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Queueing Models for Patient-Flow Dynamics in Inpatient Wards

Author

Listed:
  • Jing Dong

    (Columbia University Business School, New York, New York 10027)

  • Ohad Perry

    (Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208)

Abstract

Hospital-related queues have unique features that are not captured by standard queueing assumptions, necessitating the development of specialized models. In this paper, we propose a queueing model that takes into account the most salient features of queues associated with patient-flow dynamics in inpatient wards, including the need for a physician’s approval to discharge patients and subsequent discharge delays. In this setting, fundamental quantities, such as the (effective) mean hospitalization time and the traffic intensity, become functions of the queueing model’s primitives. We, therefore, begin by characterizing these quantities and quantifying the impacts that the discharge policy has on the average bed utilization and maximal throughput. We then introduce a deterministic fluid model to approximate the nonstationary patient-flow dynamics. The fluid model is shown to possess a unique periodic equilibrium, which is guaranteed to be approached as time increases so that long-run performance analysis can be carried out by simply considering that equilibrium cycle. Consequently, evaluating the effects of policy changes on the system’s performance and optimizing long-run operating costs are facilitated considerably. The effectiveness of the fluid model is demonstrated via comparisons to data from a large hospital and simulation experiments.

Suggested Citation

  • Jing Dong & Ohad Perry, 2020. "Queueing Models for Patient-Flow Dynamics in Inpatient Wards," Operations Research, INFORMS, vol. 68(1), pages 250-275, January.
    • Handle: RePEc:inm:oropre:v:68:y:2020:i:1:p:250-275
    DOI: 10.1287/opre.2019.1845
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    References listed on IDEAS

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    Cited by:

    1. Noa Zychlinski, 2023. "Applications of fluid models in service operations management," Queueing Systems: Theory and Applications, Springer, vol. 103(1), pages 161-185, February.
    2. Galit B. Yom-Tov & Carri W. Chan, 2021. "Balancing admission control, speedup, and waiting in service systems," Queueing Systems: Theory and Applications, Springer, vol. 97(1), pages 163-219, February.
    3. Masoud Kamalahmadi & Kurt M. Bretthauer & Jonathan E. Helm & Alex F. Mills & Edwin C. Coe & Alisa Judy-Malcolm & Areeba Kara & Julian Pan, 2023. "Mixing It Up: Operational Impact of Hospitalist Caseload and Case-Mix," Management Science, INFORMS, vol. 69(1), pages 283-307, January.
    4. Jinsheng Chen & Jing Dong & Pengyi Shi, 2020. "A survey on skill-based routing with applications to service operations management," Queueing Systems: Theory and Applications, Springer, vol. 96(1), pages 53-82, October.

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