A Knowledge-Based Variance Management System for Supporting the Implementation of Clinical Pathways

Variance management is important for computerized implementation of clinical pathways (CPs) to dynamically execute patient care processes and effectively provide high quality and efficient healthcare services. However, current related efforts are not adequate to support variance handling process involving two decision strategies, imprecise knowledge and the interaction with standardized CP workflow. This paper presents a knowledge-based variance management system that is developed using object-oriented analysis and design techniques, especially Unified Modeling Language (UML), and implements effective analysis and handling of various variances through the construction and fuzzy reasoning of generalized fuzzy ECA (GFECA) rules and typed fuzzy Petri net extended by process knowledge (TFPN-PK) models related to the clinical pathway ontology and healthcare domain ontology.