Resource Allocation in Public Healthcare : A Team-DEA Model

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

13 Scopus Citations
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Author(s)

  • LAI Kin Keung
  • CHEUNG Michael Tow
  • FU Yelin

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)463-472
Journal / PublicationJournal of Systems Science and Complexity
Volume31
Issue number2
Online published21 Mar 2017
Publication statusPublished - Apr 2018

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.

Research Area(s)

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

Citation Format(s)

Resource Allocation in Public Healthcare: A Team-DEA Model. / LAI Kin Keung; CHEUNG Michael Tow; FU Yelin.
In: Journal of Systems Science and Complexity, Vol. 31, No. 2, 04.2018, p. 463-472.

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