Università di Siena, Via Roma 56, 53100, Siena, Italy,
Health Care Manag Sci. 2014 Mar;17(1):49-59. doi: 10.1007/s10729-013-9244-0. Epub 2013 Jun 20.
This research aims at supporting hospital management in making prompt Operating Room (OR) planning decisions, when either unpredicted events occur or alternative scenarios or configurations need to be rapidly evaluated. We design and test a planning tool enabling managers to efficiently analyse several alternatives to the current OR planning and scheduling. To this aim, we propose a decomposition approach. More specifically, we first focus on determining the Master Surgical Schedule (MSS) on a weekly basis, by assigning the different surgical disciplines to the available sessions. Next, we allocate surgeries to each session, focusing on elective patients only. Patients are selected from the waiting lists according to several parameters, including surgery duration, waiting time and priority class of the operations. We performed computational experiments to compare the performance of our decomposition approach with an (exact) integrated approach. The case study selected for our simulations is based on the characteristics of the operating theatre (OT) of a medium-size public Italian hospital. Scalability of the method is tested for different OT sizes. A pilot example is also proposed to highlight the usefulness of our approach for decision support. The proposed decomposition approach finds satisfactory solutions with significant savings in computation time.
本研究旨在为医院管理层提供支持,以便在发生意外事件或需要快速评估替代方案或配置时,及时做出手术室(OR)规划决策。我们设计并测试了一种规划工具,使管理人员能够有效地分析当前手术室规划和调度的多种替代方案。为此,我们提出了一种分解方法。更具体地说,我们首先专注于每周确定主手术计划(MSS),通过将不同的外科科室分配到可用的时段来实现。然后,我们专注于仅为择期患者分配手术。根据手术持续时间、等待时间和手术优先级等多个参数,从等候名单中选择患者。我们进行了计算实验,比较了我们的分解方法与(精确)集成方法的性能。我们的模拟案例基于一家中等规模的意大利公立医院手术室的特点。还测试了该方法的可扩展性,以适应不同的手术室规模。还提出了一个试点示例,以突出我们的决策支持方法的有用性。所提出的分解方法找到了令人满意的解决方案,并大大节省了计算时间。