Abstract
Malignant tumor is a major disease that seriously threatens the health of residents, as one of the vital measures to promote treatment of the tumor, healthcare alliance is widely advocated and adopted. However, conflicting interests between the involved stakeholders in alliance hinder the implementation of healthcare alliance effectively. Based on government intervention, this paper investigated the supply chain of healthcare alliance-patient services at two levels: the tumor healthcare alliance and tumor patients, comprehensive hospitals (CH) and member hospitals (MH) that are low utilized (e.g. Primary Hospitals) within the alliance and respectively constructed the evolutionary game model between the alliance and patients, and between CH and MH to analyze the main influencing factors of the evolutionary strategies and study the optimal coordination mechanisms of the healthcare alliances to achieve the balance of the supply chain of alliance-patient services. Finally, numerical experiments are conducted to further verify the validity and rationality of the model. The results show that: “widen different reimbursement policy”, “increasing government subsidies”, “enhancing the reputational impact of the different strategies of the healthcare alliance” and “reducing the CH’s costs of supporting MH” are effective measures to encourage patients to follow first diagnosis at MH and the CH support the MH to strengthen the ability. In addition, “increasing government subsidies” and “reducing the costs of cooperation” can promote both sides to collaborate with each other. Moreover, the initial strategy probability of stakeholders would affect the evolutionary trajectories. The conclusions provide managerial insights of much practical value for the operation of tumor healthcare alliance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
http://www.360doc.com/content/20/0113/17/19913717_885989219.shtml. Accessed 28 May 2020
Billingsley, K.G., Schwartz, D.L., Lentz, S.: The development of a tele-medical cancer center within the Veterans Affairs Health Care System: a report of preliminary clinical results. Telemed. J. e-Health 8(1), 123–130 (2002)
Gao, Z., Gai, A.L., Zhou, J.: Current situation of cancer prevention and two-way referral under the new rural cooperative medical system in a pilot region of Hubei Province. China Cancer 126(5), 327–332 (2017)
Li, N., Kong, N., Li, Q., Jiang, Z.: Evaluation of reverse referral partnership in a tiered hospital system–a queuing-based approach. Int. J. Prod. Res. 55(19), 5647–5663 (2017)
Li, N., Pan, J., Xie, X.: Operational decision making for a referral coordination alliance- when should patients be referred and where should they be referred to? Omega-Int. J. Manag. Sci. 96, 1–7 (2019)
Wang, J., Li, Z., Shi, J., Chang, A.: Hospital referral and capacity strategies in the two-tier healthcare systems. Omega-Int. J. Manag. Sci., 1–56 (2020)
Gao, X., Wen, J., Song, J.: Simulation study of revenue sharing in healthcare alliances. In: 2018 Winter Simulation Conference (WSC), pp. 2680–2689 (2018)
Gao, X., Wen, J., Song, J.: Capacity allocation and revenue sharing in healthcare alliances. Flex. Serv. Manuf. J. 2, 1–23 (2019)
Chen, L.L., Yu, C.Y., Wei, L.: Analysis of operating mode of regional medical union based on game theory. China Med. Herald 13(21), 131–133 (2016)
Lei, G.H.: Construction of incentive and restraint mechanism of dual-referral: from the age of basic medical care insurance. Chin. Gen. Pract. 16(6A), 1829–1832 (2013)
Lin, Y.F., Zhang, Y.R., Qiu, T.L.: Practice and reflection on close-type medical alliance of oncology department. China Cancer 28(8), 592–595 (2019)
Xu, X.X., Li, Y.M., Lin, Q.Q.: Experience and reflection on the construction of medical alliances in a government and hospital partnership model. Chin. J. Hosp. Admin. 35(11), 903–906 (2019)
Gan, Y.Q., You, M.X., Hu, K.: Reimbursement gap, patient behavior and medical expenses-A three-stage dynamic game analyses. Syst. Eng.-Theory Pract. 34(11), 2794–2983 (2014)
Fuertes, J.N., Toporovsky, A., Reyes, M.: The physician-patient working alliance: theory, research, and future possibilities. Patient Educ. Couns. 100(4), 610–615 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Gao, G., Wu, Z., Wang, S. (2020). The Coordinated Decisions of Service Supply Chain Between Tumor Healthcare Alliance and Patients Under Government Intervention. In: Zhang, Z., Li, W., Du, DZ. (eds) Algorithmic Aspects in Information and Management. AAIM 2020. Lecture Notes in Computer Science(), vol 12290. Springer, Cham. https://doi.org/10.1007/978-3-030-57602-8_51
Download citation
DOI: https://doi.org/10.1007/978-3-030-57602-8_51
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-57601-1
Online ISBN: 978-3-030-57602-8
eBook Packages: Computer ScienceComputer Science (R0)