Capacity decisions and revenue sharing in a telemedicine healthcare system

Liangliang Sun (), Miao Yu () and Fenghao Wang ()
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Liangliang Sun: Northeastern University
Miao Yu: Shenyang Jianzhu University
Fenghao Wang: Shenyang Jianzhu University

Journal of Combinatorial Optimization, 2023, vol. 46, issue 5, No 4, 23 pages

Abstract: Abstract This paper studies the operations of a telemedicine service system consisting of independent hospitals [general hospital (GH) and telemedicine firm (TF)]. Through the healthcare alliance, the GH and the TF collaborate in capacity decisions and revenue sharing, and establish a green channel to refer patients. We adopt a two-stage game model to study a revenue sharing scheme of the telemedicine healthcare alliance. In the first-stage the game, the GH and the TF negotiate a revenue-sharing ratio to distribute the revenue of the referred patients. In the second stage game, given the profit-sharing ratio, GH makes capacity allocation decisions, and TF determines its own price to maximize its own revenue. Results show that the revenue sharing scheme can increase profits and promote collaboration between GH and TF. When a large number of mild patients arrive at the GH, the GH tends to participate in the alliance. For the TF, high prices do not always yield high profit under the comprehensive influence of the alliance.

Keywords: Healthcare operation; Telemedicine; Capacity decision; Game theory (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10878-023-01095-6

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