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Healthcare scheduling in optimization context: a review
Z.A. Abdalkareem, A. Amir, , P. Ekhan, A.I. Hammouri
Published in Springer Science and Business Media Deutschland GmbH
2021
Volume: 11
   
Issue: 3
Pages: 445 - 469
Abstract
This paper offers a summary of the latest studies on healthcare scheduling problems including patients’ admission scheduling problem, nurse scheduling problem, operation room scheduling problem, surgery scheduling problem and other healthcare scheduling problems. The paper provides a comprehensive survey on healthcare scheduling focuses on the recent literature. The development of healthcare scheduling research plays a critical role in optimizing costs and improving the patient flow, providing prompt administration of treatment, and the optimal use of the resources provided and accessible in the hospitals. In the last decades, the healthcare scheduling methods that aim to automate the search for optimal resource management in hospitals by using metaheuristics methods have proliferated. However, the reported results are disintegrated since they solved every specific problem independently, given that there are many versions of problem definition and various data sets available for each of these problems. Therefore, this paper integrates the existing results by performing a comprehensive review and analyzing 190 articles based on four essential components in solving optimization problems: problem definition, formulations, data sets, and methods. This paper summarizes the latest healthcare scheduling problems focusing on patients’ admission scheduling problems, nurse scheduling problems, and operation room scheduling problems considering these are the most common issues found in the literature. Furthermore, this review aims to help researchers to highlight some development from the most recent papers and grasp the new trends for future directions. © 2021, IUPESM and Springer-Verlag GmbH Germany, part of Springer Nature.
About the journal
JournalData powered by TypesetHealth and Technology
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH
ISSN21907188