1. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model Ontology-based reinterpretation of the SNOMED CT context model Catalina Martínez- Costa Stefan Schulz Medical University of Graz (Austria) ICBO 2013 Montreal

3. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model "… integrating resources that were developed using different vocabularies and different perspectives on the data. To achieve semantic interoperability, systems must be able to exchange data in such a way that the precise meaning of the data is readily accessible and the data itself can be translated by any system into a form that it understands." Jeff Heflin and James Hendler (2000) Semantic Interoperability on the Web http://www.cs.umd.edu/projects/plus/SHOE/pubs/extreme2000.pdf http://www.cs.umd.edu/projects/plus/SHOE/pubs/extreme2000.pdf Semantic Interoperability requires distinction between vocabularies and perspectives

4. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model "… integrating resources that were developed using different vocabularies and different perspectives on the data. To achieve semantic interoperability, systems must be able to exchange data in such a way that the precise meaning of the data is readily accessible and the data itself can be translated by any system into a form that it understands." Jeff Heflin and James Hendler (2000) Semantic Interoperability on the Web http://www.cs.umd.edu/projects/plus/SHOE/pubs/extreme2000.pdf Semantic Interoperability requires distinction between vocabularies and perspectives  Terminologies / Ontologies:  Provide codes that denote entity types  Information models  Provide structure and context for data OntologyEpistemology SNOMED CT, ICD, … openEHR HL7 RIM EN 13606, proprietary information models "Heart failure, suspected"

5. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model Epistemic Intrusion is common in biomedical vocabularies Bodenreider O, Smith B, Burgun A. The ontology-epistemology divide: A case study in medical terminology. Proceedings of the Third International Conference on Formal Ontology in Information Systems (FOIS 2004): IOS Press; 2004. p. 185-195.

6. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model "… integrating resources that were developed using different vocabularies and different on the data. To achieve semantic interoperability, systems must be able to exchange data in such a way that the precise meaning of the data is readily accessible and the data itself can be translated by any system into a form that it understands." Jeff Heflin and James Hendler (2000) Semantic Interoperability on the Web http://www.cs.umd.edu/projects/plus/SHOE/pubs/extreme2000.pdf Epistemic Intrusion is common in biomedical vocabularies  Terminologies / Ontologies:  Provide codes that denote entity types Ontology "Heart failure, suspected" Bodenreider O, Smith B, Burgun A. The ontology-epistemology divide: A case study in medical terminology. Proceedings of the Third International Conference on Formal Ontology in Information Systems (FOIS 2004): IOS Press; 2004. p. 185-195. SNOMED CT: 394887005:

7. Most epistemic-laden SNOMED CT concepts are in the hierarchy "Situation with explicit context (CM)" Body structure (body structure) Clinical finding (finding) Environment or geographical location (environment / location) Event (event) Linkage concept (linkage concept) Observable entity (observable entity) Organism (organism) Pharmaceutical / biologic product (product) Physical force (physical force) Physical object (physical object) Procedure (procedure) Qualifier value (qualifier value) Record artifact (record artifact) Situation with explicit context (situation) Social context (social concept) Special concept (special concept) Specimen (specimen) Staging and scales (staging scale) Substance (substance) ~ 3,000 precoordinated concepts patterns for postcoordination information model inside SNOMED CT SNOMED CT: ~ 300,000 concepts "CM"

8. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model CM concepts express absence, presence, history, uncertainty, … alexia and agraphia present COMPLEX CLINICAL SITUATIONS AND EPISTEMIC STATES heart failure excluded suspected neoplasm of brain history of cat allergy heart failure excluded

9. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model  Hierarchy:  "Heart failure excluded (situation)" isA "No cardiac failure (situation)" isA "Heart disease excluded (situation)" isA "Disorder excluded (situation)"  Full definition: "Heart failure excluded (situation)" isA "No Cardiac Failure (situation)" Group1 Associated finding: Heart failure (disorder) Finding context: Known absent (qualifier value) Temporal context: Current or specified time (qualifier value) Subject relationship context: Subject of record (person)  OWL EL++: (according to transformation script) 'Heart failure excluded (situation) ' subclassOf RoleGroup some (('associated finding' some 'Heart failure') and ('finding context' some 'Known absent') and ('temporal context' some 'Current of specified') and ('subject relationship context' some 'Subject of record')) Example: SNOMED CT CM concept "Heart failure excluded"

10. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model  Hierarchy:  "Heart failure excluded (situation)" isA "No cardiac failure (situation)" isA "Heart disease excluded (situation)" isA "Disorder excluded (situation)"  Full definition: "Heart failure excluded (situation)" isA "No Cardiac Failure (situation)" Group1 Associated finding: Heart failure (disorder) Finding context: Known absent (qualifier value) Temporal context: Current or specified time (qualifier value) Subject relationship context: Subject of record (person)  OWL EL++: (according to transformation script) 'Heart failure excluded (situation) ' subclassOf RoleGroup some (('associated finding' some 'Heart failure') and ('finding context' some 'Known absent') and ('temporal context' some 'Current of specified') and ('subject relationship context' some 'Subject of record')) Example: SNOMED CT CM concept "Heart failure excluded"

11. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model  Ontological homogeneity of CM ?  Do they represent clinical situations or information about situations?  What is the difference between X (finding) and X present (situation)?  Current frame-like CM ontologically inappropriate if transformed to EL++  negations (absence of)  value restrictions  expression of uncertainty  Computational consequences if using OWL DL? Problems of current interpretation of SNOMED CT CM concepts

12. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model  Ontological homogeneity of CM ?  Do they represent clinical situations or information about situations?  What is the difference between X (finding) and X present (situation)?  Current frame-like CM ontologically inappropriate if transformed to EL++  negations (absence of)  value restrictions  expression of uncertainty  Computational consequences if using OWL DL? Problems of current interpretation of SNOMED CT CM concepts

13. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model  Ontological clarification of relevant toplevel categories  Identification of modelling patterns in the CM  Re-engineering of selected pattern using OWL DL and considering basic principles of formal ontologies  Peer-review and discussion of patterns, identification of controversial design decisions  Creating SNOMED CT modules using the re-engineered portions  Benchmarking classification time with description logics reasoners Methodology

14. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model  Ontological clarification of relevant toplevel categories  Identification of modelling patterns in the CM  Re-engineering of selected pattern using OWL DL and considering basic principles of formal ontologies  Peer-review and discussion of patterns, identification of controversial design decisions  Creating SNOMED CT modules using the re-engineered portions  Benchmarking classification time with description logics reasoners Methodology

15. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model Reinterpretation of Clinical Situation as part of life when certain condition(s) present / absent PATIENT t Brain neoplasm situation Alexia and agraphia situation Cat allergy situation Clinical finding present: Suspected: Past history of: Clinical finding present: Suspected: Past history of: EHR DOCTOR Schulz S, Rector A, Rodrigues JM, Spackman K. Competing interpretations of disorder codes in SNOMED CT and ICD. AMIA Annu Symp Proc. 2012;2012:819-27.

16. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model PATIENT t Brain neoplasm situation Alexia and agraphia situation Cat allergy situation Clinical finding present: Suspected: Past history of: Clinical finding present: Suspected: Past history of: EHR DOCTOR Schulz S, Rector A, Rodrigues JM, Spackman K. Competing interpretations of disorder codes in SNOMED CT and ICD. AMIA Annu Symp Proc. 2012;2012:819-27. Particular Information object Process Material object Clinical Situation Biological Life BioTopLite:

17. Ontology Patterns for reinterpretation SNOMED CT CM concepts  "P": Clinical Finding present (situation): 'Alexia and agraphia present (situation)' equivalentTo 'Alexia (finding)' and 'Agraphia (finding)'  "A": Clinical finding absent (situation): 'Heart failure excluded (situation)' equivalentTo ClinicalSituation and not (hasProcesualPart some 'Heart failure (finding)')  "N": No past history of clinical finding in subject: 'History of cat allergy (situation)' equivalentTo InformationItem and isAboutSituation only (BiologicalLife and not (hasProcesualPart some 'Cat allergy (finding)'))  "S": Suspected clinical finding: 'Suspected brain neoplasm (situation)' InformationItem and isAboutSituation only 'Neoplasm of brain (finding)') and hasInformationObjectAttribute some Suspected CM concepts interpreted as clinical situations (conjunctions or complements) CM concepts are interpreted as information entities about clinical situations

18. Review of proposed ontology design patterns Brain neoplasm situation Alexia and agraphia situation Clinical finding present: Suspected: Past history of: Clinical finding present: Suspected: Past history of: EHR isAboutSituation only Controversy about representing "ontology binding" in OWL: -Full OWL with puns -Reference to ontology codes as literals that encode queries (e.g. SNOMED CT query syntax) -Using universal restriction operator ("only"), currently preferred working solution

19. Benchmarking of SNOMED CT CM module (Classification time) 10,773 classes 48 object properties 5,381 subclass axioms 5,391 equivalence axioms

20. Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model  SNOMED CT context model (CM): important patterns of combing clinical terms with epistemic information  Current OWL-EL representation of the CM flawed  Redesign patterns controversial regarding  interpretation of all SNOMED CT findings / disorders as clinical situations  the linkage between information entities and clinical situation classes  Bipartition of current CM: parts of CM concepts re-interpreted as clinical situations, parts as information entities  "Friendly" computational behaviour of implemented OWL-DL redesign patterns  Future work: identification of all pattern in the current CM, consensus process regarding redesign within SemanticHealthNet, scripting for producing OWL models for complete CM  Identification of epistemic-laden content in other parts of SNOMED CT Conclusions