Reconfigurable modelling with deadlock avoidance for the clinical pathway based on MCPN-CS

Abstract

Clinical Pathway (CP) is very complicated and has many exceptional variations. Generally, its treatment course and control steps cannot be totally predefined. Meanwhile, the CP embodies the “Re-flow” therapy features, which is very hard to model, control and manage. Therefore, combined modular modelling method and structure changing mechanisms, a Modular Coloured Petri Net with changeable structure (MCPN-CS) workflow modelling method is proposed. Aimed at the variations of the CP, the workflow model for the CP can be reconfigured dynamically by using the mechanisms of change-by-modification (CBM) and change-by-composition (CBC). A case study on a workflow modelling of osteosarcoma CP is constructed and the modelling is analyzed by proposed deadlock detection algorithms (DDA). The result validates that the proposed method may noticeably enhance the flexibility, adaptation, reusability and maintainability of the workflow model for the CP. (Received in March 2009, accepted in January 2010. This paper was with the authors 2 months for 1 revision.)