An Ontological Framework for Representing Clinical Knowledge in Decision Support Systems


In the last decades, clinical evidence and expert consensus have been encoded into advanced Decision Support Systems (DSSs) in order to promote a better integration into the clinical workflow and facilitate the automatic provision of patient specific advice at the time and place where decisions are made. However, clinical knowledge, typically expressed as unstructured and free text guidelines, requires to be encoded into a computer interpretable form suitable for being interpreted and processed by DSSs. For this reason, this paper proposes an ontological framework, which enables the encoding of clinical guidelines from text to a formal representation, in order to allow querying, advanced reasoning and management in a well defined and rigorous way. In particular, it jointly manages declarative and procedural aspects of a standards based verifiable guideline model, named GLM-CDS (GuideLine Model for Clinical Decision Support), and expresses reasoning tasks that exploit such a represented knowledge in order to formalize integrity constraints, business rules and complex inference rules. Keywords—Clinical Practice Guidelines, Decision Support Systems, Ontology, Rules, Unstructured Data.

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@inproceedings{Iannaccone2014AnOF, title={An Ontological Framework for Representing Clinical Knowledge in Decision Support Systems}, author={Marco Iannaccone and Massimo Esposito}, year={2014} }