A Medical Diagnostics Service Chain Optimization Method Based on Stochastic Petri Net

Medical diagnostics involves multiple levels of modern clinical diagnostic devices and the process of medical diagnostics confront different decision for data transitions among multiple layers. In this work we analyze the challenges of modern medical diagnostics, which is an important part of public healthcare, and formulate this complex process as service chain. Based on stochastic Petri net, a modeling and optimization method is proposed for the medical diagnostics service chain. The case study shows that the competition relationship in the medical diagnostic process can be resolve through adding dummy transitions into the Petri net, which reflects adding appropriate diagnostic nodes and data transmission in the medical diagnostic service chain in practice.