Maximizing the efficiency of residents operating room scheduling: a case study at a teaching hospital

Abstract Paper aims To find efficient operation room scheduling for residents considering several resources constraints and ensuring a minimum number of surgeries for approval in the training program. Originality We find no research in current literature addressing operation room resource allocation for residents training in order to meet legislation approval criteria. Research method The number of procedures to be performed by each resident was defined by Brazilian legislation and by the rules obtained from interviews with the chief professor of a vascular hospital. To solve the allocation of doctors to surgeries planning problem, also addressed in literature as Master Surgical Schedule (MSS), we propose a mathematical programming approach. Main findings The mathematical model showed that some of the current rules of resource availability bring about infeasible planning when trying to achieve the legislation quantitative rules for the residents training. Implications for theory and practice The model allowed the decision maker to plan and schedule vascular surgeries in a better and faster way, through an automated system, instead of allocating residents to surgeries manually, which takes many hours per month. Furthermore, changing the input data in the proposed model can allow other hospitals or specialists to get efficient results in less time.

摘要：
研究目标：本研究旨在解决住院医师手术室调度优化问题，需兼顾多重资源约束，并满足培训项目审批所需的最低手术量要求。
研究创新点：现有文献中尚无针对住院医师培训场景下的手术室资源分配研究，且未兼顾立法审批的量化标准要求。
研究方法：每位住院医师需完成的手术数量，由巴西相关立法文件及某血管外科医院首席教授访谈所得规则共同确定。针对医师手术规划分配问题（即文献中所称的主手术调度（Master Surgical Schedule, MSS）），本文提出一种数学规划求解方法。
核心研究结果：该数学模型显示，当试图满足住院医师培训的立法量化要求时，现行部分资源可用性规则会导致调度方案不可行。
理论与实践启示：相较于每月需耗费数小时的人工住院医师手术分配方式，本模型可通过自动化系统实现更优质、更高效的血管外科手术规划与调度，辅助决策者完成相关工作。此外，通过调整所提模型的输入数据，其他医院或专科从业者亦可在更短时间内获得高效的调度结果。