Gastric esophageal surgery risk analysis with a fault tree and Markov integrated model

Reliability methods have been widely used in risk analysis of medical surgeries. In this study, the authors combine a fault tree with Markov models to assess time independent- and dependent factors together. Dynamics are integrated in the traditional fault tree, and meanwhile the processes of solving Markov are simplified with the modular approach. Continuous time Markov chains are adopted in evaluating the failure probability of a gastric esophageal surgery after categorizing basic events in the fault tree, and a certain time dependent variables, such as failure rate of medical equipment, surgery frequency, and rescue timeliness are involved into risk analysis. A case is studied with data collected from a general hospital, to illustrate the operational process of the proposed method. Results based on the inputs show that taking rescue actions into consideration can reduce the gap between the result of fault tree analysis and the reality. Sensitivity analysis for measuring the impacts of the above time relevant variables is conducted, as well as limitations of the Markov model are discussed.