A Method For Goal-Oriented Guideline Modeling In Proforma And Its Preliminary Evaluation

ARTIFICIAL INTELLIGENCE IN MEDICINE: KNOWLEDGE REPRESENTATION AND TRANSPARENT AND EXPLAINABLE SYSTEMS, AIME 2019(2019)

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摘要
Goal-based reasoning may be used to support clinical decision making for multimorbidity patients; medical knowledge originating in different computer-interpretable guidelines (CIGs) and from medical ontologies may be matched at the goal level. This matching may be based on CIG metaproperty specifications referring to standard medical ontologies (e.g., as the U.S. Department of Veterans Affairs National Drug File - Reference Terminology) and adhering to standard patient information models (e.g., HL7's Fast Healthcare Interoperability Resources). To support such knowledge and data integration, we developed a method for specifyingmetaproperty annotations within PROforma CIGs. We positioned this specification step within an existing method for CIG knowledge elicitation/specification, known as the Consensus method. Because clinicians time is costly, the research question thatwe evaluated in this studywaswhether knowledge engineers could successfully use this method to specify clinical practice guideline consensus documents in goal-annotated PROforma terms. The preliminary evaluation with nine information systems students taking an advanced knowledge representation course indicates is encouraging. We discuss the technical and conceptual modeling errors and how they could guide instruction of the goal-oriented CIG modeling.
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关键词
Computer-interpretable guidelines, Goal modeling, Multimorbidity, FHIR, NDF-RT
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