Towards the Merging of Multiple Clinical Protocols and Guidelines via Ontology-Driven Modeling
AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
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Computerization of Clinical Practice Guidelines (CPG) render them to be executable at the point-of-care. In this paper, we present a knowledge modeling methodology to model the form and function of CPG in terms of a new CPG ontology that supports CPG computerization and execution. We developed a CPG ontology, in OWL using Protégé, to represent both the structural elements and the knowledge objects encapsulated in a CPG. We instantiated over 5 different CPG using our CPG ontology, whereby the instantiated CPG can be executed, with patient data, using a logic-based execution engine to provide patient-specific recommendations. We also investigated the dynamic merging of multiple CPG, at the encoding and execution levels, to handle patient co-morbidities. We evaluated the CPG ontology by examining its representational efficacy to adequately model the salient constructs of a CPG based on an existing CPG modeling formalism.