CIMI – SemanticHealthNet Meeting Brussels 2014 Presentation of WP 4: "Harmonised Resources for Semantic Interop

1. CIMI – SemanticHealthNet Meeting Brussels 2014Presentation of WP 4: "Harmonised Resources for Semantic Interoperability"

2. Activity domain: Tangible evidence Activity domain: Generalisability & scalability and sustainability • WP 3 • Stakeholder validation • Additional conditions and patient populations • Professional communities • Clinical governance • Citizen communities • Health authorities • Global public health • WP 1 • Patient care exemplar: chronic heart failure Workstream III Sustainability / Network co-ordination Workstream I Health-directed requirements, success criteria, governance • WP 2 • Public health exemplar: cardio-vascular prevention • WP 7 • Adoption & sustainability strategies • Business success factors • Sustainability models • WP 4 • Harmonised resources for EHRs/PHRs & aggregation • WP 6 • Industrial engagement • Integration into clinical/public health information systems • Industrial exploitation • Recommendations to SDOs Workstream II SDO-harmonised and tailored resources, tools and methods • WP 8 • European Virtual Organisation • Community building • Organisational governance • Liaison with EU initiatives • Liaison with national bodies • Education, training • WP 5 • Infostructure & tools • Artefact governance, certification & testing • WP 9 • Project management, dissemination, promotion

3. …planned follow up of SemanticHealthNet

4. Activity domain: Tangible evidence Activity domain: Generalisability & scalability and sustainability • WP 3 • Stakeholder validation • Additional conditions and patient populations • Professional communities • Clinical governance • Citizen communities • Health authorities • Global public health • WP 1 • Patient care exemplar: chronic heart failure Workstream III Sustainability / Network co-ordination Workstream I Health-directed requirements, success criteria, governance • WP 2 • Public health exemplar: cardio-vascular prevention • WP 7 • Adoption & sustainability strategies • Business success factors • Sustainability models • WP 4 • Harmonised resources for EHRs/PHRs & aggregation • WP 6 • Industrial engagement • Integration into clinical/public health information systems • Industrial exploitation • Recommendations to SDOs Workstream II SDO-harmonised and tailored resources, tools and methods • WP 8 • European Virtual Organisation • Community building • Organisational governance • Liaison with EU initiatives • Liaison with national bodies • Education, training • WP 5 • Infostructure & tools • Artefact governance, certification & testing • WP 9 • Project management, dissemination, promotion

5. Workpackage 4 • Leader: Medical University of Graz • Participants: Mission: Provide an intermediate semantic layer able to deal with the unavoidable heterogeneity which arises when clinical information is represented across or within the same medical domain. External experts: Daniel Karlsson, RahilQamar, Ronald Cornet, Alan Rector, Rong Chen, JesualdoTomás, Diego Boscá, Mathias Brochhausen, Bill Hogan, Mar Marcos - Ocean Informatics- EN 13606- HL7 International- Eurorec - Geneva Univ. Hospital- INSERM, Paris- IHTSDO- WHO

6. Basic assumption of WP 4 • Plurality of Information Model approaches exists: • openEHR, 13606 / SIAMM / HL7 v3 / CIMI, … • Local schemas are still largely predominant • Information model like structures in existing terminology systems: context model of SNOMED CT • Free text (on purpose out of scope in SHN) • Plurality of representations within one specification exists • WP4's relation to information models • does not develop "yet another" information model • maintains equidistance and neutrality • does not contribute to the development of new information models or model variants • looks at content and not at structure • WP4 wants to explore formal approaches to improve interoperability

7. Role of Ontology and Logic • Transform existing resources (terminologies, clinical models) into “semantically enhanced” ones, using ontology-based formalisms • Rationales for using formal ontology: • Possibility to detect equivalences across different distributions of content between information models and terminologies using logic-based reasoning • Advanced exploitation of clinical information by means of semantic query possibilities also • Terminologies like SNOMED CT increasingly using ontology languages such as OWL • Fuzziness of terminology / information model boundary

8. Overlap Terminologies / Information Models Terminologies to be used without information models Clinical Terminologies • Clinical Information models to be used without or with inexpressive terminologies Clinical Information Models • Contextual statements (negation, plans, beliefs…) within terminologies • SNOMED CT context model • ICD 11 content model • Local terminology within IMs • Postcoordination within IMs

9. Consequence: Plurality of isosemantic expressions

10. Consequence: Plurality of isosemantic expressions cancer confirmed It provides some semantics but does not distinguish between information and what it represents. Reference to terminological / ontological standard is optional • Information model representation (no binding)

11. Consequence: Plurality of isosemantic expressions cancer confirmed It provides some semantics but does not distinguish between information and what it represents. Reference to terminological / ontological standard is optional Everything packaged in one codeNo separate information model needed • Information model representation (no binding) • Terminology representation 395099008 |cancer confirmed|

12. Consequence: Plurality of isosemantic expressions cancer cancer confirmed confirmed It provides some semantics but does not distinguish between information and what it represents. Reference to terminological / ontological standard is optional Everything packaged in one codeNo separate information model needed • Information model representation (no binding) • Terminology representation 395099008 |cancer confirmed| NO SEMANTIC INTEROPERABILITY • Information model / Terminology representation Cancer Terminology expression binding

13. Ontologies – chances and difficulties • Our hypothesis: ontologies can act as a “semantic glue” to create an unambiguous representation by relating information model entities and clinical terminologies • Ontologies will help us to distinguish between: • Clinical entities “what does Heart Failure exactly mean?” • Information entities “what is documented about a specific heart failure instance?” • Epistemic entities “how sure am I whether it is heart failure?” • Clinical process entities “what is done to acquire the knowledge I need?” • Known limitations • expressiveness limited if computable (subset FOL) • the difficulty of "thinking ontologically"

14. Ontologies re-used and created in SemanticHealthNet • InformationArtifacts • ClinicalProcesses • "Clinical entities" (findings, disorders, procedures, substances, organisms...)

15. Ontologies re-used and created in SemanticHealthNet • InformationArtifacts SNOMED CTDomain Ontology • ClinicalProcesses • "Clinical entities" (findings, disorders, procedures, substances, organisms...)

16. Ontologies re-used and created in SemanticHealthNet Toplevel Categories • InformationArtifacts SNOMED CTDomain Ontology • ClinicalProcesses • "Clinical entities" (findings, disorders, procedures, substances, organisms...) BioTopLiteUpper LevelOntology Basic relations Constraining axioms Constraining axioms

17. existence of concrete instances in a real patient may be hypothetic existence can be taken for granted • InformationArtifacts ? ? ? ? • ClinicalProcesses • "Clinical entities" (findings, disorders, procedures, substances, organisms...)

18. Neoplasia Basic representational pattern for terminology binding Patient X Demographics Time stamps Metadata • Example: Diagnosis (statement about clinical situation) • annotation of an information item "this is an information entity of a certain type (e.g. diagnostic statement) which has an attribute (e.g. "suspected") , which is created by a health professional at a given time and is about some type of clinical entity (e.g. neoplasia)…" EHR WHAT? WHO? WHEN?

19. Example: “Suspected heart failure caused by ischaemic heart disease” • One code or postcoordinated expression in SNOMED CT • Reference to two kinds of disorders (ontological types / concepts) • Semantic relation between both • Epistemic context: represents state of knowledge about a clinical situation • Not clear whether there is really some heart failure at all! • Many entries in EHRs must not be interpreted as factual statements • Blending of ontological and epistemic information in one code characteristic for many clinical terminologies

20. Three heterogeneous representations of the same statement Three different atomic information entities “Suspected heart failure caused by ischaemic heart disease” Organ Failure Diagnosis Diagnosis Diagnosis Organ Heart Suspected heart failure caused by ischaemic heart disease Heart Failure Status Suspected Status x Suspected Yes NoUnknown Caused by ischaemic heart disease Cause Ischaemic heart disease

21. “Suspected heart failure caused by ischaemic heart disease” Annotation 1 i s a d i a g n o s i s a b o u t o r g a n i s a f a i l u r e d i a g n o s i s a b o u t h e a r t f a i l u r e O r g a n F a i l u r e D i a g n o s i s O r g a n H e a r t S t a t u s S u s p e c t e d x Y e s C a u s e d b y i s c h a e m i c N o h e a r t d i s e a s e U n k n o w n i s a s u s p e c t e d o r g a n f a i l u r e d i a g n o s i s i s a o r g a n f a i l u r e d i a g n o s i s a b o u t a d i s o r d e r c a u s e d b y i s c h a e m i c h e a r t d i s e a s e

22. “Suspected heart failure caused by ischaemic heart disease” Annotation 1

23. “Suspected heart failure caused by ischaemic heart disease” Annotation 2

24. “Suspected heart failure caused by ischaemic heart disease” Annotation 3

25. One diagnosis instance for each model

26. Query 1 All three information instances found

27. Query 2 All three information instances found

28. How do we apply that? Clinical Model ISO 13606 annotated with Clinical Model openEHR SHN Ontology Framework annotated with SEMANTIC PATTERNS compliant with annotated with Clinical Model HL7 CDA annotated with Clinical Model … SNOMED CTContextModel Use cases: heart failure and cardivascular health

29. How do we apply that? CIMI Clinical Model ISO 13606 annotated with Clinical Model openEHR SHN Ontology Framework annotated with SEMANTIC PATTERNS compliant with annotated with Clinical Model HL7 CDA annotated with Clinical Model … SNOMED CTContextModel Use cases: heart failure and cardivascular health