The planning and scheduling of operating rooms: A simulation approach

This paper considers the stochastic off-line planning and on-line scheduling of operating rooms (OR) at the operational level. It studies the problem for a local public hospital that adopts a closed block scheduling strategy for elective surgical cases. Emergency cases have their dedicated ORs; thus are not considered. At the off-line level, the coordinating surgeon of a given department assigns a subset of elective surgeries to each OR of the operating theater (OT). At the on-line level, unless mandated by extraneous factors, a surgical crew performs all surgical cases assigned to the OR, sequencing them in a non-increasing order of their largest expected surgical time. This paper investigates how to enhance the OT's expected under and over utilization while maintaining the current average number of surgical cases in general and of major ones in particular. Specifically, it considers two methods that reduce the over utilization of the OT: canceling surgical cases at the on-line operational level, and limiting the workload planned at the off-line operational level. In addition, it considers three management strategies that monitor and control the flow of surgical cases with the objective of diminishing the variability of OR completion times. These strategies are: transferring a surgical case from a busy OR to a free one, using a single queue for all ORs, and adopting an alternative set up of the OT where surgical cases are separated by type. The paper builds a simulation model for each strategy, and compares the model's output to that of the current situation. It assesses the utility of each strategy based on statistical inferential techniques. Regarding the OR over and under utilization, it is recommended to cancel surgical cases that start after the closing time of the OT. Since this may be difficult to implement, it is advisable to reduce the workload planned at the off-line operational level to 90% of the OT's capacity. Regarding the variability of the OR completion times, it is judicious to adopt a single queue for all surgical cases. When this is infeasible from a technical or a managerial point of view, mixing surgical cases is preferable to separating them by type unless the hospital further decreases the number of minor cases assigned to the OT. Finally, the transfer of the last surgical case from a busy OR to a free one reduces the range of OR completion times. The proposed simulation model can be easily extended to other hospitals and/or to the strategic and tactical managerial levels. It can account for different constraints and/or managerial procedures. It can be used in conjunction with optimization techniques. Its implementation requires limited knowledge of basic simulation techniques while it offers a simple, user friendly, interactive, decision support system that can be used by coordinating surgeons and management. (C) 2014 Elsevier Ltd. All rights reserved.