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Online scheduling for outpatient services with heterogeneous patients and physicians

Author

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  • Huiqiao Su

    (Shanghai Jiao Tong University)

  • Guohua Wan

    (Shanghai Jiao Tong University)

  • Shan Wang

    (Shanghai Jiao Tong University)

Abstract

In outpatient services, it is critical to schedule patients for physicians to reduce both patients waiting and physicians overtime working. In this paper, we regard the problem as an online scheduling problem and based on analysis of a real data set from a big hospital in China, we develop a dynamic programming model to solve the problem. We propose a Policy Iteration Algorithm to find the optimal solution in the steady state, and obtain the structural properties of the policy. We conduct numerical experiments to compare the performance of the policy with that of the two policies used in practice by simulating various scenarios. The numerical results show that the policy has the best performance across all scenarios, especially when the system is heavily loaded. We also discuss the managerial implications of the study for practitioners. The model and solution method can be easily extended to multi-server case and can be applied to the general service scheduling problems with heterogeneous customers and service providers.

Suggested Citation

  • Huiqiao Su & Guohua Wan & Shan Wang, 2019. "Online scheduling for outpatient services with heterogeneous patients and physicians," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 123-149, January.
    • Handle: RePEc:spr:jcomop:v:37:y:2019:i:1:d:10.1007_s10878-017-0216-z
    DOI: 10.1007/s10878-017-0216-z
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    References listed on IDEAS

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    Cited by:

    1. J. Behnamian & Z. Gharabaghli, 2023. "Multi-objective outpatient scheduling in health centers considering resource constraints and service quality: a robust optimization approach," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-35, March.
    2. Jing Fan & Hui Shi, 0. "A three-stage supply chain scheduling problem based on the nursing assistants’ daily work in a hospital," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-13.
    3. Jing Fan & Hui Shi, 2021. "A three-stage supply chain scheduling problem based on the nursing assistants’ daily work in a hospital," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 896-908, November.

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