Ontology-based modeling of clinical practice guidelines: a clinical decision support system for breast cancer follow-up interventions at primary care settings.

Abstract

Breast cancer follow-up care can be provided by family physicians after specialists complete the primary treatment. Cancer Care Nova Scotia has developed a breast cancer follow-up Clinical Practice Guideline (CPG) targeting family physicians. In this paper we present a project to computerize and deploy the said CPG in a Breast Cancer Follow-up Decision Support System (BCF-DSS) for use by family physicians in a primary care setting. We present a semantic web approach to model the CPG knowledge and employ a logic-based proof engine to execute the CPG in order to infer patient-specific recommendations. We present the three stages of the development of BCF-DSS--i.e., (a) Computerization of the paper-based CPG for Breast Cancer follow-up; (b) Development of three ontologies--i.e., the Breast Cancer Ontology, the CPG ontology based on the Guideline Element Model (GEM) and a Patient Ontology; and (c) Execution of the Breast Cancer follow-up CPG through a logic-based CPG execution engine.