AIME 89 pp 221-233 | Cite as

Design of a generic information system and its application to Primary Care

  • Andrzej Glowinski
  • Mike O’Neil
  • John Fox
Conference paper
Part of the Lecture Notes in Medical Informatics book series (LNMED, volume 38)

Abstract

There is a growing need for sophisticated information systems in primary care. Achieving a comprehensive information service for primary care is a challenge because of the range of medicine it must cover and the variety of patient management decisions to be faced. A framework has been developed with the versatility required to support information retrieval, data management and decision support facilities for medical practitioners. The design abstracts specific medical facts from the methods that use them, and decision procedures are represented as a set of meta theories. This abstraction permits the use of medical knowledge in a variety of ways. The approach simplifies the task of constructing and maintaining a very large medical knowledge base and provides an opportunity to meet the difficult user interface requirements of general practice. The framework has been incorporated in a prototype implementation, the Oxford System of Medicine.

Keywords

Editing Alopecia 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    B. Chandrasekaran (1987) “Towards a functional architecture for intelligence based on generic information processing tasks”, UCAI-87, 2, pp 1183–1192Google Scholar
  2. 2.
    W. Clancey (1983) “The epistemology of a rule-based system: A framework for explanation”, Artificial Intelligence, 20, pp 215–251CrossRefGoogle Scholar
  3. 3.
    M.B. First, L.J. Soffer and R.A. Miller (1985) “QUICK (QUick Index of Caduceus Knowledge): Using the Internist-1/Caduceus knowledge base as an electronic textbook of medicine”, Computers and Biomedical Research, 18, pp 137–165PubMedCrossRefGoogle Scholar
  4. 4.
    J. Fox and D. Frost (1985) “Artificial Intelligence in Primary Care,” in “Artificial Intelligence in Medicine”, ed. I. de Lotto and M Stefanelli, Elsevier Science Publishers, North Holland, pp. 137–154Google Scholar
  5. 5.
    J. Fox, A. Glowinski, and M. O’Neil (1987) “The Oxford System of Medicine: A Prototype System for Primary Care”, Procedings of the European Conference on Artificial Intelligence in Medicine, Marseilles, Springer-Verlag, pp. 213–216Google Scholar
  6. 6.
    J. Fox and A. Rector (1982) “Expert Systems for Primary Medical Care?”, Automedica, 4, pp 123–130Google Scholar
  7. 7.
    D. Frost, J. Fox, T. Duncan, and N. Preston (1986) “Knowledge Engineering Through Knowledge Programming: The PROPS 2 Package,” Imperial Cancer Research Fund Technical Report pp 1–11Google Scholar
  8. 8.
    R.A. Miller, H.E. Pople, and J.D. Myers (1982) “INTERNIST-1: An experimental computer-based diagnostic consultant for general internal medicine”, New England Journal of Medicine, 307(8), pp 468–476PubMedCrossRefGoogle Scholar
  9. 9.
    M. O’Neil, A. Glowinski and J. Fox (1989) “A symbolic theory of decision-making applied to several medical tasks”, to appear in the Procedings of the Second European Conference on Artificial Intelligence in Medicine, London, Springer-VerlagGoogle Scholar
  10. 10.
    A.L. Rector (1985) “The knowledge based medical record — IMMEDIATE-1 — A basis for clinical decision support in general practice”, in “Artificial Intelligence in Medicine”, ed. I. de Lotto and M Stefanelli, Elsevier Science Publishers, North Holland, pp 37–50Google Scholar
  11. 11.
    T. Timpka (1987) “Knowledge-based decision support for general practitioners: an integrated design”, Computer Methods and Programs in Biomedicine, 25, pp 49–60PubMedCrossRefGoogle Scholar
  12. 12.
    R. Westcott and R.V.H. Jones (1988) “Information Handling in General Practice”, Croom Helm, LondonGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1989

Authors and Affiliations

  • Andrzej Glowinski
    • 1
  • Mike O’Neil
    • 1
  • John Fox
    • 1
  1. 1.Imperial Cancer Research Fund LaboratoriesLondonUK

Personalised recommendations