Surgery Scheduling Under Case Cancellation and Surgery Duration Uncertainty

Abstract

Surgery scheduling is of critical importance, because an operating room (OR) is the major cost generating unit in the hospital. However, schedulers face tremendous challenges brought by case cancellation, which have been observed in most departments. On the other hand, the randomness of surgery duration also has a significant impact on an OR schedule. In this paper, we develop a stochastic integer programming model for multiple ORs that simultaneously considers the uncertainties of case cancellation and surgery duration. We aim at minimizing the costs from the perspectives of both health care providers and patients. The Benders decomposition is used to address the computational complexity. A series of experiments is conducted to show the effectiveness of the proposed model and solution approaches. A case study based on two departments at West China Hospital is carried out, where the total cost can be reduced by approximately 27%. A sensitivity analysis is conducted in the case study, from which we gain managerial insights. Note to Practitioners —The effectiveness and efficiency of operating room (OR) scheduling are highly valued by hospital practitioners, as the OR department is one of the most resource-intensive units in a hospital. The uncertainty of surgery duration and patient cancellation in OR scheduling brings a tremendous challenges to the decision makers. We propose a stochastic integer programming model by taking these uncertain factors into consideration. The proposed model significantly outperforms the current practice according to our case study. We also conduct a sensitivity analysis to obtain managerial insights. The value of stochastic solutions is calculated to show the importance of considering both the uncertain factors.