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Computational Linguistics for Referent Tracking in Electronic Healthcare Records: A Research Agenda

This presentation discusses the use of computational linguistics in solving problems with terminologies and referent tracking in electronic healthcare records. It also explores opportunities for collaboration and interdisciplinary research in ontology-based healthcare applications.

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Computational Linguistics for Referent Tracking in Electronic Healthcare Records: A Research Agenda

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  1. Computational Linguistics for Referent Tracking in Electronic Healthcare Records: a research agendaCogSCI Colloquium Oct 19, 2005 Dr. W. Ceusters European Centre for Ontological Research Saarland University, Saarbrücken - Germany

  2. Presentation overview • ECOR and me • The Electronic Health Record (EHR) • Problems with terminologies and their use in the EHR • Realist ontology • Referent Tracking • Opportunities for computational linguistics

  3. European Centre forOntological Research

  4. ECOR’s members & partners External members Local members Partners Status Oct 2, 2005

  5. Goals and objectives • sustained and coordinated collaboration with institutions with proven track record of excellence in ontological research and in the application of ontology to solve concrete problems. • interdisciplinary approach based on philosophical rigour • exchange of research personnel for short research visits • participation in joint projects, • joint supervision of doctoral research, • joint production of software and authorship of research papers • collaborate in seeking funding at national and international levels for ontology-related research and development activities

  6. Recently also in the US

  7. 1977 1959 - 2005 2004 1989 2002 1992 1998 Short personal history

  8. The Electronic Health Record

  9. Current US GOV eHealth goals & strategies • G1: Inform Clinical Practice: • S1. Provide incentives for EHR adoption. • S2. Reduce risk of EHR investment. • S3. Promote EHR diffusion in rural and underserved areas. • G2: Interconnect Clinicians. • S1. Regional collaborations. • S2. Develop a national health information network. • S3. Coordinate federal health information systems. • Goal 3: Personalize Care. • S1. Encourage use of Personal Health Records. • S2. Enhance informed consumer choice. • S3. Promote use of telehealth systems. • Goal 4: Improve Population Health. • S1. Unify public health surveillance architectures. • S2. Streamline quality and health status monitoring. • S3. Accelerate research and dissemination of evidence. US Department of Health and Human Services July 21, 2004

  10. Electronic Health Record • ISO/TS 18308:2003 • Electronic Health Record (EHR): • A repository of information regarding the health of a subject of care, in computerprocessable form. • EHR system: • the set of components that form the mechanism by which electronic health records arecreated, used, stored, and retrieved. It includes people, data, rules and procedures,processing and storage devices, and communication and support facilities. • More common meaning of EHR system: • only the “software being executed”

  11. The Medical Informatics dogma To structure or NOT to be • Fact: computers can only deal with a structured representation of reality: • structured data: • relational databases, spread sheets • structured information: • XML simulates context • structured knowledge: • rule-based knowledge systems • Conclusion: a need for structured data entry (???)

  12. Example of data entry form www.comchart.com

  13. Structured EHR data entry • Current technical solutions: • Data entry forms • provide the structure • various paradigms: • Rigid, pre-fixed • Adaptable to user-preferences, but fixed when used • Dynamically adapting to entered data in context • Terminologies, coding and classification systems: • provide the language to be used • Exchange of information preserving meaning • Statistics and epidemiology

  14. The International Classification of diseases (WHO). • ... • Chapter II: Neoplasms (C00-D48) • Chapter III: Diseases of the Blood and Blood-forming organs and certain disorders involving the immune mechanism (D50-D89) • Excludes : auto-immune disease (systemic) NOS (M35.9) • .... • Nutritional Anemias (D50-D53) • D50 Iron deficiency anaemia • Includes: ... • D50.0 Iron deficiency anaemia secondary to blood loss (chronic) • Excludes : ... • D50.1 ... • D51 Vit B12 deficiency anaemia • Haemolytic Anemias (D55-D59) • ... • Chapter IV: ...

  15. The alphabetic index of ICD-9-CM • hydrops 782.3 • abdominis 789.5 • amnii (complicating pregnancy) (see also hydramnios) 657 • congenital - see Hydrops, fetalis • fetal(is) or new-born 778. • due to iso-immunisation 773.3 • not due to iso-immunisation 778.0 • meningeal NEC 331.4 • pericardium - see Pericarditis

  16. Snomed International (1995)Number of records (V3.1) • T Topography 12,385 • M Morphology 4,991 • F Function 16,352 • L Living Organisms 24,265 • C Drugs &Biological Products 14,075 • A Physical Agents, Forces and Activities 1,355 • D Disease/ Diagnosis 28,623 • P Procedures 27,033 • S Social Context 433 • J Occupations 1,886 • G General Modifiers 1,176 • TOTAL RECORDS 132,641

  17. T - 3 5 3 2 2 Snomed International (1995):knowledge in the codes. leaflet posterior anatomic mitral cardiac valve cardiovascular

  18. Snomed International :multiple ways to express the same thing D5-46210 Acute appendicitis, NOS D5-46100 Appendicitis, NOS G-A231 Acute M-41000 Acute inflammation, NOS G-C006 In T-59200 Appendix, NOS G-A231 Acute M-40000 Inflammation, NOS G-C006 In T-59200 Appendix, NOS

  19. The search for internal formal consistency: medSORT-II (Evans & Hersh, ‘93) no pin-prick sensation in calf ==> | <neuro-sensation-mx> | <method> | <pin-prock-test> [pin-prick] | <locus> | <body-region> [calf] | <result> | <eval-attr> | <attr> [sensation] | <value> [absent]

  20. UMLS: Unified Medical Language System (NLM) • Tool for information retrieval of 4 components: • Metathesaurus contains information about biomedical concepts and how they are represented in diverse terminological systems. • Semantic Network contains information about concept categories and the permissible relationships among them • Information Sources Map contains both human-readable and machine-processable information about all kinds of biomedical terminological systems • Specialist lexicon: english words with POS

  21. UMLS Semantic Network

  22. Main problems • Internal and external consistency of terminologies. • What do the terms in a terminology stand for ?

  23. Lack of face value Agrammatical constructions Shift in ontological category (or ambiguous meaning) Problems with terminologies (1)

  24. Problems with terminologies (2) ‘ventricle’ used in 2 different meanings

  25. Problems with terminologies (3) • Mixing of differentiae • Ontological nonsense

  26. Problems with terminologies (4) Incomplete classification

  27. Previous work • Many of these deficiencies can be identified corrected or prevented by doing the right sort of “ontology” using a proper tool. • SNOMED-CT • NCIT • UMLS Semantic Network • But this is NOT the topic of this presentation

  28. What’s wrong with currentuse of terminologies (and)ontologies in the EHR ?

  29. wisdom (- representation) knowledge - representation information - representation • Questions not often enough asked: • What part of our data corresponds with something out there in reality ? • What part of reality is not captured by our data, but should because it is relevant ? data - representation Reality What is there on the side of the patient Current mainstream thinking

  30. The story of Jane Smithan old case, well known in the literature ...

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

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

  33. Diagnosis: a severe spiral fracture of the femur

  34. CityHC’s representation formalism(for statements in records) Categories: “represent concepts and are analogous to classes in other formalisms” Individuals: “concrete instances of categories which persist in space and time” 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.” 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.

  35. PtID Date ObsCode Narrative 5572 5572 298 5572 5572 5572 298 2309 47804 5572 5572 12/07/1990 01/04/1997 22/08/1993 22/08/1993 01/04/1997 12/07/1990 21/03/1992 03/04/1993 04/07/1990 17/05/1993 04/07/1990 26442006 2909872 9001224 26442006 9001224 58298795 26442006 9001224 79001 79001 81134009 Essential hypertension closed fracture of shaft of femur Fracture, closed, spiral closed fracture of shaft of femur Accident in public building (supermarket) Other lesion on other specified region closed fracture of shaft of femur Essential hypertension Accident in public building (supermarket) Closed fracture of radial head Accident in public building (supermarket) 5572 04/07/1990 79001 Essential hypertension 0939 24/12/1991 255174002 benign polyp of biliary tract 2309 21/03/1992 26442006 closed fracture of shaft of femur 0939 20/12/1998 255087006 malignant polyp of biliary tract A look at the database: Use of SNOMED codes for ‘unambiguous’ understanding How many numerically different disorders are listed here ? * How many different types of disorders are listed here ? * How many disorders have patients 5572, 2309 and 298 each had thus far in their lifetime ? * * cause, not disorder

  36. PtID Date ObsCode Narrative 2309 298 5572 298 5572 5572 5572 47804 5572 5572 5572 01/04/1997 04/07/1990 04/07/1990 22/08/1993 12/07/1990 22/08/1993 12/07/1990 01/04/1997 21/03/1992 03/04/1993 17/05/1993 79001 26442006 9001224 81134009 26442006 26442006 58298795 2909872 9001224 79001 9001224 Accident in public building (supermarket) Closed fracture of radial head closed fracture of shaft of femur Fracture, closed, spiral closed fracture of shaft of femur closed fracture of shaft of femur Other lesion on other specified region Accident in public building (supermarket) Essential hypertension Accident in public building (supermarket) Essential hypertension Would it be easier if youcould see the code labels ? 5572 04/07/1990 79001 Essential hypertension 0939 24/12/1991 255174002 benign polyp of biliary tract 2309 21/03/1992 26442006 closed fracture of shaft of femur 0939 20/12/1998 255087006 malignant polyp of biliary tract

  37. Different patients. Same supermarket? Maybe the same (irrelevant ?) freezer section ? Or different supermarkets, but always in the freezer sections ? PtID Date ObsCode Narrative Same patient, same hypertension code: Same (numerically identical) hypertension ? 5572 5572 5572 2309 47804 5572 298 298 5572 5572 5572 21/03/1992 12/07/1990 22/08/1993 17/05/1993 01/04/1997 22/08/1993 01/04/1997 04/07/1990 03/04/1993 04/07/1990 12/07/1990 26442006 9001224 58298795 2909872 26442006 26442006 81134009 79001 9001224 79001 9001224 Accident in public building (supermarket) Closed fracture of radial head closed fracture of shaft of femur Essential hypertension Other lesion on other specified region closed fracture of shaft of femur Fracture, closed, spiral Essential hypertension closed fracture of shaft of femur Accident in public building (supermarket) Accident in public building (supermarket) 5572 04/07/1990 79001 Essential hypertension 0939 24/12/1991 255174002 benign polyp of biliary tract Same patient, different dates, same fracture codes: same (numerically identical) fracture ? 2309 21/03/1992 26442006 closed fracture of shaft of femur Same patient, same date, 2 different fracture codes: same (numerically identical) fracture ? Same patient, different dates, Different codes. Same (numerically identical) polyp ? Different patients, same fracture codes: Same (numerically identical) fracture ? 0939 20/12/1998 255087006 malignant polyp of biliary tract A look at the problems ...

  38. Main problem areasfor CityHC’s EHR • Statements refer only very implicitly to the concrete entities about which they give information. • Idiosyncracies of concept-based terminologies • tell us only that some instance of the class the codes refer to, is refered to in the statement, but not what instance precisely. • Are usually confused about classes and individuals. • “Country” and “Belgium”. • Mixing up the act of observation and the thing observed. • Mixing up statements and the entities these statements refer to.

  39. Consequences • Very difficult to: • Count the number of (numerically) different diseases • Bad statistics on incidence, prevalence, ... • Bad basis for health cost containment • Relate (numerically same or different) causal factors to disorders: • Dangerous public places (specific work floors, swimming pools), • dogs with rabies, • HIV contaminated blood from donors, • food from unhygienic source, ... • Hampers prevention • ...

  40. Proposed solution:Referent Tracking • Purpose: • explicitreference 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 individual (= particular, = instance). • Distinguish between • IUI assignment: for instances that do exist • IUI reservation: for entities expected to come into existence in the future

  41. Ontology • ‘Ontology’: the study of being as a science • ‘An ontology’ is a representation of some pre-existing domain of realitywhich • (1) reflects the properties of the objects within its domain in such a waythat there obtains a systematic correlation between realityand the representation itself, • (2) is intelligible to a domain expert • (3) is formalized in a way that allows it to support automatic information processing • ‘ontological’ (as adjective): • Within an ontology. • Derived by applying the methodology of ontology • ...

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

  43. Fracture Of Femur Severe Spiral Jane Smith’s Fracture Of Femur Jane Smith’s Fracture Of Femur’s severity Jane Smith’s Fracture Of Femur’s shape Jane Smith CityHC Dr. Peters City HC exists on 4th July 1990 Dr. Peters locatedat City HC on 4th July 1990 Ontological recategorisation 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

  44. Essentials of Referent Tracking • Generation of universally unique identifiers; • deciding what particulars should receive a IUI; • finding out whether or not a particular has already been assigned a IUI (each particular should receive maximally one IUI); • using IUIs in the EHR, i.e. issues concerning the syntax and semantics of statements containing IUIs; • determining the truth values of statements in which IUIs are used; • correcting errors in the assignment of IUIs.

  45. IUI assignment • = an act carried out by the first ‘cognitive agent’ feeling the need to acknowledge the existence of a particular it has information about by labellingit with a UUID. • ‘cognitive agent’: • A person; • An organisation; • A device or software agent, e.g. • Bank note printer, • Image analysis software.

  46. Criteria for IUI assignment (1) • The particular’s existence must be determined: • Easy for persons in front of you, body parts, ... • Easy for ‘planned acts’: they do not exist before the plan is executed ! • Only the plan exists and possibly the statements made about the future execution of the plan • More difficult: subjective symptoms • But the statements the patient makes about them do exist ! • However: • 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, one pain out of a series of pain attacks that made the patient worried • But: this is not a matter of choice, not ‘any’ out of ...

  47. Criteria for IUI assignment (2) • The particular’s existence ‘may not already have been determined as the existence of something else’: • Morning star and evening star • Himalaya • Multiple sclerosis • May not have already been assigned a IUI. • It must be relevant to do so: • Personal decision, (scientific) community guideline, ... • Possibilities offered by the EHR system • If a IUI has been assigned by somebody, everybody else making statements about the particular should use it

  48. Fracture Of Femur Severe Spiral Jane Smith’s Fracture Of Femur Jane Smith’s Fracture Of Femur’s severity Jane Smith’s Fracture Of Femur’s shape Jane Smith CityHC Dr. Peters 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 4th July 1990 Representation in the EHR particulars • Relevant particulars referred to using IUIs • Relationships that obtain between particulars at time t expressed using relations from an ontology (type OBO) • Statements describing for each particular, at time t: • Of what universal from an ontology it is an instance of • AND/OR (if one insists): • By means of what concept from a concept-based system it can sensibly be described

  49. Pragmatics of IUIs in EHRs • IUI assignment requires an additional effort • In principle no difference qua (or just a little bit more) effort compared to using directly 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 that IUI comes a wealth of already registered information • If for the same patient different IUIs apply, the user must make the decision which one is the one under scrutiny, or whether it is again a new instance • A transfert or reference mechanism makes the statements visible through the RTDB

  50. PtID Date ObsCode Narrative IUI-001 5572 5572 2309 5572 5572 5572 298 5572 298 5572 47804 03/04/1993 01/04/1997 04/07/1990 04/07/1990 12/07/1990 12/07/1990 21/03/1992 01/04/1997 17/05/1993 22/08/1993 22/08/1993 26442006 81134009 26442006 9001224 9001224 79001 58298795 79001 2909872 26442006 9001224 Accident in public building (supermarket) closed fracture of shaft of femur Other lesion on other specified region closed fracture of shaft of femur Essential hypertension Accident in public building (supermarket) Closed fracture of radial head Essential hypertension closed fracture of shaft of femur Fracture, closed, spiral Accident in public building (supermarket) IUI-001 IUI-001 IUI-007 5572 04/07/1990 79001 IUI-005 Essential hypertension 0939 24/12/1991 255174002 IUI-004 benign polyp of biliary tract 2309 21/03/1992 26442006 IUI-002 closed fracture of shaft of femur IUI-007 IUI-005 IUI-007 IUI-012 IUI-005 0939 20/12/1998 255087006 IUI-004 malignant polyp of biliary tract Advantage: betterreality representation IUI-003

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