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Strategic Queueing Behavior of Two Groups of Patients in a Healthcare System

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  • Youxin Liu

    (School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing 210094, China
    Department of Elementary Teaching, Wuhu Institute of Technology, Wuhu 241003, China)

  • Liwei Liu

    (School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing 210094, China)

  • Tao Jiang

    (College of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, China)

  • Xudong Chai

    (School of Mathematics-Physics and Finance, Anhui Polytechnic University, Wuhu 241000, China)

Abstract

Long waiting times and crowded services are the current medical situation in China. Especially in hierarchic healthcare systems, as high-quality medical resources are mainly concentrated in comprehensive hospitals, patients are too concentrated in these hospitals, which leads to overcrowding. This paper constructs a game-theoretical queueing model to analyze the strategic queueing behavior of patients. In such hospitals, patients are divided into first-visit and referred patients, and the hospitals provide patients with two service phases of “diagnosis” and “treatment”. We first obtain the expected sojourn time. By defining the patience level of patients, the queueing behavior of patients in equilibrium is studied. The results suggest that as long as the patients with low patience levels join the queue, the patients with high patience levels also join the queue. As more patients arrive at the hospitals, the queueing behavior of patients with high patience levels may have a negative effect on that of patients with low patience levels. The numerical results also show that the equilibrium behavior deviates from a socially optimal solution; therefore, to reach maximal social welfare, the social planner should adopt some regulatory policies to control the arrival rates of patients.

Suggested Citation

  • Youxin Liu & Liwei Liu & Tao Jiang & Xudong Chai, 2024. "Strategic Queueing Behavior of Two Groups of Patients in a Healthcare System," Mathematics, MDPI, vol. 12(10), pages 1-27, May.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:10:p:1579-:d:1397239
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    References listed on IDEAS

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    1. Qu Qian & Pengfei Guo & Robin Lindsey, 2017. "Comparison of Subsidy Schemes for Reducing Waiting Times in Healthcare Systems," Production and Operations Management, Production and Operations Management Society, vol. 26(11), pages 2033-2049, November.
    2. Ni, Guanqun & Xu, Yinfeng & Dong, Yucheng, 2013. "Price and speed decisions in customer-intensive services with two classes of customers," European Journal of Operational Research, Elsevier, vol. 228(2), pages 427-436.
    3. Ming Hu & Yang Li & Jianfu Wang, 2018. "Efficient Ignorance: Information Heterogeneity in a Queue," Management Science, INFORMS, vol. 64(6), pages 2650-2671, June.
    4. Edelson, Noel M & Hildebrand, David K, 1975. "Congestion Tolls for Poisson Queuing Processes," Econometrica, Econometric Society, vol. 43(1), pages 81-92, January.
    5. Qian, Qu & Zhuang, Weifen, 2017. "Tax/subsidy and capacity decisions in a two-tier health system with welfare redistributive objective," European Journal of Operational Research, Elsevier, vol. 260(1), pages 140-151.
    6. Na Li & Nan Kong & Quanlin Li & Zhibin Jiang, 2017. "Evaluation of reverse referral partnership in a tiered hospital system – A queuing-based approach," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5647-5663, October.
    7. Li, Zhong-Ping & Chang, Aichih (Jasmine) & Zou, Zongbao, 2023. "Design mechanism to coordinate a hierarchical healthcare system: Patient subsidy vs. capacity investment," Omega, Elsevier, vol. 118(C).
    8. Jinting Wang & Ke Sun, 2022. "Optimal pricing and capacity sizing for online service systems with free trials," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 57-86, March.
    9. Jianpei Wen & Hanyu Jiang & Jie Song, 2019. "A Stochastic Queueing Model for Capacity Allocation in the Hierarchical Healthcare Delivery System," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(01), pages 1-24, February.
    10. Zhang, Zhe George & Yin, Xiaoling, 2021. "Information and pricing effects in two-tier public service systems," International Journal of Production Economics, Elsevier, vol. 231(C).
    11. Kim, Seung-Chul & Horowitz, Ira & Young, Karl K. & Buckley, Thomas A., 1999. "Analysis of capacity management of the intensive care unit in a hospital," European Journal of Operational Research, Elsevier, vol. 115(1), pages 36-46, May.
    12. Zhou, Wenhui & Lian, Zhaotong & Wu, Jinbiao, 2014. "When should service firms provide free experience service?," European Journal of Operational Research, Elsevier, vol. 234(3), pages 830-838.
    13. Antonis Economou, 2022. "How much information should be given to the strategic customers of a queueing system?," Queueing Systems: Theory and Applications, Springer, vol. 100(3), pages 421-423, April.
    14. Naor, P, 1969. "The Regulation of Queue Size by Levying Tolls," Econometrica, Econometric Society, vol. 37(1), pages 15-24, January.
    15. Balaraman Rajan & Tolga Tezcan & Abraham Seidmann, 2019. "Service Systems with Heterogeneous Customers: Investigating the Effect of Telemedicine on Chronic Care," Management Science, INFORMS, vol. 65(3), pages 1236-1267, March.
    16. Wenhui Zhou & Weixiang Huang & Vernon N. Hsu & Pengfei Guo, 2023. "On the Benefit of Privatization in a Mixed Duopoly Service System," Management Science, INFORMS, vol. 69(3), pages 1486-1499, March.
    17. Rouba Ibrahim, 2018. "Sharing delay information in service systems: a literature survey," Queueing Systems: Theory and Applications, Springer, vol. 89(1), pages 49-79, June.
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