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Journal of Healthcare Engineering - Volume 3 2012, Issue 3, Pages 477-502

Research Article

Industrial and Systems Engineering, Russ College of Engineering and Technology, USA

J. Warren McClure School of Information and Telecommunication Systems, Ohio University, Athens, Ohio 45701, USA

Department of Social and Public Health, College of Health Sciences and Professions, Ohio University, Athens, Ohio 45701, USA

College of Science and Engineering, Central State University, Wilberforce, Ohio 45384, USA

Received 1 August 2011; Accepted 1 April 2012

Copyright © 2012 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This article presents a systematic literature review of the application of industrial engineering methods in healthcare scheduling, with a focus on the role of patient behavior in scheduling. Nine articles that used mathematical programming, data mining, genetic algorithms, and local searches for optimum schedules were obtained from an extensive search of literature. These methods are new approaches to solve the problems in healthcare scheduling. Some are adapted from areas such as manufacturing and transportation. Key findings from these studies include reduced time for scheduling, capability of solving more complex problems, and incorporation of more variables and constraints simultaneously than traditional scheduling methods. However, none of these methods modeled no-show and walk-ins patient behavior. Future research should include more variables related to patient and-or environment.

Autor: Maria M. Rinder, Gary Weckman, Diana Schwerha, Andy Snow, Peter A. Dreher, Namkyu Park, Helmut Paschold, and William Young



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