Int. J. of Industrial and Systems Engineering   »   2012 Vol.11, No.4

 

 

Title: A multi-tool integrated methodology for distributed resource allocation in healthcare

 

Authors: Shao-Jen Weng; Teresa Wu; Gerald T. Mackulak; William A. Verdini

 

Addresses:
Department of Industrial Engineering and Enterprise Information, Tunghai University, Box 5-985, Taichung 40799, Taiwan
School of Computing, Informatics, Decision Systems Engineering, Arizona State University, P.O. Box 875906, Tempe, AZ 85287-5906, USA
School of Computing, Informatics, Decision Systems Engineering, Arizona State University, P.O. Box 875906, Tempe, AZ 85287-5906, USA
Department of Supply Chain Management, Arizona State University, P.O. Box 874706, Tempe, AZ 85287-4706, USA

 

Abstract: Resource allocation distributes limited resources among activities so as to achieve certain objectives. Either centralised methods or distributed methods can be applied to such problems. Over the last decade, one emerging research effort evident is to investigate distribution methods due to the inherent decentralised nature of many resource allocation problems. These methods are well suited for production and supply network problems where price functions can be easily derived. However, a healthcare system considers not only the cost function, but also the appropriate level of services to the patient which is usually assessed by an efficiency index. Indeed, the potential cost savings to a healthcare institution are much greater if it is operated as efficiently as possible. Thus this paper focuses on how to make distributed resource allocation decisions among several hospitals aiming to achieve better operational efficiency for each hospital. A bi-level framework, termed multi-tool integrated methodology (MTIM) is proposed. The experimental results indicate that the MTIM is able to locate an optimal staffing configuration for each emergency room from different hospitals which achieves high operational efficiency within the available budget defined by the headquarter.

 

Keywords: healthcare resource allocation; DEA; data envelopment analysis; GAs; genetic algorithms; discrete event simulation; distributed resource allocation; hospitals; operational efficiency; hospital cooperation; optimal staffing; emergency rooms.

 

DOI: 10.1504/IJISE.2012.047545

 

Int. J. of Industrial and Systems Engineering, 2012 Vol.11, No.4, pp.428 - 452

 

Available online: 27 Jun 2012

 

 

Editors Full text accessAccess for SubscribersPurchase this articleComment on this article