1. Multiple Ontologies for Medical Informatics (discussant) Stanley M. Huff, M.D. Intermountain Health Care University of Utah Salt Lake City, Utah

2. Biases Very practical – Homer Warner and the HELP system – Design and manage interfaces (mostly HL7) – Maintain vocabulary server for decision support – UMLS contractor, involved in SNOMED, co-chair of the LOINC committee But… – Truth is stranger than fiction – the real problems present more of a challenge than the theoretical/philosophical ones

3. Thoughts All relationships in ontologies reflect a particular purpose All mappings between terminologies are use specific Some context can only be captured in the a complete clinical record We must prioritize what relationships we want to represent Ontologies must be connected to the real world if they are to be useful All names (terms) are not created equal Controlled combinatorial explosion is unavoidable

4. All relationships in terminologies/ontologies/classific ations reflect a particular purpose

5. Often the purpose is not stated SNOMED CT – mostly reflects a hierarchy for easy maintenance of the terminology I have never found a single hierarchy in SNOMED (or any other published terminology/classification/ontology) that met my clinical need without modification But, all of the published sources are VERY useful as a starting point

6. IHC Diabetic protocol: “All diabetics should get a Hgb A1c test every 6 months.” Diabetes Mellitus – Diabetes mellitus type 1 (disorder) – Diabetes mellitus type 2 (disorder) – Brittle diabetes mellitus (disorder) – Maternal diabetes mellitus (disorder) – Diabetes mellitus during pregnancy, childbirth and the puerperium (disorder) Gestational diabetes mellitus (disorder)

7. SAGE Immunization Protocol: “If the patient has an acute illness, then don’t immunize.” General body state finding (finding) – Illness – (No term for “acute illness”, no children of illness) If there was a term for “acute illness” then it would not be the set of things I want in the context of immunizations

8. All mappings between terminologies are use specific LOINC to CPT mapping for billing 3376-1BARBITURATE S:ACNC:PT: SER/PLAS/BLD :ORD: 82205Barbiturates, not elsewhere classified 3924-8PENTOBARBIT AL:MCNC:PT: SER/PLAS:QN: 82205Barbiturates, not elsewhere classified

9. Context in the next version of IHC’s vocabulary database Concept1, Relationship, Concept2, Context, Owner (person or organization) “Type I Diabetes is-a Diabetes Mellitus in the context of the HgbA1C protocol, Beatriz Rocha”

10. Some context can only be captured in the a complete clinical record Heart rate in Bruce Stage 3 treadmill protocol “The blood pressure that was 47 minutes after a 60 milligram dose of gentamicin given I.V. piggy back, 32 minutes after the sponge bath, 14 minutes after a family visit, with patient supine in ICU bed 6.”

11. We must prioritize what relationships we want to represent The most useful knowledge may not tie directly to verifiable science Mappings for billing codes – It is not exciting scientifically – It is ultimately the choice of a payer

12. Homer Warner – Knowledge engineering sessions What decision are you going to make that requires that data? Only collect data that you are going to use to make a specific decision or answer a specific research question Corrollary: We should only make ontologies (and cross mappings) where we know they will be used and for what purpose

13. What sorts of knowledge will really be used? IHC – – Drugs (structural relationships) – Drugs (functional relationships) – Microorganisms (gram stain morphology) – Limited anatomy Other things are short enough to put in a list in line in the decision logic – Antibiotic Assistant (Scott Evans) – “Drugs metabolized in the kidney.”

14. Why do we choose particular things to put in our terminologies An innate interest – “My father has hypertension.” – “I just always liked dinosaurs.” Funding Publications Fame Improved patient care (These all represent biases)

15. Even if we narrow the scope to verifiable things There are an infinite number of things that are true in the real world We cannot represent all knowledge at once When we make the selection of what to do first, we are demonstrating a bias

16. Ontologies must be connected to the real world if they are to be useful The only way they can be connected is by people through words – (Connecting them to an arbitrary cohort/instance ID is useless) Words change meaning over time People have been unsuccessful in enforcing usage – Homer Warner: Let’s get people to use the words we want them to use – It is a great theory, and we should try to support proper use, but it will never be perfect You must be able to handle semantic drift in the words and concepts that people use

17. All names (terms) are not created equal Just a handle - The name of a “gene” (BRCA1) denotes a particular sequence of nucleic acid bases, much of the meaning and computability is contained in an associated database – Sequence, protein(s), disease risk, correlations in animals Semantically rich - Lung, heart, baby, infant, blood, have a rich context from daily experience We may need different ways of creating and displaying ontologies based on the kinds of names with which we are dealing

18. Controlled combinatorial explosion is unavoidable Combinations are not random, they serve a purpose – Stage IIb adenosquamous cell carcinoma of the rectum with K- ras oncogene expression Combinations come from sources that you cannot control – National Registry of Myocardial Infarctions – Society of Thoracic Surgeons – Cancer registries Post coordination causes complexity in addressing a concept as it participates in decision logic or as clinicians think about it – Carcinoma with body_site = rectum, with stage = Iib, with oncogene expression = K-ras