An ontology to model time in Clinical Practice Guidelines

Clinical Practice Guidelines (CPGs) are developed to reduce inappropriate variations in clinical practice, to improve health care quality and to control costs. In order to provide patient-specific treatment, the collection and processing of temporal data are vitally important in many clinical settings, especially for chronic diseases. Representation of temporal data within CPGs is a critical issue for computer based guideline development. Our objective is to create an ontology formalism to represent practice-oriented temporal knowledge in a collection of CPGs for chronic diseases. The CPGs selected for the development of the temporal model were on Diabetes. Our methodology is comprised of five steps: identifying the purpose, scope, and users of semantic models; domain analysis and knowledge acquisition; building a conceptual ontological model; building a formal ontological model using Protege; and ontology evaluation. One of the potential applications of our ontological model is its integration with decision support and patient management applications.