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Resource Allocation in Public Healthcare: A Team-DEA Model

LAI Kin Keung*, CHEUNG Michael Tow, FU Yelin

*Corresponding author for this work

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    This paper combines the theory of teams and data envelopment analysis (DEA) to design a mechanism to optimally allocate resources in public healthcare. A statutory authority and the public hospitals under its governance are interpreted as a team, the members of which seek to operate efficiently under the shared institutional constraint that public healthcare is a public good. The individual public hospital exploits DEA to maximize own-payoff, subject to the team-condition that the payoff of each other public hospital does not fall and thereby subtract from the external effects created by the public supply of healthcare. The resulting team-DEA solution, which is shown to be both an individually-efficient and team-satisficing equilibrium and to be computable in terms of a convergent algorithm, can then be applied by the authority to determine the optimal allocation of resources in public healthcare. A case based on Chinese data is presented to illustrate the team-DEA model’s ready operationalization and computation.
    Original languageEnglish
    Pages (from-to)463-472
    JournalJournal of Systems Science and Complexity
    Volume31
    Issue number2
    Online published21 Mar 2017
    DOIs
    Publication statusPublished - Apr 2018

    Research Keywords

    • Data envelopment analysis
    • hospital authority
    • public goods
    • public healthcare
    • resource allocation mechanism
    • teams

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