Clinical Practice Guidelines (CPGs) contain recommendations intended to optimize patient care, produced based on a systematic review of evidence. In turn, Computer-Interpretable Guidelines (CIGs) are formalized versions of CPGs for use as decision-support systems. We consider the enrichment of the CIG by means of an OWL ontology that describes the clinical domain of the CIG, which could be exploited e.g. for the interoperability with the Electronic Health Record (EHR). As a first step, in this paper we describe a method to support the development of such an ontology starting from a CIG. The method uses an alignment algorithm for the automated identification of ontological terms relevant to the clinical domain of the CIG, as well as a web platform to manually review the alignments and select the appropriate ones. Finally, we present the results of the application of the method to a small corpus of CIGs.

Learning Objective 1: Understand how Computer Interpretable Guidelines can be semantically enriched through the identification of relevant terms in ontologies

Learning Objective 2: Learn the benefits and disadvantages of using an NLP token-based algorithm for finding alignments between ontological terms and the natural language codified in Computer Interpretable Guidelines


Manuel Quesada-Martínez, Universidad de Murcia / IMIB-Arrixaca
Mar Marcos (Presenter)
Universitat Jaume I

Francisco Abad-Navarro, Universidad de Murcia / IMIB-Arrixaca
Begoña Martinez-Salvador, Universitat Jaume I
Jesualdo Fernández Breis, Universidad de Murcia / IMIB-Arrixaca

Presentation Materials: