1. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Introduction to Medical Informatics Terminology and Ontology Challenges SUNY at Buffalo - December 13, 2010 Werner CEUSTERS Center of Excellence in Bioinformatics and Life Sciences Ontology Research Group University at Buffalo, NY, USA http://www.org.buffalo.edu/RTU

2. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Focus of the case study Information technology (IT) in support of local clinical operations. Goal: provide clinicians with IT tools that allow them to do their job: –more efficiently, through: computerized order entry work-flow support standardized in-house electronic communication –and with less risks for errors, through: automated decision support. 2

3. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U What is not discussed Structured medical reporting, Coding of health data, Semantic interoperability with IT systems in other healthcare facilities that provide care to the same patients, N-ary use of the data for clinical research, prevention, drug discovery, … 3

4. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U A more modern view Everything collected wherever, whenever and about whomever which is relevant to a medical problem in whomever, whenever and wherever, should be accessible without loss of relevant detail.

5. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Is this scary? The misuse of medical records has led to loss of jobs, discrimination, identity theft and embarrassment. –An Atlanta truck driver lost his job after his insurance company told his employer that he had sought treatment for alcoholism. –A pharmacist disclosed to a California woman that her ex-spouse was HIV positive, information she later used against him in a custody battle. –A 30-year employee of the FBI was forced into early retirement when the FBI found his mental health prescription records while investigating the man’s therapist for fraud. http://www.consumer-action.org/

6. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Requires ‘agents’ (in at least 2 meanings)

7. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Is this desirable? (2005) An estimated thirty to forty cents of every United States’ dollar spent on healthcare, or more than a half-trillion dollars per year, is spent on costs associated with ‘overuse, underuse, misuse, duplication, system failures, unnecessary repetition, poor communication, and inefficiency’. –Proctor P. Reid, W. Dale Compton, Jerome H. Grossman, and Gary Fanjiang, Editors (2005) Building a Better Delivery System: A New Engineering/Health Care Partnership. Committee on Engineering and the Health Care System, National Academies Press.

8. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Is this desirable? (2006) At least 1.5 million preventable adverse drug events occur in the United States each year. –Institute of Medicine. Preventing Medication Errors. 2006

9. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Is this possible? There are already so many amazing technologies available or ready for clinical trial: –Smart pills that send emails when taken, –‘Blood bots’ for endovascular surgery, –Thought-controlled artificial limbs, –‘Breathalyzer’ for disease diagnosis, –Implantable nano wires to monitor blood pressure, –…

10. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U It is possible if the focus is not just on ‘doing’ observing acting representing comparing

11. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U This brings new requirements Data should not only be understandable by humans, but also by machines. –natural language is a hard nut to crack for machines. 11

12. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Language is ambiguous Often we can figure it out … in Miami hotel lobby warning on plastic bag

13. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Language is ambiguous in Amsterdam hotel elevator Sometimes, we can not …

14. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U The problem of reference in free text ‘The surgeon examined Maria. She found a small tumor on the left side of her liver. She had it removed three weeks later.’ Ambiguities: –who denotes the first ‘she’: the surgeon or Maria ? –on whose liver was the tumor found ? –who denotes the second ‘she’: the surgeon or Maria ? –what was removed: the tumor or the liver ?

15. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U This brings new requirements Data should not only be understandable by humans, but also by machines. –natural language is a hard nut to crack for machines. Data should be unambiguous: –clinicians can deal with certain ambiguities, but machines can not. 15

16. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Coding systems used naively preserve certain ambiguities 557204/07/199026442006closed fracture of shaft of femur 557204/07/199081134009Fracture, closed, spiral 557212/07/199026442006closed fracture of shaft of femur 557212/07/19909001224Accident in public building (supermarket) 557204/07/199079001Essential hypertension 093924/12/1991255174002benign polyp of biliary tract 230921/03/199226442006closed fracture of shaft of femur 230921/03/19929001224Accident in public building (supermarket) 4780403/04/199358298795Other lesion on other specified region 557217/05/199379001Essential hypertension 29822/08/19932909872Closed fracture of radial head 29822/08/19939001224Accident in public building (supermarket) 557201/04/199726442006closed fracture of shaft of femur 557201/04/199779001Essential hypertension PtIDDateObsCodeNarrative 093920/12/1998255087006malignant polyp of biliary tract

17. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 557204/07/199026442006closed fracture of shaft of femur 557204/07/199081134009Fracture, closed, spiral 557212/07/199026442006closed fracture of shaft of femur 557212/07/19909001224Accident in public building (supermarket) 557204/07/199079001Essential hypertension 093924/12/1991255174002benign polyp of biliary tract 230921/03/199226442006closed fracture of shaft of femur 230921/03/19929001224Accident in public building (supermarket) 4780403/04/199358298795Other lesion on other specified region 557217/05/199379001Essential hypertension 29822/08/19932909872Closed fracture of radial head 29822/08/19939001224Accident in public building (supermarket) 557201/04/199726442006closed fracture of shaft of femur 557201/04/199779001Essential hypertension PtIDDateObsCodeNarrative 093920/12/1998255087006malignant polyp of biliary tract IUI-001 IUI-003 IUI-004 IUI-005 IUI-007 IUI-002 IUI-012 IUI-006 7 distinct disorders Codes for ‘types’ AND identifiers for instances

18. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 18 The solution: terminology + ontology Terminology: –solves certain issues related to language use, i.e. with respect to how we talk about entities in reality (if any); Relations between terms / concepts –does not provide an adequate means to represent independent of use what we talk about, i.e. how reality is structured; Women, Fire and Dangerous Things (Lakoff). Ontology (of the right sort) : –Language and perception neutral view on reality. Relations between entities in first-order reality

19. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 19 Terminology alone gets it often wrong Africa [Z01.058] + Americas [Z01.107] + Antarctic Regions [Z01.158] Arctic Regions [Z01.208] Asia [Z01.252] + Atlantic Islands [Z01.295] + Australia [Z01.338] + Cities [Z01.433] + Europe [Z01.542] + Historical Geographic Locations [Z01.586] + Indian Ocean Islands [Z01.600] + Oceania [Z01.678] + Oceans and Seas [Z01.756] + Pacific Islands [Z01.782] + Ancient Lands [Z01.586.035] + Austria-Hungary [Z01.586.117] Commonwealth of Independent States [Z01.586.200] + Czechoslovakia [Z01.586.250] + European Union [Z01.586.300] Germany [Z01.586.315] + Korea [Z01.586.407] Middle East [Z01.586.500] + New Guinea [Z01.586.650] Ottoman Empire [Z01.586.687] Prussia [Z01.586.725] Russia (Pre-1917) [Z01.586.800] USSR [Z01.586.950] + Yugoslavia [Z01.586.980] +

20. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 20 Terminology alone gets it often wrong Wolfram Syndrome All MeSH Categories Diseases Category Nervous System Diseases Cranial Nerve Diseases Optic Nerve Diseases Optic Atrophy Optic Atrophies, Hereditary Neurodegenerative Diseases Heredodegenerative Disorders, Nervous System Eye Diseases Eye Diseases, Hereditary Optic Nerve Diseases Male Urogenital Diseases Urologic Diseases Kidney Diseases Diabetes Insipidus Female Urogenital Diseases and Pregnancy Complications Female Urogenital Diseases

21. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 21 What would it mean if used in the context of a patient ? Wolfram Syndrome All MeSH Categories Diseases Category Nervous System Diseases Cranial Nerve Diseases Optic Nerve Diseases Optic Atrophy Optic Atrophies, Hereditary has Neurodegenerative Diseases Heredodegenerative Disorders, Nervous System Eye Diseases Eye Diseases, Hereditary Optic Nerve Diseases Female Urogenital Diseases and Pregnancy Complications Female Urogenital Diseases Male Urogenital Diseases Urologic Diseases Kidney Diseases Diabetes Insipidus ??? … has

22. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 22 Snomed CT (July 2007): “fractured nasal bones”

23. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 23 SNOMED-CT: abundance of false synonymy nose bones fracture

24. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 24 Coding / Classification confusion A patient with a fractured nasal bone A patient with a broken nose A patient with a fracture of the nose = =

25. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 25 A patient with a fractured nasal bone A patient with a broken nose A patient with a fracture of the nose = = Coding / Classification confusion A patient with a fractured nasal bone A patient with a broken nose A patient with a fracture of the nose = =

26. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U ‘Ontology’ In philosophy: –Ontology (no plural) is the study of what entities exist and how they relate to each other; In computer science and many biomedical informatics applications: –An ontology (plural: ontologies) is a shared and agreed upon conceptualization of a domain; The realist view within the Ontology Research Group combines the two: –We use Ontological Realism, a specific methodology that uses ontology as the basis for building high quality ontologies, using reality as benchmark.

27. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 27 Terminological versus Ontological approach The terminologist defines: –‘a clinical drug is a pharmaceutical product given to (or taken by) a patient with a therapeutic or diagnostic intent’. (RxNorm) The ontologist thinks: –Does ‘given’ includes ‘prescribed’? –Is manufactured with the intent to … not sufficient? Are newly marketed products – available in the pharmacy, but not yet prescribed – not clinical drugs? Are products stolen from a pharmacy not clinical drugs? What about such products taken by persons that are not patients? –e.g. children mistaking tablets for candies.

28. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Observations and similarities

29. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U A useful parallel: Alberti’s grid reality representation Ontological theory

30. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 30

31. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U L1 L2 L3 31

32. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U A (trivial?) example: diagnosis versus disease The disease is hereThe diagnosis is here

33. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Conclusion The challenges: –Revision of the appropriatness of concept-based terminology for specific purposes; –Relationship between models and that part of reality that the models want to represent; –Adequacy of current tools and languages for representation; –Boundaries between terminology and ontology and the place of each in semantic interoperability.