the role of clinicians in clinical concept modelling
DESCRIPTION
The Role of Clinicians in Clinical Concept Modelling. Kalra D. eHealth week 2010 (Barcelona: CCIB Convention Centre; 2010)TRANSCRIPT
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The role of clinicians in
clinical concept modelling
Dr Dipak Kalra
Centre for Health Informatics and Multiprofessional Education
(CHIME)
University College London
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European health systems:
priorities and challenges
• Growing expectations for equity of access, quality and
efficiency, patient empowerment and engagement
• Rising incidence of chronic diseases and increased
complexity of their treatment
• age related: dementia, cancer
• lifestyle related: diabetes, asthma, obesity, ischaemic heart
disease
• Growing expectations and concerns about patient safety
• Need for better integration across wellness, health care,
public health, occupational health and social care
• Demographic change: ageing population
• Societal pressure for demonstrable protection of privacy
EU National ICT Research Directors Forum, November 9th, 2009
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Point of care
delivery
Continuing care (within the institution)
Long-term shared
care (regional
national, global)
Teaching
Research
Clinical trials
explicit consent
Education
Research
Epidemiology
Data mining
de-identified
+/- consent
Public health
Health care
management
Clinical audit
implied consent
A pan-European Health Infostructure
Citizen in the
community
Social care
Occupational
health
School health
Wellness
Fitness
Complementary
health
real-time knowledge directed carerapid bench to bed translation
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Goals for EHR semantic
interoperability
• To support patient safety, quality of care, chronic
disease management, extended home-care, patient
empowerment
• enable the safe, meaningful sharing and combining of health
record data between heterogeneous systems and actors / care
providers
• enable the integration and safe use of computerised protocols,
alerts and care pathways by EHR systems
• link EHR data to explanatory and educational materials to
support patient and family engagement and professional
development
• ensure the necessary data quality and consistency to enable
meaningful and reliable use of longitudinal and heterogeneous
data for public health, research, health service management
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Electronic Health Record - EHR 2.0
Whittington
Hospital
Healthcare Record
John SmithDoB: 12.5.46
Clinical trials,
functional genomics,
public health databasesEHR repositories
Clinical devices,
instruments
Clinical
applications
Decision support,
knowledge management
and analysis components
Mobile devices
Personnel registers,
security services
Social computing:
forums, wikis and blogs
Integrating information
Centring services on citizens
Creating and using knowledge
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CompositionsSet of entries comprising a clinical care
session or document e.g. test result, letter
EHR ExtractPart or all of the electronic health record
for one person, being communicated
FoldersHigh-level organisation of the EHR
e.g. per episode, per clinical speciality
SectionsHeadings reflecting the flow of information
gathering, or organising data for readability
ClustersMultipart entries, tables,time series,
e.g. test batteries, blood pressure, blood
count
ElementsElement entries: leaf nodes with values
e.g. reason for encounter, body weight
Data values Date types for instance values
e.g. coded terms, measurements with units
EntriesClinical “statements” about Observations,
Evaluations, and Instructions
Contextual building blocks of the EHR
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ISO EN 13606-1 Reference Model
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TreatmentMedication and prescriptions
Symptoms
and history
Body physical
examination findings
Procedures and operations
Hypotheses,
health issues
(problems
and
diagnoses),
risks
Conventional medical summary
Care planning
Advice and education
Chronic
disease
manageme
ntTests and investigations
Self management
and home monitoring
Protocols, guidelines, care
pathways
Prevention and
screening,
population
health
measures
Communication, team-based collaboration
Well-being and fitness,
rehabilitation after illness
Consent, permissions, disclosures, complaints
Social welfare, culture,
religion, attitudes,
expectations, hopes, fears
The EHR landscape that needs modelling
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TreatmentMedication and prescriptions
Symptoms
and history
Body physical
examination findings
Procedures and operations
Hypotheses,
health issues
(problems
and
diagnoses),
risks
Conventional medical summary
Care planning
Advice and education
Chronic
disease
manageme
ntTests and investigations
Self management
and home monitoring
Protocols, guidelines, care
pathways
Prevention and
screening,
population
health
measures
Communication, team-based collaboration
Well-being and fitness,
rehabilitation after illness
Consent, permissions, disclosures, complaints
Social welfare, culture,
religion, attitudes,
expectations, hopes, fears
The EHR landscape that needs modelling
Cardiovascular medicine
Mental health
Hospital admission
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What is a clinical archetype?
• a clinical archetype is an agreed, formal and
interoperable specification
• for representing a given clinical entity such as a
clinical observation, a finding, a plan or a treatment
• within an electronic health record
• invented and maintained by openEHR
• ratified by CEN: EN 13606 Part 2
• ratified by ISO: ISO 13606 Part 2
• to be quality labelled and licensed by EuroRec
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What value do archetypes add?
• A user friendly means to capture and collate professional
consensus on how clinical data should be represented
• A formal model of clinical domain concepts
• e.g. “blood pressure”, “discharge summary”, “fundoscopy”
• Can provide a focussed context for selection of relevant
terms
• Can be published and shared within a clinical community, or
globally
• Can be imported by vendors into EHR system data
dictionaries
• Defines a systematic EHR target for queries and for decision
support
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openEHR Clinical Knowledge Managerhttp://www.openehr.org/knowledge/
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openEHR Clinical Knowledge Managerhttp://www.openehr.org/knowledge/
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openEHR Clinical Knowledge Managerhttp://www.openehr.org/knowledge/
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openEHR Clinical Knowledge Managerhttp://www.openehr.org/knowledge/
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openEHR Clinical Knowledge Managerhttp://www.openehr.org/knowledge/
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openEHR CKM archetypes
• Gold standard (best practice) definitions
• Leveraging the available published evidence
• Referring to as many guidelines as can be found
• Inclusive of as many variants on the requirements as
possible (maximal)
• Openly developed in a social community environment
• Wide, international multi-stakeholder contributions
• Dependent upon level of interest, and on high quality
inputs (like Wikipedia)
• Final decisions based on consensus
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Royal College of Physicians: Clinical
headings
• A standard and defined set of headings for
• acute medical admission
• hospital handover
• discharge summary
• Method:
• literature reviews
• evaluating proformas used by different NHS Trusts
• clinician workshops
• a questionnaire based on the headings and definitions
• > 3000 people responded and 80% agreed on 30 of the 36 suggested
headings
• Feedback and subsequent endorsement from several
other Royal Colleges
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RCP Archetype approach
• Selection of a focussed domain
• Single profession, for now
• Start top down, with clinical headings
• Define content per heading
• Involve clinicians and other stakeholders through
workshops
• Get them to propose content
• Focus on what every good doctor should record
• Not necessarily maximal
• Consider most items to be optional
• Use a paper record template to provide a visual cue to
the content being proposed
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North Central London Integrated Care
Whittington Hospital
and its collaborating
Hospitals
CHIME
(UCL)
Consultant-led
Community Clinical
Services
GP Practices
and
Pharmacies
Collaborative
development
of EHR
systems
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Generic
Commonly used fragments
Medical summary
Medication, prescriptions
Disease management
Cardiovascular
Anticoagulation
Heart failurerespiratory
cardiac
planning
monitoring
Dementia
Assessment
Treatmenteffectiveness
prescriptions
scales & scores
self-care
Audit and governance
Shared care management Clinical letters and reports
Notifications and alerts
Consents, carers
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Generic
Commonly used fragments
Medical summary
Medication, prescriptions
Disease management
Cardiovascular
Anticoagulation
Heart failurerespiratory
cardiac
planning
monitoring
Dementia
Assessment
Treatmenteffectiveness
prescriptions
scales & scores
self-care
Audit and governance
Shared care management Clinical letters and reports
Notifications and alerts
Consents, carers
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Anticoagulation
planning
monitoring
Indication for anticoagulation - {mandatory, ordinal, 15 specified
conditions}
Other indication - {optional, free text}
Anticoagulant drug name - {mandatory, ordinal, 3 specified drugs}
Target INR - {mandatory, quantity, range 0-5}
Target INR range
Upper - {mandatory, quantity}
Lower - {mandatory, quantity}
Intended end date - {optional, calendar date} ------------- one
must
If life-long treatment intended - {optional, Boolean} ------------- be
provided
Actual end date - {optional, calendar date}
Precautions to be taken - {optional, free text}
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Anticoagulation
planning
monitoring Present health situation
Treatment controller
Current INR
Decision support recommended warfarin dose
If recommended dose accepted
Actual warfarin dosage
Decision support recommended monitoring interval
If recommended interval accepted
Actual appointment date
Clinic name
Advice given
Medical comments
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De facto archetype approach
• Focus on the specific support of clinical shared care
• Work with multiple professionals from the start
• Develop archetypes with a view to what is feasible to
record and useful to share
• Archetypes mirror the data structures in real use
• Build on existing paper and electronic systems if they
are useful and used
• Developed with rapid reflection back via clinical
application screens and practice data entry
• Diversity still needs to exist - clinical best practice might
not always be at a consensus - yet!
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TreatmentMedication and prescriptions
Symptoms
and history
Body physical
examination findings
Procedures and operations
Hypotheses,
health issues
(problems and
diagnoses),
risks
Conventional medical summary
Care planning
Advice and education
Chronic
disease
managemen
t
Tests and investigations
Self management and
home monitoring
Protocols, guidelines, care
pathways
Prevention and
screening,
population
health
measures
Communication, team-based collaboration
Well-being and fitness,
rehabilitation after illness
Consent, permissions, disclosures, complaints
Social welfare, culture,
religion, attitudes,
expectations, hopes, fears
Best practice:
published evidence, guidelines,
international consensus,
focus on maximal completeness
De facto:
existing practice, existing systems,
local consensus,
focus on supporting shared care
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Key challenges for successful
clinical modelling
• Semantic interoperability needs to be underpinned by
shared clinical data structures: archetypes
• Large scale, professionally-driven, archetype library
development is now needed
• Professionals will need better (ontology-driven) visuals
to understand their archetype landscape
• Rapid testing of models via clinical applications is vital
• The quality labelling and publication of archetypes must
be centrally co-ordinated within Europe
• More research is needed on how SNOMED CT can
help with semantic consistency across multiple
archetypes
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Getting clinical engagement right
• Involve a wide range of working clinicians
• Develop archetypes with multi-professional input
• Combine available evidence and consensus practice
• Solve real clinical information gaps
• join up virtual teams to improve safety and shared care
• define the benefits right at the start
• No need to structure everything
• start by codifying the data that will improve care
• remember narrative is good for human to human communication
• Quality assure archetypes before they are used
• Pilot in real settings before wide roll out