Adaptive Behavior of Service Providers to Schedule Deviations and Its Consequences: Evidence from Operating Rooms

Problem definition: We study how clinical teams adaptively respond to real-time deviations from the planned operating room (OR) schedules and the associated consequences of these responses. Specifically, we explore whether clinical personnel adjust their service speed when they are ahead of or behind the original schedule and whether this affects patient reoperation rates. We then analyze the complicated relationships between OR schedules, patient wait times, and reoperations to offer recommendations for achieving the best speed-quality tradeoff. Methodology/results: Our empirical investigation utilizes a unique data set that includes both actual and scheduled surgery timestamps. We construct a dynamic panel model and apply the Arellano-Bond estimator to identify adaptive behavior. We use an instrumental variable approach to address potential endogeneity in estimating the effects of surgical speed and patient wait times on reoperations. The empirical study reveals that surgical and cleaning teams tend to speed up when falling behind schedule and slow down when ahead, with the slowdown effect being more pronounced. Furthermore, the findings indicate that the reoperation rate increases with patient waiting time but decreases with surgical duration. Building on these insights, we model the surgical waitlist as an M/M/1 queue, where the patient returning rate depends on both waiting time and service rate. We use this model to identify how surgery job allowance affects tradeoffs between patient wait time and surgery quality. Managerial implications: The queuing model demonstrates that increasing the average time allowance for surgeries, despite prolonging patient wait times, ultimately decreases reoperation rates under mild assumptions. By varying the time allowance, we derive Pareto curves that illustrate the tradeoffs between reoperation rates and average patient wait times. This provides actionable guidance for surgical departments to schedule their procedures.

Funding: This work was supported by the Natural Sciences and Engineering Research Council of Canada [Grants RGPIN-2019-04398, RGPIN-2019-05539, and RGPIN-2025-05592].

Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0200.