An integrated approach for enhancing operating room management: capacity planning, fair scheduling, and surgeon resilience

弹性(材料科学) 调度(生产过程) 计算理论 运筹学 计算机科学 综合业务规划 能力管理 运营管理 计算机网络 工程类 管理 经济 热力学 物理 程序设计语言
作者
Vahid Kayvanfar,Roberto Baldacci,Kannan Govindan
出处
期刊:Annals of Operations Research [Springer Science+Business Media]
卷期号:350 (3): 1385-1412 被引量:2
标识
DOI:10.1007/s10479-025-06565-0
摘要

Abstract In the realm of operating room management (ORM), several key challenges loom large, including the reduction of overtime and idle time for surgeons, avoiding overutilization and underutilization of ORs, and the equitable allocation of patients to surgeons to mitigate workload pressures. Moreover, the potential disruption risks associated with surgeons can lead to surgery cancellations. This research presents a comprehensive framework for addressing these challenges through a unified approach encompassing capacity planning and equitable scheduling within surgery departments. An essential component of this approach involves the identification of backup surgeons to minimize the surgery cancellations risk attributable to surgeon unavailability. The capacity planning phase is executed in the initial stage, leveraging Markovian queueing systems to optimize resource allocation. In the second stage, a resilient scheduling model is introduced, considering the equitable assignment of patients to surgeons. This scheduling model is developed using a goal programming approach and is solved efficiently using a novel decomposition-based heuristic method designed to expedite the optimal solution attainment. To validate the efficacy of this innovative approach, a real-world case study is undertaken, showcasing its practical application and demonstrating its proficiency in addressing the complex challenges inherent in ORM, followed by some valuable managerial insights. By implementing the proposed approach, the optimal number of operating rooms is obtained from the preceding queueing model in the capacity planning phase, and the effect of changing surgeon numbers is analyzed. Results show that optimizing unit capacity improves surgery scheduling and demonstrates the proposed framework’s efficiency.
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