1. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Principles of Referent Tracking and its Application in Biomedical Informatics October 20, 2009 Rochester Clinical & Translational Research Curriculum Seminar Series Werner CEUSTERS Center of Excellence in Bioinformatics and Life Sciences Ontology Research Group University at Buffalo, NY, USA

2. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Seminar overview 1.Setting the scene: a rough description of what Referent Tracking is and why it is important 2.Review the basics of Basic Formal Ontology relevant to Referent Tracking The crucial distinction between representations and what they represent 3.How to apply this past and ongoing projects translational data warehousing at UB

3. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Part 1: Setting the scene Referent Tracking: What and Why ?

4. New York State Center of Excellence in Bioinformatics & Life Sciences R T U What is Referent Tracking ? A paradigm under development since 2005, –based on Basic Formal Ontology, –designed to keep track of relevant portions of reality and what is believed and communicated about them, –enabling adequate use of realism-based ontologies, terminologies, thesauri, and vocabularies, –originally conceived to track particulars on the side of the patient and his environment denoted in his EHR, –but since then studied in and applied to a variety of domains, –and now evolving towards tracking absolutely everything, not only particulars, but also universals.

5. New York State Center of Excellence in Bioinformatics & Life Sciences R T U ‘Principles for Success’ Evolutionary change Radical change: Principle 6: Architect Information and Workflow Systems to Accommodate Disruptive Change »Organizations should architect health care IT for flexibility to support disruptive change rather than to optimize today’s ideas about health care. Principle 7: Archive Data for Subsequent Re-interpretation »Vendors of health care IT should provide the capability of recording any data collected in their measured, uninterpreted, original form, archiving them as long as possible to enable subsequent retrospective views and analyses of those data. NOTE NOTE: ‘See, for example, Werner Ceusters and Barry Smith, “Strategies for Referent Tracking in Electronic Health Records” Journal of Biomedical Informatics 39(3):362-378, June 2006.’ Willam W. Stead and Herbert S. Lin, editors; Committee on Engaging the Computer Science Research Community in Health Care Informatics; National Research Council. Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions (2009)

6. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Source of all data Reality !

7. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Ultimate goal of Referent Tracking A digital copy of the world

8. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Requirements for this digital copy R1:A faithful representation of reality R2… of everything that is digitally registered, what is generic  scientific theories what is specific  what individual entities exist and how they relate R3:… throughout reality’s entire history, R4… which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes,...

9. New York State Center of Excellence in Bioinformatics & Life Sciences R T U In fact … the ultimate crystal ball

10. New York State Center of Excellence in Bioinformatics & Life Sciences R T U The ‘binding’ wall How to do it right ? I don’t want a cartoon of the world

11. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Terminologies for ‘unambiguous representation’ ??? 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

12. 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 If two different fracture codes are used in relation to observations made on the same day for the same patient, do they denote the same fracture ? Terminologies for ‘unambiguous representation’ ???

13. 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 If the same fracture code is used for the same patient on different dates, can these codes denote the same fracture? Terminologies for ‘unambiguous representation’ ???

14. 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 Can the same fracture code used in relation to two different patients denote the same fracture? Terminologies for ‘unambiguous representation’ ???

15. 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 Can two different tumor codes used in relation to observations made on different dates for the same patient, denote the same tumor ? Terminologies for ‘unambiguous representation’ ???

16. 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 Do three references of ‘hypertension’ for the same patient denote three times the same disease? Terminologies for ‘unambiguous representation’ ???

17. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Terminologies for ‘unambiguous representation’ ??? 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 Can the same type of location code used in relation to three different events denote the same location?

18. 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 How will we ever know ?

19. New York State Center of Excellence in Bioinformatics & Life Sciences R T U The problem in a nutshell Generic terms used to denote specific entities do not have enough referential capacity –Usually enough to convey that some specific entity is denoted, –Not enough to be clear about which one in particular. For many ‘important’ entities, unique identifiers are used: –UPS parcels –Patients in hospitals –VINs on cars –…

20. New York State Center of Excellence in Bioinformatics & Life Sciences R T U 1.explicit reference to the concrete individual entities relevant to the accurate description of some portion of reality,... Fundamental goals of ‘our’ Referent Tracking Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun;39(3):362-78.

21. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Method: numbers instead of words Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun;39(3):362-78. –Introduce an Instance Unique Identifier (IUI) for each relevant particular (individual) entity 78

22. 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

23. New York State Center of Excellence in Bioinformatics & Life Sciences R T U The shift envisioned From: –‘this human being is a 40 year old patient with a stomach tumor’ To (something like) : –‘this-1 on which depend this-2 and this-3 has this-4’, where this-1 instanceOf human being at t 1 this-2 instanceOf age-of-40-years at t 2 this-2 qualityOf this-1 at t 2 this-3 instanceOf patient-roleat t 3 this-3 roleOf this-1at t 3 this-4 instanceOf tumorat t 4 this-4 partOf this-5at t 6 this-5 instanceOf stomachat t 7 this-5 partOf this-1at t 8 …

24. New York State Center of Excellence in Bioinformatics & Life Sciences R T U The shift envisioned From: –‘this human being is a 40 year old patient with a stomach tumor’ To (something like) : –‘this-1 on which depend this-2 and this-3 has this-4’, where this-1 instanceOf human being at t 1 this-2 instanceOf age-of-40-years at t 2 this-2 qualityOf this-1 at t 2 this-3 instanceOf patient-roleat t 3 this-3 roleOf this-1at t 3 this-4 instanceOf tumorat t 4 this-4 partOf this-5at t 6 this-5 instanceOf stomachat t 7 this-5 partOf this-1at t 8 … denotators for particulars

25. New York State Center of Excellence in Bioinformatics & Life Sciences R T U The shift envisioned From: –‘this human being is a 40 year old patient with a stomach tumor’ To (something like) : –‘this-1 on which depend this-2 and this-3 has this-4’, where this-1 instanceOf human being at t 1 this-2 instanceOf age-of-40-years at t 2 this-2 qualityOf this-1 at t 2 this-3 instanceOf patient-roleat t 3 this-3 roleOf this-1at t 3 this-4 instanceOf tumorat t 4 this-4 partOf this-5at t 6 this-5 instanceOf stomachat t 7 this-5 partOf this-1at t 8 … denotators for appropriate relations

26. New York State Center of Excellence in Bioinformatics & Life Sciences R T U The shift envisioned From: –‘this human being is a 40 year old patient with a stomach tumor’ To (something like) : –‘this-1 on which depend this-2 and this-3 has this-4’, where this-1 instanceOf human being at t 1 this-2 instanceOf age-of-40-years at t 2 this-2 qualityOf this-1 at t 2 this-3 instanceOf patient-roleat t 3 this-3 roleOf this-1at t 3 this-4 instanceOf tumorat t 4 this-4 partOf this-5at t 6 this-5 instanceOf stomachat t 7 this-5 partOf this-1at t 8 … denotators for universals or particulars

27. New York State Center of Excellence in Bioinformatics & Life Sciences R T U The shift envisioned From: –‘this human being is a 40 year old patient with a stomach tumor’ To (something like) : –‘this-1 on which depend this-2 and this-3 has this-4’, where this-1 instanceOf human being at t 1 this-2 instanceOf age-of-40-years at t 2 this-2 qualityOf this-1 at t 2 this-3 instanceOf patient-roleat t 3 this-3 roleOf this-1at t 3 this-4 instanceOf tumorat t 4 this-4 partOf this-5at t 6 this-5 instanceOf stomachat t 7 this-5 partOf this-1at t 8 … time periods (for continuants) when the relationships hold

28. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Relevance: the way RT-compatible systems ought to interact with representations of generic portions of reality instance-of at t #105 caused by

29. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Yes, but … what are particulars ? what are universals ? what are denotators ? … the answer is in …

30. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Part 2: Basic Formal Ontology No (good) Referent Tracking without (good = realism-based) Ontology

31. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Ontology In computer science: –a formal specification of a conceptualization

32. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Not the wrong sort

33. New York State Center of Excellence in Bioinformatics & Life Sciences R T U No serious scholar should work with ‘concepts’

34. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Slow penetration of the idea …

35. New York State Center of Excellence in Bioinformatics & Life Sciences R T U More serious scholars become convinced … what is a concept description a description of?

36. New York State Center of Excellence in Bioinformatics & Life Sciences R T U The right sort of ontology can help … In computer science: –a formal specification of a conceptualization leads to bad ontologies In philosophy: –a representation of reality In the OBO Foundry: – a representational artifact which is intended to represent universals and some defined classes. foundation in philosophical realism

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

38. New York State Center of Excellence in Bioinformatics & Life Sciences R T U 1.There is an external reality which is ‘objectively’ the way it is; 2.That reality is accessible to us; 3.We build in our brains cognitive representations of reality; 4.We communicate with others about what is there, and what we believe there is there. Basic axioms underlying OBO Foundry ontologies Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, Biomedical Ontology in Action, November 8, 2006, Baltimore MD, USA

39. New York State Center of Excellence in Bioinformatics & Life Sciences R T U instanceOf What is there ? The parts of BFO relevant for Referent Tracking some continuant particular some continuant universal instanceOf at t some occurrent particular some occurrent universal

40. New York State Center of Excellence in Bioinformatics & Life Sciences R T U instanceOf at t 2 instanceOf at t 1 instanceOf at t 2 The importance of temporal indexing this-1’s stomach benign tumor instanceOf at t 1 this-4 malignant tumor partOf at t 1 stomach partOf at t 2

41. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Sorts of relations U1U2 P1 P2 UtoU: isa, partOf(UU), … PtoU: instanceOf, lacks, denotes(PU)… PtoP: partOf, denotes, …

42. New York State Center of Excellence in Bioinformatics & Life Sciences R T U tt t instanceOf The essential pieces material object spacetime region me some temporal region my life my 4D STR some spatial region history spatial region temporal region dependent continuant some quality located-in at t … at t participantOf at toccupies projectsOn projectsOn at t

43. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Three levels of reality of what is there L1 R L2L3 beliefs symbolizations ‘about’

44. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Representations in Referent Tracking Portion of Reality Entity Particular Universal Defined class Representation Non-referring particular Denotator IUI RT-tuple corresponds-to Configuration represents CUIUUI denotes is about Representational unit denotes contains class Extension … … … Relation RUI denotes Information content ent.

45. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Part 3: Applications of Referent Tracking

46. New York State Center of Excellence in Bioinformatics & Life Sciences R T U (1) Making existing EHR systems RT compatible In: Teich JM, Suermondt J, Hripcsak C. (eds.), AMIA 2007 Proceedings, Biomedical and Health Informatics: From Foundations to Applications to Policy, Chicago IL, 2007. –Rudnicki R, Ceusters W, Manzoor S, Smith B. What Particulars are Referred to in EHR Data? A Case Study in Integrating Referent Tracking into an Electronic Health Record Application. –Manzoor S, Ceusters W, Rudnicki R. A Middleware Approach to Integrate Referent Tracking in EHR Systems.

47. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Problems with prevailing EHR paradigms Perfect ‘semantic’ tools are useless if data captured at the source is not of high quality Prevailing HIT information models don’t allow data to be stored at acceptable quality level: –No formal distinction between disorders and diagnosis –Messy nature of the notions of ‘problem’ and ‘concern’ –No unique identification of the entities about which data is stored Unique IDs for data-elements cannot serve as unique IDs for the entities denoted by these data-elements

48. New York State Center of Excellence in Bioinformatics & Life Sciences R T U MedtuityEMR Patient’s Encounter Document

49. New York State Center of Excellence in Bioinformatics & Life Sciences R T U (2) The ReMINE Project on Adverse Events Ceusters W, Capolupo M, De Moor G, Devlies J. Introducing Realist Ontology for the Representation of Adverse Events. In: Eschenbach C, Gruninger M. (eds.) Formal Ontology in Information Systems, IOS Press, Amsterdam, 2008;:237-250 Ceusters W, Capolupo M, Smith B, De Moor G. An Evolutionary Approach to the Representation of Adverse Events. In: Medical Informatics Europe 2009, Sarajevo, Bosnia and Herzegovina, August 31, 2009. Studies in health technology and informatics 150;:537-541

50. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Risk Manager’s Event Administration System ReMINE Taxonomy Annotated Events

51. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Part of the ReMINE Domain Ontology

52. New York State Center of Excellence in Bioinformatics & Life Sciences R T U ReMINE’s RT-compatible event registration an incident (#1) that happened at time t2 to a patient (#2) after some intervention (#3 at t1) is judged at t3 to be an adverse event, thereby giving rise to a belief (#4) about #1 on the part of some person (#5, a caregiver as of time t6). This requires the introduction (at t4) of an entry (#6) in the adverse event database (#7, installed at t0).

53. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Advantages Synchronisation of two distinct representations of the same reality: –taxonomies: user-oriented view data annotation Domain ontology compatible with OBO-Foundry ontologies: –no overlap, –easier to re-use. Not only tracking of incidents, but also: –how well individual clinicians and organizations manage adverse events, –how well one learns from past experiences. –ontologies: realism-based view unconstrained reasoning

54. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Over the past 15 years, nearly 500 genes that contribute to inherited eye diseases have been identified. Disease- causing mutations are associated with many ocular diseases, including glaucoma, cataracts, strabismus, corneal dystrophies and a number of forms of retinal degenerations. This remarkable new genetic information highlights the significant inroads that are being made in understanding the medical basis of human ophthalmic diseases. As a result, gene-based therapies are actively being pursued to ameliorate ophthalmic genetic diseases that were once considered untreatable. (3)

55. New York State Center of Excellence in Bioinformatics & Life Sciences R T U eyeGENE™ core medical data schema Patient Clinical Encounter Patient Clinical Finding Patient Diagnosis Specimen Lab Result Clinical Finding Diagnosis Finding Link Diagnosis Clinical Finding Unit Link Units Ceusters W. Providing a Realist Perspective on the eyeGENE Database System. In: Smith B. (ed.) Proceedings of the International Conference on Biomedical Ontologies (ICBO), Buffalo, NY, July 23-26, 2009;67-70.ICBO

56. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Some recommendations (1) For each table, data field and associated allowed values, hard- or soft-coded business rule that restrict data-input, 1.assess what (type of) entity in reality would be denoted by any data instance, –includes any ‘value’ from ‘value sets’, external terminologies, etc 2.represent how these entities in reality relate to each other as well as to other ontologically relevant entities that are not explicitly addressed in the information model, the domain model proper, –based on realism-based ontologies 3.describe formally how the information model has to be interpreted in terms of the domain model. –‘interpretation model’

57. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Some recommendations (2) The (relevant parts of the) interpretation model should be part of any information exchange. Change user interfaces and information model only when no ‘realist interpretation’ is possible or faithful data entry cannot be achieved. –certain fields should not be ‘required’, –formatting, e.g. phone numbers, is acceptable in a user- interface when it satisfies local situations (not ‘requirements’), but not for exchange, –‘unknown’ and ‘null values’ are acceptable, if suitable interpretations are provided in the interpretation model, not just as text in data-dictionaries.

58. New York State Center of Excellence in Bioinformatics & Life Sciences R T U (4) Translational data warehousing observation & measurement data organization model development use add Generic beliefs verify further R&D (instrument and study optimization) application Δ = outcome Today’s data generation and use

59. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Key components data information knowledge hypotheses Players HIT Outcomes generates influences

60. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Key components data information knowledge hypotheses Players HIT Outcomes generates influences representation reality about

61. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Current deficiencies At the level of first-order reality: –Desired outcomes different for distinct players Competing interests –Multitude of HIT applications and paradigms At the level of representations: –Variety of formats –Silo formation (incompatible representations, privacy) –Doubtful semantics In their interplay: –Very poor provenance or history keeping –No formal link with that what the data are about –Low quality

62. New York State Center of Excellence in Bioinformatics & Life Sciences R T U General principles of RT-enabled data warehousing (1)

63. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Unique identifier for: –each data-element and combinations thereof (L3) –what the data-element is about (L1) –each generated copy of an existing data-element (L3) –each transaction involving data-elements (L3) Identifiers centrally managed in RTS Exclusive use of ontologies for type descriptions following OBO-Foundry principles Centrally managed data dictionaries, data-ownership, exchange criteria General principles of RT-enabled data warehousing (2)

64. New York State Center of Excellence in Bioinformatics & Life Sciences R T U General principles of RT-enabled data warehousing (3) Central inventory of ‘attributes’ but peripheral maintenance of ‘values’ Identifiers function as pseudonyms –centrally known that for person IUI-1 there are values about instances of UUI-2 maintained by researcher/clinician IUI-3 for periods IUI-4, IUI-5, … Disclosure of what the identifiers stand for based on need and right to know Generation of off-line datasets for research with transaction-specific identifiers for each element

65. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Feedback to clinical care Finding ‘similar’ patient cases –suggestions for prevention, investigation, treatment ‘Outbreak’ detection Comparing outcomes –related to disorders, providers, treatments, … Links to literature Clinical trial selection …

66. New York State Center of Excellence in Bioinformatics & Life Sciences R T U Summary Referent tracking breaks with ‘traditional’ information management Visionary or Folie à deux ? –work thus far primarily theoretical successful in finding problems and suggesting solutions, but not yet large scale implementations –a lot of redundancy and overhead –simple algorithms but huge search space It took barcodes 15 year to become accepted, thus time is in our favor.