Knowledge-based hybrid variance handling for patient care workflows based on clinical pathways

Variance handling plays a key role in the computerized clinical pathway (CP) management enabling high-quality and efficient patient care processes and healthcare services. Based on the analyses of the classifications and handling characteristics of variances, this paper proposes a hybrid variance handling approach combing generalized fuzzy ECA (GFECA) rules and a typed fuzzy Petri net extended by process knowledge (TFPN-PK) model to effectively support handling decisions of different types of variances. A prototype system is developed to implement the proposed approach and facilitate dynamic management of CP-based healthcare workflows.