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Estimating the waiting time of multi-priority emergency patients with downstream blocking

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  • Di Lin
  • Jonathan Patrick
  • Fabrice Labeau

Abstract

To characterize the coupling effect between patient flow to access the emergency department (ED) and that to access the inpatient unit (IU), we develop a model with two connected queues: one upstream queue for the patient flow to access the ED and one downstream queue for the patient flow to access the IU. Building on this patient flow model, we employ queueing theory to estimate the average waiting time across patients. Using priority specific wait time targets, we further estimate the necessary number of ED and IU resources. Finally, we investigate how an alternative way of accessing ED (Fast Track) impacts the average waiting time of patients as well as the necessary number of ED/IU resources. This model as well as the analysis on patient flow can help the designer or manager of a hospital make decisions on the allocation of ED/IU resources in a hospital. Copyright The Author(s) 2014

Suggested Citation

  • Di Lin & Jonathan Patrick & Fabrice Labeau, 2014. "Estimating the waiting time of multi-priority emergency patients with downstream blocking," Health Care Management Science, Springer, vol. 17(1), pages 88-99, March.
    • Handle: RePEc:kap:hcarem:v:17:y:2014:i:1:p:88-99
    DOI: 10.1007/s10729-013-9241-3
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    References listed on IDEAS

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    1. Elif Akcali & Murray Côté & Chin Lin, 2006. "A network flow approach to optimizing hospital bed capacity decisions," Health Care Management Science, Springer, vol. 9(4), pages 391-404, November.
    2. Shimshak, Daniel G. & Gropp Damico, Dru & Burden, Hope D., 1981. "A priority queuing model of a hospital pharmacy unit," European Journal of Operational Research, Elsevier, vol. 7(4), pages 350-354, August.
    3. Per Hokstad, 1978. "Approximations for the M / G / m Queue," Operations Research, INFORMS, vol. 26(3), pages 510-523, June.
    4. Lin, Winston T., 1989. "Modeling and forecasting hospital patient movements: Univariate and multiple time series approaches," International Journal of Forecasting, Elsevier, vol. 5(2), pages 195-208.
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    Cited by:

    1. Mohammadi Bidhandi, Hadi & Patrick, Jonathan & Noghani, Pedram & Varshoei, Peyman, 2019. "Capacity planning for a network of community health services," European Journal of Operational Research, Elsevier, vol. 275(1), pages 266-279.
    2. Amir Elalouf & Guy Wachtel, 2022. "Queueing Problems in Emergency Departments: A Review of Practical Approaches and Research Methodologies," SN Operations Research Forum, Springer, vol. 3(1), pages 1-46, March.
    3. Wu, Xiaodan & Li, Juan & Chu, Chao-Hsien, 2019. "Modeling multi-stage healthcare systems with service interactions under blocking for bed allocation," European Journal of Operational Research, Elsevier, vol. 278(3), pages 927-941.
    4. Valentina Klimenok & Alexander Dudin & Vladimir Vishnevsky, 2020. "Priority Multi-Server Queueing System with Heterogeneous Customers," Mathematics, MDPI, vol. 8(9), pages 1-16, September.
    5. Mani Suleiman & Haydar Demirhan & Leanne Boyd & Federico Girosi & Vural Aksakalli, 2022. "Bayesian prediction of emergency department wait time," Health Care Management Science, Springer, vol. 25(2), pages 275-290, June.
    6. Mahmoud, Hussam & Kirsch, Thomas & O'Neil, Dan & Anderson, Shelby, 2023. "The resilience of health care systems following major disruptive events: Current practice and a path forward," Reliability Engineering and System Safety, Elsevier, vol. 235(C).

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