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SNOMED Bound to (Information) ModelPutting terminology to work…
Koray Atalag MD, PhD, [email protected]
Senior Research Fellow (NIHI & ABI)openEHR Management Board Member
Vice Chair HL7 New ZealandMember HISO / SAG
HL7 NZ Workshop, 24 Jul 2015
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Information Models
• Definitely NOT reference information models; – as in HL7 v3 RIM, openEHR/ISO13606 or FHIR resource ontology!
• Define how to capture/represent health information, not the actual concepts (that’s epistemology/ontology!)– e.g. FHIR Patient resource is concerned with how to capture patient
information, not define what patient means per se!
• Use terminology to define clinical meaning or bind valuesets• They may employ a number of formats and methods; inc.
– Spreadsheets, data dictionaries, mindmaps, UML, XSD, Archetypes, v3 & FHIR and even programming languages
• Examples: FHIR (HL7), Archetypes (openEHR), Detailed Clinical Models (DCM), Clinical Element Models (CEM-Intermountain)
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Dealing with forms, Access databases
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Dealing with forms, Access databases
From 2001!!!
http://pathos-web.sf.net
Using ASTM healthcare DTDs…No CDA, no archetype!
First class IM
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Where in the interop stack?
• Technical/FormatNetwork & Data
Standards
• Syntax/SemanticsTerminology
Standards
• Process/IntegrationExchange Standards
• Structure/Advanced semanticsContent
Standards
SNOMED, ICD, ICPCLOINC, NZMT/NZULMATC / GMDN
UN/EDIFACTHL7 v2, v3, FHIRopenEHR/13606 Extract
HL7 FHIR, CDA, ASTM CCRopenEHR/13606/CIMIDICOM SR
TCP/IP, HTTPHTML, XMLRDF, JSON, DDL
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Structure with terminology: SNOMEDInconsistencies due to different post-coordination of concepts
In a vasculitis physical examination: “Vascular exams: Carotid Right/Tender”
247348008 | tenderness (finding) | :363698007 | finding site | = 69105007 | Carotid artery structure (body structure) | : 24028007 | Right (qualifier value) |
_____________________________________________________________________________
301390006 | tenderness of cardiovascular structure | : 363698007 | finding site | = 69105007 | Carotid artery structure (body structure) |: 272741003 | laterality | = 24028007 | Right (qualifier value) |
_______________________________________________________________________________309655006 | On examination-artery (finding) | :
69105007 | Carotid artery structure (body structure) | : 24028007 | Right (qualifier) |:247348008 | tenderness |
_______________________________________________________________________________401050002 | Carotid artery finding (finding) | :
363698007 | finding site | = 69105007 | Carotid artery structure (body structure) | :272741003 | laterality | = 24028007 | Right (qualifier value) | :247348008 | tenderness |
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The Sensible Wayto tackle structure from the point of implementers
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The Sensible Wayto tackle structure from the point of implementers
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The Sensible Wayto tackle structure from the point of implementers
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The Sensible Wayto tackle structure from the point of implementers
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Open specs, tools and content for representing health records & building EHR Systems– 20+ years of international experience (Good European Health Record - GEHR)– Origin and superset of ISO/CEN 13606 Standard– An MDA/MDD Software Engineering Paradigm (e.g. “Inside Systems” vs HIE)– Learning curve for implementers BUT easy on clinicians / modellers
Governed by openEHR Foundation (not-for-profit) I’m one of 4 elected Management Board members (end of 2014)
What’s different? Modelling method: separation of clinical and technical worlds Mature tooling, scientific research & reference implementations in
almost all programming languages
• Once in Gartner Hype Cycle!– Steady international community, maturing now – Underpins many national EHR programs (most Nordic, Brazil, Slovenia)
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The Sensible Waycont.
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The Sensible Waycont.
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The Sensible Waycont.
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The Sensible Waycont.
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The Sensible Waycont.
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The Sensible Waycont.
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IM & Terminology
Terminology: Labels/codes attached to atomic concepts (mostly without clinical context)
– Diabetes Mellitus, ear ache, left hip, CT scan etc.
Some have hierarchy (ICD) & relationships (SNOMED)
Boundary Problem(overlap) Terminology binding
Information Model: structure and semantics of concrete clinical concepts with clinical context/provenance
– Health condition, lab test result, discharge summary, adverse reaction, prescription etc.
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Terminology Binding‘A formally expressible connection between information model
representation and terminology representation of clinical statements recorded in the EHR’
Examples define a terminology subset
^ 1111000000132 |allergy event|:
246075003 |causative agent| =
< 373873005 |pharmaceutical / biologic product|
OR
< 105590001 |substance|
Two different types of terminology bindings:1) linking a data item to external terminology/ontology for
the purpose of defining its real-world meaning2) Linking data element values to external terminology
(e.g. a RefSet or terminology query)
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Blood Pressure Measurement
mindmap representation of openEHR Archetype
1) Linking items to SNOMED to define clinical meaning
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NZ Cardiac Registry: Medication2) Linking data element values to external terminology (NZULM)
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Clinical Information Modeling Initiative
• Led by Stan Huff to address profiling needs• Develop a single curated repository of models• Using a single modelling formalism
– Selected Archetypes as starting point– Will harmonise with UML > Archetype Modeling Language (OMG is on
it!)
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&• FHIR resources and Archetypes are closely related
– should avoid reinvention at all costs!– Also FHIR extensions/profiles <> openEHR Templates
• Archetype FHIR resource conversion is expected to be seamless– Archetypes are usually more detailed; as opposed to
• FHIR resources include most commonly used items (80/20 rule) with an option to extend as needed
• An opportunity exists for FHIR to leverage openEHR content, tooling and expertise– FHIRman says base resources are not enough!
• Oh did I just forget SNOMED?– Not really, both FHIR and openEHR allow for terminology bindings
(for data items which make sense to encode)
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Conclusions
• Information Models key for putting SNOMED to work– Package structure, syntax and semantics in one go– Easy to transform and consume for implementers
• There’s no point coding every data element! – But SNOMED (and other terminology) play key role in:
• Advanced decision support (using ontology-like features/inferencing)• Analytics, research and reporting
• It requires effort, tools and training• Good news is (for implementers)– They don’t have to be concerned (terminologists and
modellers’ job!)– FHIR (inc. SNOMED bindings) sufficient for HIE