A semantics-based clinical pathway workflow and variance management framework

A clinical pathway defines the optimal multidisciplinary care process performed by a team of health care professionals for a particular diagnosis or procedure. Its computerized implementation in the web-based knowledge intensive environment is very important for the delivery of healthcare services with higher quality and efficiency. This paper proposes a framework for semantics-based clinical pathway and variance management to enable such implementation. A clinical pathway ontology (CPO) and relevant domain ontology are developed to serve as a common semantic foundation for the framework. In addition, a hierarchical approach and a temporal rule approach based on Semantic Web rule language (SWRL) are combined to semantically model the knowledge of clinical pathways including clinical outcomes, workflows and temporal relationships for clinical pathway workflow management. Moreover, the generalized fuzzy event-condition-action (GFECA) rule and typed fuzzy Petri net extended by process knowledge (TFPN-PK) models are presented to provide support for the fuzzy analysis and handling decision of different types of variances that occur during patient care processes following clinical pathways.