Abstract

This article addresses a weekly physician scheduling problem in Covid-19. This problem has arisen in fever clinics in two collaborative hospitals located in Shanghai, China. Because of the coronavirus pandemic, the hospitals must consider some specific constraints in the scheduling problem. For example, due to social distance limitation, the patient queue lengths are much longer in the coronavirus pandemic, even with the same waiting patients. Thus, the hospitals must consider the maximum queue length in the physician scheduling problem. Moreover, the fever clinic’s scheduling rules are different from those in the common clinic, and some specific regulatory constraints have to be considered in the epidemic. We first build a mathematical model for this problem, in which a pointwise stationary fluid flow approximation method is used to compute the queue length. Some linearization techniques are designed to make the problem can be solved by commercial solvers, such as Gurobi. We find that solving this model from practical applications of the hospital within an acceptable computation time is challenging. Consequently, we develop an efficient two-phase approach to solve the problem. A staffing model and a branch-and-price algorithm are proposed in this approach. The performances of our models and approaches are discussed. The effectiveness of the proposed algorithms for real-life data from collaborative hospitals is validated. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article is motivated by our collaborations with two hospitals in Shanghai, China. Covid-19 has swept the world since 2019 and is still raging in many regions, posing an unprecedented challenge to healthcare systems in countries worldwide. The hospitals are the frontlines of healthcare service, and the physicians are the most critical resource in the battles to coronavirus pandemic. In China, many large-scale hospitals establish fever clinics to serve fever patients. The physician scheduling for such clinics is different and complicated in the Covid-19 due to many specific constraints. We find that the managers are tough to give high-quality schedules to physicians. Thus, we propose a set of algorithms to solve this problem. Especially, a two-phase approach that consists of a staffing standard and a branch-and-price algorithm is designed. Based on hospitals’ real-life data, we show that the methods presented in this article can be used to help hospital managers obtain more reasonable scheduling solutions that can improve the service quality without increasing the workloads of physicians.

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