Optimising teams and the outcomes of surgery

Abstract

The outcomes of robotic surgery involve nonlinear interactions of many factors, including patient-related and surgical team-related elements. In robotic surgery, not only the surgeon but also all team members play an important role in determining surgery outcomes. Therefore, it is important to study optimal surgical team configuration decisions. In this study, we investigate regression models for accurate predictions of surgical outcomes by analysing robotic surgery data. We further develop an optimisation model to investigate the optimal team configuration decisions by considering two separate objectives: 1) to minimise the maximum operating room occupation time; 2) to minimise the average operating room occupation time. In our numerical analyses, we compare the optimal team configuration decisions with the current configuration decisions and show that the optimal team allocation decision can result in a 17% decrease in operating room occupation time. Our results suggest that efforts for reducing operating room occupation time should focus on increasing the experience of surgery team members, e.g., via running training programs. [Submitted: 10 September 2018; Accepted: 31 May 2019]