Representation of medical guidelines using a classification-based system

  • Authors:

  • C. Heinlein;K. Kuhn;P. Dadam

  • Affiliations:

  • Dept. Databases and Information Systems, University of Ulm, D-89069 Ulm, Germany;Dept. Internal Medicine, University of Ulm, D-89069 Ulm, Germany;Dept. Databases and Information Systems, University of Ulm, D-89069 Ulm, Germany

  • Venue:
  • CIKM '94 Proceedings of the third international conference on Information and knowledge management
  • Year:
  • 1994

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Abstract

Medical guidelines play an increasing role in selecting diagnostic and therapeutic steps under the aspects of effectiveness, invasiveness, and costs. To work directly on patient data already available in electronic form, they should be integrated into a medical information system. In order to develop a “medical guideline module” (MGM) managing and applying guidelines to patients, a “knowledge level” representation of guidelines is necessary which reflects the structure of medical knowledge and matches medical processes. Furthermore, a direct transformation to the “symbol level” is needed. We use a nested, frame-like structure on the knowledge level and show that a classification-based knowledge representation system (CBKRS) is principally well suited for the symbol level. To facilitate the usage and to be independent of a particular CBKRS, we introduce an intermediate level called “intelligent object system” (IOS). It is developed by augmenting a simple data model for describing complex objects with prototypes and implications as a means to classify objects and to draw inferences based on this classification. Finally, the transformation of guidelines to prototypes and implications is described.