The ILP-based optimization tool improved operating room scheduling efficiency and responsiveness to emergency surgeries in a Naples hospital, enabling dynamic adaptation to unforeseen events with enhanced OR utilization and reduced surgery postponements.
A two-phase ILP-based optimization tool can effectively balance operating room utilization with real-time responsiveness to emergencies and surgery duration variability.
Abstract Effective management of operating rooms ( ORs ) is a challenging yet crucial aspect of ensuring the proper functioning of hospitals. One of the critical issues in ORs management is developing an efficient surgery schedule. This challenge is known in scientific literature as part of the broader Integrated Operating Room Planning and Scheduling ( IORPS ). In its more general form, the IORPS involves making decisions about when and where surgeries should take place, considering various operational issues and constraints, such as resource utilization, patient priority, surgeon and equipment availability, and possible variations in conditions. This work addresses the specific IORPS faced by a hospital in Naples, aiming to balance two contrasting objectives throughout the planning horizon: maximizing OR utilization and accommodating unforeseeable events, such as variations in surgery durations and emergency arrivals. To address these challenges, we propose a two-phases optimization approach. Phase I focuses on designing an efficient and proactive surgery schedule that maximizes ORs utilization while ensuring an adequate responsiveness to unforeseeable events. Phase II reacts to these events, minimizing deviations from the schedule established in Phase I and remaining efficient and responsive throughout the planning horizon. Both phases are developed in an Integer Linear Programming fashion and integrated into an optimization tool. The effectiveness and performance of the proposed approach are validated using real data provided by the hospital. Experimental results demonstrate that our approach could be a valuable resource for supporting surgery department executives.
Boccia et al. (Wed,) conducted a other in Patients requiring elective and emergency surgeries in a surgical department of a hospital in Naples implementing shared operating room policy. Two-phase Integer Linear Programming (ILP)-based online optimization tool for surgery scheduling and re-scheduling vs. Current hospital standard scheduling practice without optimization tool was evaluated on Maximizing operating room utilization while ensuring responsiveness to emergencies and minimizing surgery postponements. The ILP-based optimization tool improved operating room scheduling efficiency and responsiveness to emergency surgeries in a Naples hospital, enabling dynamic adaptation to unforeseen events with enhanced OR utilization and reduced surgery postponements.
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