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Optimal patient assignment for W queueing network in a diagnostic facility setting

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  • Na Geng
  • Letian Chen
  • Ran Liu
  • Yanhong Zhu

Abstract

Quick examination is becoming increasingly critical for the diagnosis of patients. Increasing demand and insufficient diagnostic facilities lead to longer patient waiting times. It is important for hospital managers to reduce the waiting time of high-priority patients. To reduce the patients’ waiting time, the capacity in working time is divided into special time slots for high-priority patients and regular time slots for all patients. Low-priority patients are allowed to be referred to extra time slots by overtime or using the capacity of other hospitals. Two types of patients and three types of capacities form a W queueing network. This paper proposes an average-cost Markov Decision Process (MDP) model to assign the patients to the appropriate queue with the objective of minimising the weighted waiting cost and referral penalty. Structural properties of the optimal control policy under a given capacity are proved via discount-cost MDP. Extensive numerical experiments are performed to show the efficiency of the proposed patient assignment policy and to explore the impact of different parameters on the control policy.

Suggested Citation

  • Na Geng & Letian Chen & Ran Liu & Yanhong Zhu, 2017. "Optimal patient assignment for W queueing network in a diagnostic facility setting," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5609-5631, October.
  • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:19:p:5609-5631
    DOI: 10.1080/00207543.2017.1324650
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    References listed on IDEAS

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    1. Geng, Na & Xie, Xiaolan, 2012. "Optimizing contracted resource capacity with two advance cancelation modes," European Journal of Operational Research, Elsevier, vol. 221(3), pages 501-512.
    2. J. Michael Harrison & Assaf Zeevi, 2004. "Dynamic Scheduling of a Multiclass Queue in the Halfin-Whitt Heavy Traffic Regime," Operations Research, INFORMS, vol. 52(2), pages 243-257, April.
    3. Jiafu Tang & Yu Wang, 2015. "An adjustable robust optimisation method for elective and emergency surgery capacity allocation with demand uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7317-7328, December.
    4. Alexander Erdelyi & Huseyin Topaloglu, 2009. "Computing protection level policies for dynamic capacity allocation problems by using stochastic approximation methods," IISE Transactions, Taylor & Francis Journals, vol. 41(6), pages 498-510.
    5. Carrie Ka Yuk Lin, 2015. "An adaptive scheduling heuristic with memory for the block appointment system of an outpatient specialty clinic," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7488-7516, December.
    6. Jonathan Patrick & Martin L. Puterman & Maurice Queyranne, 2008. "Dynamic Multipriority Patient Scheduling for a Diagnostic Resource," Operations Research, INFORMS, vol. 56(6), pages 1507-1525, December.
    7. George Steiner & Rui Zhang, 2011. "Revised Delivery-Time Quotation in Scheduling with Tardiness Penalties," Operations Research, INFORMS, vol. 59(6), pages 1504-1511, December.
    8. Chongjun Yan & Jiafu Tang & Bowen Jiang & Richard Y.K. Fung, 2015. "Sequential appointment scheduling considering patient choice and service fairness," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7376-7395, December.
    9. Linda V. Green & Sergei Savin & Ben Wang, 2006. "Managing Patient Service in a Diagnostic Medical Facility," Operations Research, INFORMS, vol. 54(1), pages 11-25, February.
    10. J Patrick & M L Puterman, 2007. "Improving resource utilization for diagnostic services through flexible inpatient scheduling: A method for improving resource utilization," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 235-245, February.
    11. Nan Liu & Serhan Ziya & Vidyadhar G. Kulkarni, 2010. "Dynamic Scheduling of Outpatient Appointments Under Patient No-Shows and Cancellations," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 347-364, September.
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    1. Hao, Yuchen & Liu, Chuang & Zhao, Lugang & Liu, Weibo, 2023. "A dual-clustering algorithm for a robust medical grid partition problem considering patient referral," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).

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