A Network-Based Formulation for Scheduling Clinical Rotations

• 成果类型: Article
• 署名作者: Cire, Andre A.; Diamant, Adam; Yunes, Tallys; Carrasco, Alejandro
• 署名单位: University of Toronto; University Toronto Scarborough; University of Toronto; York University - Canada
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.12978
• 发表日期: 2019
• 页码: 1186-1205
• 关键词: rotation scheduling; medical training; network-based formulation; optimization; simulation

摘要

We investigate the scheduling practices of a medical school that must assign a cohort of students to a series of clinical rotations, while respecting both operational and quality-of-service requirements. Students become available to start clerkship progressively throughout the year and can complete rotations at hospitals in different geographic regions. Each hospital may offer a subset of the clinical rotations, with different start dates, capacities, and cost rates. We propose a novel network-flow model based on decision diagrams, a graphical structure that compresses the state space of a dynamic program, to model feasible schedules. We demonstrate that our network model has several interesting structural features, is computationally superior as compared to a classical mixed-integer linear program, and can be used to generate useful insights that can aid in managerial decision-making. Using a dataset collected from the American University of the Caribbean, we perform a counterfactual analysis which shows that had our scheduling approach been implemented, a cost reduction of approximately 19% on average could have been achieved. To understand how assignment decisions can affect future costs, we develop a discrete-event simulation of the licensing examination and clerkship scheduling process. We then compare our exact scheduling approach with current practice and achieve an average cost reduction of 25%. We also show that this cost reduction is robust with respect to estimation and forecast uncertainty, specifically, the licensing exam failure rate and the future cohort size.