Capacity reallocation via sinking high-quality resource in a hierarchical healthcare system

Document Type

Article

Publication Date

5-1-2021

Abstract

This paper studies the capacity reallocation in a hierarchical medical ecosystem via sinking high-quality resource from high-level hospitals to low-level hospitals. To facilitate the capacity sinking, we develop two payment schemes: fee-for-capacity (FFC) and performance payment (PP). Under the FFC scheme, the low-level hospital always pays a unit capacity sinking price to the high-level hospital, whereas under the PP scheme, the reallocation price is paid contingent on the increased patient visits at the low-level hospital due to capacity sinking. By considering the profit- and utility-maximizing behaviors of strategic parties, we build a four-stage Stackelberg sequential game model within a queuing framework to derive the equilibrium results in terms of the low-level hospital’s capacity, the high-level hospital’s capacity sinking rate, and the funder’s capacity sinking price. In the absence of funder’s coordination, it is shown that any increase in sinking price always reduces the capacity sinking rate. In the presence of funder’s coordination, we find that: (1) the payment schemes under study will not alter the efficiency or coordination of the overall healthcare systems; (2) for the setting with a high perceived value by patients, under each payment scheme, the capacity sinking program is efficient to increase the high-level hospital’s profit and the social welfare as well, but it lowers the patient visit rate at the low-level hospital; (3) for the setting with a higher difference between the patients’ perceived values at the two levels of hospitals, the capacity sinking program is efficient to increase the patient visit rate at the low-level hospital and the social welfare as well, but it sacrifices the high-level hospital’s profit. Finally, numerical studies provide more useful managerial insights.

Identifier

85099918332 (Scopus)

Publication Title

Annals of Operations Research

External Full Text Location

https://doi.org/10.1007/s10479-020-03853-9

e-ISSN

15729338

ISSN

02545330

First Page

97

Last Page

135

Issue

1

Volume

300

Grant

71421001

Fund Ref

National Natural Science Foundation of China

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