of an EHR
Structure
Security
Versioning
People, Dates, Times, Data types
Expressed, but hidden, in the tooling
NO CONTENT

ALL THE CONTENT(not restricted to clinical content)
openEHR content models
Archetypes + Templates (+ Terminology)
Domain experts model their domain

Two level modelling
Templates
Archetypes
Archetypes
Archetypes
CLINICAL
TECHNICAL
Software is built independently of the content

Clinicians driving EHRs!

Archetype class  Process
1
Observations
Published evidence base
Domain Expert
Subject
4
Personal knowledge base
Actions
2
Evaluation
3
Investigator’s agents
Instructions
Compositions
Sections
Entries
measurable or observable
5
Admin Entry
Recording data for each activity
order or initiation of a workflow process
clinically interpreted findings

openEHR Archetypes
Focus: Single clinical concepts
Basis for a coherent and consistent approach to clinical knowledge management
Capture, display, querying
Simplify messaging/exchange
Multilingual; no language primacy
Terminology independent
Tightly governed

openEHR Archetypes 2
Provide a ‘glide path’ to knowledge-level interoperability of health information:
Bootstrap new application development
Provide a forward ‘roadmap’ for existing applications
Support data integration
Enable data aggregation & comparative analysis
Enable knowledge-based activities

openEHR Templates
Focus: Use cases, multiple concepts
“Archetypes get all the glory; Templates do all the work!”
Allows tight governance of forms, messaging, reporting formats etc
MORE IMPORTANTLY...
Allows flexible expression of clinical & domain requirements
no need for ‘one size fits all’ approach if based on tightly governed building blocks - archetypes

Clinical knowledge ecosystem
Clinical Knowledge Manager (CKM): www.openEHR.org/knowledge
Online Repository – ‘one stop shop’
openEHR Archetypes & Templates,
Terminology subsets, including SNOMED CT, ICD, LOINC
?Other knowledge artefacts
Manage Publication process
Web 2.0 approach - harness online community collective knowledge and resources; avoid physical meetings
Peer Review and publication of Content, Translations & Terminology binding
Govern knowledge artefacts via digital asset management system
Provenance, audit trails, validation checking
Release sets for implementation

Semantic architecture
Semantic reference

Achievable?
̴ 10-20 archetypes  core clinical information to ‘save a life’
̴ 100 archetypes  primary care EHR
̴ 2000 archetypes  hospital EHR
[compared to >400,000 concepts in SNOMED]
Because openEHR combines:
Structure of archetypes/templates
Terminology codes/value sets

Achievable? 2
Initial core clinical content is common to all disciplines and will be re-used by other specialist colleges and groups
Online archetype consensus in CKM:
Achieved in weeks/archetype
Minimises need for F2F meetings
Multiple archetype reviews run in parallel
Leverage existing and ongoing international work

Can clinicians agree?
“What is a heart attack?”
“5 clinicians, 6 answers” – probably accurate!
“What is an issue vs problem vs diagnosis?”
No consensus in HL7 for years
BUT
There is generally agreement on the structure and concepts – ‘first principles’
HUMAN PROBLEM
Terms, value sets
Problem/Diagnosis name
Status
Date of initial onset
Age at initial onset
Severity
Clinical description
Date clinically recognised
Anatomical location
Aetiology
Occurrences
Exacerbations
Related problems
Date of Resolution
Age at resolution
Diagnostic criteria

Core clinical content
openEHR Top 10 – ‘archetypes to save a life’
Emergency summary
Any health summary
Discharge Summary
Consultation records
Many communications
eReferral

openEHR...
Data independentof technology & applications
Basis for potential “Universal health record”
Enables lifelong health information
Caters for clinical diversity
Caters for dynamic knowledge
Supports data liquidity/exchange
Enables re-use of health information
Multilingual solution
Terminology agnostic
;-)

openEHR brings
A comprehensive semantic framework:
Based on a quality logical EHR
Clear separation of clinical and technical domains
Engagement of clinicians/domain experts
Quality and safety; ‘Fit for purpose’
Independent of communication formats or implementations
Consistent /coherent definition of clinical data, documents and messages
Data liquidity – create the data once, re-use when and where required

Ocean Informatics?
Australian Company
Offices in London, Chile
Co-founder of openEHR Foundation
Executives
Clinician informaticians, Software engineers
Primary authors of openEHR specification
Tools
OceanEHR Platform
Enterprise-scale EHR server, EHR application components
Clinical Modeling Studio
Archetypes, Templates, Terminology Server, Clinical Knowledge Manager
EhrAdapter integration framework
HL7 V2, HL7 CDA, XML etc

Where is Ocean working?
National Health Programs
Sweden
United Kingdom NHS
Australia
Singapore
Kazakhstan
Brazil
Vendors
Slovakia
Netherlands
Research projects
United Kingdom
Australia
Relationships
Open Health Tools
Microsoft
Professional Colleges
American College of Rheumatologists
Royal College of Pathologists of Australasia
Interest:
Australian College of GPs (RACGP)
Australian Rheumatologists
College of Family Physicians of Canada
Royal Australian & New Zealand College of Obstetricians & Gynaecologists
International Council of Nurses

Tooling Demonstration
Clinical Knowledge Manager
Archetype Editor
Template Designer
Terminology Query Editor

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Clinician-led eHealth records

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