Development of a Perioperative Medication Suspension Decision Algorithm Based on Bayesian Networks.

In this study, we developed a perioperative drug suspension decision system using a Bayesian network to estimate the appropriate drug suspension period for antithrombotic drugs in the perioperative period. In the past, physicians relied on a vast amount of information in the guidelines to determine the drug suspension period. However, determining the appropriate suspension period was sometimes difficult when competing thrombotic and bleeding risks were present at the time of guideline reference. The proposed method accumulates expert judgments and builds a Bayesian network model based on these data, which successfully demonstrates the estimation of the drug suspension period even in the presence of competing risks. Additionally, a web-application-based interface was created to visually present causal relationships.