Resource Allocation in Public Healthcare : A Team-DEA Model
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 463-472 |
Journal / Publication | Journal of Systems Science and Complexity |
Volume | 31 |
Issue number | 2 |
Online published | 21 Mar 2017 |
Publication status | Published - Apr 2018 |
Link(s)
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.
In: Journal of Systems Science and Complexity, Vol. 31, No. 2, 04.2018, p. 463-472.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review