Capacity allocation and revenue sharing in healthcare alliances

• Main Authors: GAO, Xiaoquan, WEN, Jianpei, SONG, Jie
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: approximate dynamic programming; large-scale MDP; uncrewed aerial vehicles; dispatching; simulation; Health and Medical Administration; Operations and Supply Chain Management
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/7665; https://ink.library.smu.edu.sg/context/lkcsb_research/article/8664/viewcontent/CapcityAllocation_RS_HA_av.pdf
• Institution: Singapore Management University

This study investigates the operations of a healthcare alliance, where two types of independent hospitals [general hospitals (GHs) and community healthcare centers (CHCs)] collaborate in capacity allocation and revenue management to improve efficiency and revenue. Specifically, the GH allocates part of its capacity to establish a dedicated green channel for referral patients from the CHC based on a negotiated revenue sharing scheme. Generally, independent hospitals, like GHs and CHCs, in the healthcare delivery system provide complementary and substitute services due to the referral process and patients choice. Both service providers need each other, and their collaboration is very beneficial to their own market share. We propose a two-stage game-theoretic approach to study the optimal incentive and coordination mechanisms of the healthcare alliances. In the first-stage cooperative game, two providers negotiate fixed proportion rates to share the revenue from referral patients. In the second-stage non-cooperative game, the GH makes the capacity allocation decision and the CHC decides the treatment threshold to maximize their own revenues. We derive a revenue-sharing scheme that is efficient, in the sense that the decentralized system can achieve the same revenue as the situation where a a central planner manages the alliance. When the capacity of the CHC and the number of patients visiting the CHC for the first diagnosis is large enough, the CHC is willing to take more efforts to treat more patients with alliances. In our study, simulation is employed to analyze the characteristics of the healthcare alliances as a supplement of theoretical analyses and a verification of the revenue-sharing scheme’s feasibility and efficiency. The equilibrium decisions obtained through simulation provides suggestions of much practical value for the operation of healthcare alliances.