Interface of Inference Models with Concept and Medical Record Models

  • Alan L. Rector
  • Peter D. Johnson
  • Samson Tu
  • Chris Wroe
  • Jeremy Rogers
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2101)


Medical information systems and standards are increasingly based on principled models of at least three distinct sorts of information — patient data, concepts (terminology), and guidelines (decision support). Well defined interfaces are required between the three types of model to allow development to proceed independently. Two of the major issues to be dealt with in the defining of such interfaces are the interaction between ontological and inferential abstractions — how general notions such as ‘abnormal cardiovascular finding’ are abstracted from concrete data- and the management of the meaning of information in guidelines in different contexts. This paper explores these two issues and their ramifications.


Information Model Electronic Patient Record Inference Model Clinical Information System British National Formulary 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Rector, A.L. The Interface between Information, Terminology, and Inference Models. in Medinfo-2001 (2001) (in press).Google Scholar
  2. 2.
    Tu, S.W. and M.A. Musen. Modeling data and knowledge in the EON guideline architecture. in Medinfo 2001 (2001) (in press).Google Scholar
  3. 3.
    HL7, HL7 Data Model Development, (2000),
  4. 4.
    CEN/WG1, ENV13606: Electronic Healthcare Record Architecture,. 1999, CEN.Google Scholar
  5. 5.
    Ingram, D., GEHR: The Good European Health Record, in Health in the New Communications Age, M. Laires, M. Ladeira, and J. Christensen, Editors. IOS Press: Amsterdam. (1995) 66–74.Google Scholar
  6. 6.
    Education, C.f.H.I.a.M., The GEHR Homepage, (1997),
  7. 7.
    Spackman, K.A., K.E. Campbell, and R.A. Côté, SNOMED-RT: A reference Terminology for Health Care. Journal of the American Medical Informatics Association (JAMIA), ((Symposium special issue)): (1997) 640–644.Google Scholar
  8. 8.
    OpenGALEN, OpenGALEN Home Page,
  9. 9.
    Rector, A., Thesauri and formal classifications: Terminologies for people and machines. Methods of Information in Medicine, 37(4-5): (1998) 501–509.Google Scholar
  10. 10.
    Pryor, T. and G. Hripscsak, The Arden syntax for medical logic modules. Int J Clin Monit Comput,. 10(4): (1993) 214–224.CrossRefGoogle Scholar
  11. 11.
    Tu, S.W. and M.A. Musen. A flexible approach to guideline modelling. in AMIA Fall Symposium. Hanley and Belfus (1999) 420–424.Google Scholar
  12. 12.
    Johnson, P.D., et al., Using scenarios in chronic disease management guidelines for primary care. JAMIA, (Symposium Special Issue): (2000) 389–393.Google Scholar
  13. 13.
    Fox, J. and S. Das, Safe and Sound., Cambridge MA: MIT Press. (2000).Google Scholar
  14. 14.
    Peleg, M., et al. GLIF3: The evolution of a guideline representation format. in AMIA Fall Symposium (2000) 645–649.Google Scholar
  15. 15.
    Shahr, Y. Timing is everything: temporal reasoning and temporal data maintenance in medicine. in Seventh Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making. Springer Verlag (1999)Google Scholar
  16. 16.
    Berg, M., Medical work and the computer-based patient record: A sociological perspective. Methods of Information in Medicine, 37: (1998) 294–301.Google Scholar
  17. 17.
    Bray, J., et al., Identifying patients with ischaemic heart disease in general practice: cross sectional study of paper and computerised medical records. British Medical Journal, 321: (2000) 548–050.CrossRefGoogle Scholar
  18. 18.
    Hripscak, G., et al. The Arden Syntax for Medical Logic Modules. in Fourteenth Annual Symposium on Computer Applications in Medical Care (SCAMC-90). McGraw Hill (1990)Google Scholar
  19. 19.
    HL7, HL7 Home Page,
  20. 20.
    Solomon, W., et al., Having our cake and eating it too: How the GALEN Intermediate Representation reconciles internal complexity with users’ requirements for appropriateness and simplicity. Journal of the American Medical Informatics Association, (Fall Symposium Special Issue): (2000) 819–823.Google Scholar
  21. 21.
    College of American Pathologists, SNOMED Home Page,
  22. 22.
    Nowlan, W.A., Clinical workstation: Identifying clinical requirements and understanding clinical information. International Journal of Bio-Medical Computing,. 34: (1994) 85–94.CrossRefGoogle Scholar
  23. 23.
    Franconi, E. A Semantic approach for schema evolution and versioning in object-oriented databases. in 6th International Conference on Rules and Objects in Databases (DOOD’2000) (2000)Google Scholar
  24. 24.
    The OIL Home Page, (2000),

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Alan L. Rector
    • 1
  • Peter D. Johnson
    • 2
  • Samson Tu
    • 3
  • Chris Wroe
    • 1
  • Jeremy Rogers
    • 1
  1. 1.Medical Informatics Group, Dept of Computer ScienceUniversity of ManchesterUK
  2. 2.Sowerby Centre for Health Informatics in NewcastleUniversity of Newcastle upon TyneUK
  3. 3.Stanford Medical InformaticsStanford UniversityUSA

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