2. 1 The Ontologically Privileged Status of the Past Barry Smith

3. 2 Universals vs. instances Assertions in scientific texts pertain to universals in reality Assertions in a lab report pertain (also) to instances of these universals

4. 3 Universals are those invariants in reality which make possible the use of general terms in scientific inquiry the use of standardized therapies in clinical care the use of standardized procedures in business transactions...

5. 4 universalsinstances / particulars scientific texts, dictionaries diaries, biographies, histories, journalism medical ontologies, terminologies clinical records, lab reports, X-ray images macroeconomic surveys credit card transaction records databases

6. 5 universals / conceptsinstances / particulars scientific texts, dictionaries diaries, biographies, histories, journalism medical ontologies, terminologies clinical records macroeconomic surveys credit card transaction records databases relate indiscriminately to past, present and future

7. 6 universals / conceptsinstances / particulars scientific texts, dictionaries diaries, biographies, histories, journalism medical ontologies, terminologies clinical records, lab reports, X-ray images macroeconomic surveys credit card transaction records relate only to the past

8. 7 universalsinstances / particulars scientific texts, dictionaries diaries, biographies, histories, journalism medical ontologies, terminologies clinical records macroeconomic surveys credit card transaction records databases

9. 8 universals / conceptsinstances / particulars scientific texts, dictionaries diaries, biographies, histories, journalism medical ontologies, terminologies clinical records macroeconomic surveys credit card transaction records databases

10. 9 UMLS Semantic Network

11. 10 Pleural Cavity Pleural Cavity Interlobar recess Interlobar recess Mesothelium of Pleura Mesothelium of Pleura Pleura(Wall of Sac) Pleura(Wall of Sac) Visceral Pleura Visceral Pleura Pleural Sac Parietal Pleura Parietal Pleura Anatomical Space Organ Cavity Organ Cavity Serous Sac Cavity Serous Sac Cavity Anatomical Structure Anatomical Structure Organ Serous Sac Mediastinal Pleura Mediastinal Pleura Tissue Organ Part Organ Subdivision Organ Subdivision Organ Component Organ Component Organ Cavity Subdivision Organ Cavity Subdivision Serous Sac Cavity Subdivision Serous Sac Cavity Subdivision Foundational Model of Anatomy

12. 11 Pleural Cavity Pleural Cavity Interlobar recess Interlobar recess Mesothelium of Pleura Mesothelium of Pleura Pleura(Wall of Sac) Pleura(Wall of Sac) Visceral Pleura Visceral Pleura Pleural Sac Parietal Pleura Parietal Pleura Anatomical Space Organ Cavity Organ Cavity Serous Sac Cavity Serous Sac Cavity Anatomical Structure Anatomical Structure Organ Serous Sac Mediastinal Pleura Mediastinal Pleura Tissue Organ Part Organ Subdivision Organ Subdivision Organ Component Organ Component Organ Cavity Subdivision Organ Cavity Subdivision Serous Sac Cavity Subdivision Serous Sac Cavity Subdivision part_of is_a

13. 12 Gene Ontology

14. 13 Gene Ontology

15. 14 Holy grail of biomedical informatics = integration of genomic and EHR data Main obstacles 1. Poor facility for dealing with time and instances / particulars in current ontologies 2. Poor facility for dealing with instances / particulars in current clinical record systems

16. 15 Current ontologies are about meanings (‘concepts’, ‘conceptualizations’)

17. 16 The Ontologically Privileged Status of Universals

18. 17 The Ontologically Privileged Status of Universals (a.k.a. Concepts)

19. 18 ? The concept diabetes mellitus becomes ‘associated with a diabetic patient’ concept patient concept diabetes what it is on the side of the patient ?

20. 19 ? The concept diabetes mellitus becomes ‘associated with a diabetic patient’ concept patient concept diabetes what it is on the side of the patient ? What is the relation here? Not a relation between concepts

21. 20 A contains B =def the concept A stands in a containment relation to the concept B A causes B =def the concept A stands in a causative relation to the concept B A is_a B =def. ‘A’ is more specific in meaning than ‘B’

22. 21 GALEN vomitus contains carrot

23. 22 UMLS Semantic Network: Food causes Experimental Model of Disease Biomedical or Dental Material causes Mental or Behavioral Dysfunction Manufactured Object causes Disease or Syndrome

24. 23 vomitus contains carrot The authors of ontologies have not paid attention to the question whether these are all or some assertions

25. 24 because they have not paid attention to instances some instances of vomitus contain instances of carrot all instances of vomitus contain instances of carrot

26. 25 IFOMIS proposal: move from associative relations between concepts/meanings to strictly defined relations between the universals (types, kinds) in reality embraced also by Gene Ontology Consortium

27. 26 Key idea Ontological relations like contains, part_of, causes are relations between universals, but to define them properly we need to take account of instances and of time

28. 27 Three kinds of relations : is_a, part_of,... : this throb here and now instance_of the class throb : Mary’s heart part_of Mary at t

29. 28 part_of A part_of B =def. given any particular a and any time t, if a is an instance of A at t, then there is some instance b of B such that a is an instance-level part_of b at t HAS ALL-SOME FORM

30. 29 transformation_of c at t 1 C c at t C 1 time same instance mature RNA transformation_of pre-RNA adult transformation_of child

31. 30 transformation_of A transformation_of B =def for all a, t, if a is an instance of A at t then there is some t´ earlier than t which is such that a is an instance of B at t´ HAS ALL-SOME FORM

32. 31 transformation_of in short: A transformation_of B =def. any instance of A was at some earlier time an instance of B Contrast: A transforms_into B child transforms_into adult The ontologically privileged status of relations pointing towards the past

33. 32 C c at t c at t 1 C 1 embryological development

34. 33 C c at t c at t 1 C 1 tumor development

35. 34 Advantages of the methodology of enforcing commonly accepted coherent definitions promote quality assurance (better coding) guarantee automatic reasoning across ontologies and across data at different granularities yields direct connection to times and instances in EHR

36. 35 The story of Jane Smith (with thanks to Werner Ceusters)

37. 36 Jane’s favourite supermarket July 4th, 1990: Jane goes shopping: The freezer section of Jane’s favourite supermarket The only available warning sign used outside A very suspiciously shaped upper leg

38. 37 A visit to the hospital City Health Centre Dr. Peters (City HC) Dr. Longley

39. 38 Diagnosis: a severe spiral fracture of the femur

40. 39 The City HC’s medical record captures in a structured form all of the ‘clinically significant’ information in the narrative notes Rector AL, Nowlan WA, Kay S, Goble CA, Howkins TJ. A framework for modelling the electronic medical record. Methods Inf Med. 1993 Apr;32(2):109-19.

41. 40 Structured Medical Record www.medappz.com/ 04/07/1990 – 17:10Dr. Peters Jane Smith Orthopedics Emergency visit: 04/07/1990 – 17.00 Severe Left upper leg Since fall on floor Constant 26442006closed fracture of shaft of femur 81134009fracture, closed, spiral

42. 41 CityHC’s representation formalism for statements in records Occurrences: “ are specific occurrences of individuals and must be situated in space and time. The most important group of occurrences are observations — i.e. agents ’ observations of individuals. ”

43. 42 City HC’s EHR model

44. 43 Rector et al: “Every occurrence level statement concerning the Jane Smith’s Fracture of the Femur is an observation of the corresponding individual.” “The existence of the individual Jane Smith’s Fracture of Femur does not imply that Jane Smith has, or has ever had, a fracture of the femur, but merely that some observation has been made about Jane Smith regarding a fracture of the femur.” “(The only observation recorded about Jane Smith’s Fracture of the Femur might be that she did not have it.)”

45. 44 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 Same patient, same hypertension code: Same (numerically identical) hypertension ? Different patients, same fracture codes: Same (numerically identical) fracture ? Same patient, different dates, same fracture codes: same (numerically identical) fracture ? Same patient, same date, 2 different fracture codes: same (numerically identical) fracture ? Problems Different patients. Same supermarket? Maybe the same (irrelevant ?) freezer section ? Or different supermarkets, but always in the freezer sections ? Same patient, different dates, Different codes. Same (numerically identical) polyp ?

46. 45 Main problems of EHRs Statements refer only implicitly to the concrete entities about which they give information. Codes are general: they tell us only that some instance of the class the codes refer to, is referred to in the statement, but not what instance precisely. Mixing up the act of observation and the thing observed. Mixing up statements and the entities these statements refer to.

47. 46 Consequences Difficult to: –count the number of (numerically) different diseases Bad statistics on incidence, prevalence,... Bad basis for health cost containment –relate (numerically the same or different) causal factors to disorders: –Dangerous public places (specific work floors, swimming pools), HIV contaminated blood from donors, food from unhygienic source,... Hampers prevention

48. 47 Proposed solution: Referent Tracking Purpose: –explicit reference to the concrete individual entities relevant to the accurate description of each patient’s condition, therapies, outcomes,... Method: –Introduce an Instance Unique Identifier (IUI) for each relevant particular / instance

49. 48 CUI (coo-ey): Concept Unique Identifier (e.g. a SNOMED code) UUI (oo-ey): Universal Unique Identifier IUI (you-ey): Instance Unique Identifier (e.g. a Social Security Number)

50. 49 Referent tracking a response to the hard NLP problem of reference resolution in running text

51. 50 Ontology An ontology is a representation of some pre- existing domain of reality which (1) reflects the properties of the objects within its domain in such a way that there obtains a systematic correlation between reality and the representation itself, (2) is intelligible to a domain expert (3) is formalized in a way that allows it to support automatic information processing

52. 51 Basic Formal Ontology ContinuantsOccurrents / Events endure identically through time while undergoing changes, including gaining and losing parts unfold themselves through time in successive temporal phases

53. 52 Basic Formal Ontology ContinuantsOccurrents Independent: things, substances Always dependent on their bearers (participants/agents) Dependent: functions, qualities, shapes, roles...

54. 53 An ontological analysis continuants City HC The freezer section of Jane’s favourite supermarket Jane’s left femur Jane’s left femur fracture Jane Smith Dr. Peters Jane’s left femur Jane’s fracture’s image Dr. Longley City HC’s EHR system t Universals EHR system HC Freezer section Person Femur Fracture Image Jane’s falling Jane’s femur breaking Dr. Peter’s examination of Jane’s fracture Dr. Peter’s ordering of an X-ray Shooting the pictures of Jane’s leg occurrents Jane’s fracture’s healing Dr. Peter’s diagnosis making Jane dies Freezer section dismantled Dr. Longley’s examination of Jane’ s fracture

55. 54 Essentials of Referent Tracking Deciding what particulars should receive a IUI; Finding out whether or not a particular has already been assigned a IUI; Using IUIs in the EHR, resolve issues concerning the syntax and semantics of statements containing IUIs; Correcting errors in the assignment of IUIs; Dealing with relation between IUI-identified instances and corresponding universals

56. 55 Architecture of a Referent Tracking System (RTS) Ideally set up to be as geographically broad in scope as possible Services: –IUI generator –IUI repository: statements about assignments and reservations –Referent Tracking Database (RTDB): statements relating instances to instances and universals

57. 56 IUI generation Universally Unique IDs: –recently standardized through ISO/IEC 9834- 8:2004, –specifies format and generation rules enabling users to produce 128-bit identifiers that have a very high probability of being globally unique –Meaningless strings

58. 57 IUI assignment = an act of labelling carried out by the first cognitive agent needing to acknowledge the existence of a particular it has information about cognitive agent: –A person –An organisation –A device or software agent, e.g. Bank note printer Image analysis software Credit card transaction reader

59. 58 Criteria for IUI assignment (1) The particular’s existence must be determined: –Easy for persons in front of you, for body parts, for X- ray images –More difficult for subjective symptoms –No need to know what the particular exactly is, i.e. which universal it instantiates –No need to be able to point to it precisely One bee out of a particular swarm that stung the patient

60. 59 Criteria for IUI assignment (2) The particular should not have been already determined as something else: Morning star / evening star May not have already been assigned a IUI. Must be salient/relevant/significant: Personal decision, (scientific) community guideline,... Reflects a possibility offered by the EHR system Once a IUI has been assigned, everybody making statements about this particular should use it

61. 60 IUI assignments The act of IUI assignment can be represented as: d a = IUI of the registering agent A i = p a = IUI of the author of the assertion p p = IUI of the particular t ap = time of assignment c = optional description t d = time of registering A i in the IUI-repository Neither ‘t d ’ nor ‘t ap ’ give any information about when #p p began to exist.

62. 61 Management of IUI-repository Adequate safety and security provisions –Access authorisation, control, read/write,... –Pseudonymisation Deletionless but with facilities for correcting mistakes. Central management with adequate search facilities.

63. 62 Representation in the EHR Relevant particulars referred to using IUIs Relationships that obtain between particulars at time t expressed using strictly defined relations from an ontology Statements describing for each particular at time t of what universal from an ontology it is an instance CityHCDr. Peters Jane Smith Jane Smith’s Fracture Of Femur Fracture Of Femur Severe Spiral Jane Smith’s consultation with Dr. Peters at City HC on 4th July 1990 Dr. Peters’ assessment of Jane Smith’s fracture of femur at City HC on 4th July 1990 Jane Smith’s Fracture Of Femur’s severity Jane Smith’s Fracture Of Femur’s shape 4th July 1990

64. 63 PtoP (particular to particular) statements ordered sextuples of the form: s a the IUI of the author of the statement, t a the time when the statement is made, r a relationship obtaining between the particulars referred to in P, o the ontology from which r is taken, P an ordered list of the IUIs of the particulars between which r obtains, t r the time at which r obtains.

65. 64 PtoCL (particular to class) statements s a the IUI of the author of the statement, t a the time when the statement is made, inst an instance relationship available in o obtaining between p and cl, o the ontology from which inst and cl are taken, p the IUI of the particular whose inst relationship with cl is asserted, cl the class in o to which p enjoys the inst relationship, t r the time at which the relationship obtains.

66. 65 PtoCO (particular to concept code) statements s a the IUI of the author of the statement, t a the time when the statement is made, cbs the concept-based system from which co is taken, p the IUI of the particular which the author associates with co, co the concept-code in cbs which the author associates with p, t r a reference to the time at which the author considers the association appropriate,

67. 66 Interpretation of PtoCO statements Such statements tell us that within the linguistic and scientific community in which cbs is used, the terms associated with co may be used to denote p

68. 67 A SNOMED-CT example #IUI-0945: author of the statement #IUI-1921: the left testicle of patient #IUI-78127 367720001: the SNOMED concept-code to which “left testis” is (in SNOMED) attached as term So we can denote #IUI-1921 by means of that left testis that entire left testis that testicle, that male gonad, that testis that genital structure that physical anatomical entity BUT NOT: that SNOMED-CT concept

69. 68 Pragmatics of IUIs in EHRs IUI assignment requires (just a bit) more effort compared to current use of general codes from concept-based systems –A search for concept-codes is replaced by a search for the appropriate IUI using exactly the same mechanisms Browsing Code-finder software Auto-coding software (CLEF NLP software Andrea Setzer) –With some IUIs there comes a wealth of already registered information

70. 69 IUIs in structured EHRs www.medappz.com/ 04/07/1990 – 17:10Dr. Peters Jane Smith Orthopedics Emergency visit: 04/07/1990 – 17.00 Severe Left upper leg Since fall on floor Constant 26442006closed fracture of shaft of femur 81134009fracture, closed, spiral Replaced by the IUI for the patient’s left upper leg That IUI might be found by using “left upper leg” as a search term to query the RTDB Both replaced by the IUI for that fracture By means of PTCO statements is the IUI related to the SNOMED-codes

71. 70 Advantage: better reality 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 IUI-001 IUI-003 IUI-004 IUI-005 IUI-007 IUI-002 IUI-012

72. 71 Other Advantages Mappings between ontologies and coding systems created as by-product of tracking –Descriptions about the same particular using different systems e.g. in different hospitals Quality control of ontologies and concept- based systems –Systematically inconsistent descriptions within or across terminologies may indicate poor definition of the respective terms

73. 72 Other advantages credit card transaction records already constitute a referent tracking database can give a global picture of economic patterns in a given society Our proposal will provide for something analogous in the realm of healthcare

74. 73 Other Advantages Referent tracking can be used in decision support when making diagnoses We can consider the results of assignment of different clinical codes to one and the same collection of IUIs assembled over a period (and thereby uncover new patterns of symptoms, e.g. in a case of multiple sclerosis)

75. 74 Conclusion Referent tracking can solve a number of problems in an elegant way. Existing (or emerging) technologies can be used for the implementation. Old technologies can play an interesting role. Big Brother feeling is to be expected, but with adequate measures easy to fight. Pilot is being established

76. 75 Generalizing beyond healthcare 1) intelligence/security: tracking movements of people and goods 2) tracking copies of papers, music-files, over the internet. Numbers can be assigned by producers of the files, but also by the people who forward them (buying and selling numbers) 3) creation of tag-technology for all forms of hardware/collectibles 4) gaming (turning spam into a game): collaborative, distributed story writing 5) gambling/play mixture: a question is asked, and every tenth, twentieth,... person who calls the TV studio is allowed to answer. But calling costs you $1. Referent tracking allows this idea to be realized over email/internet.