Simulation optimization for an emergency department healthcare unit in Kuwait

This paper integrates simulation with optimization to design a decision support tool for the operation of an emergency department unit at a governmental hospital in Kuwait. The hospital provides a set of services for different categories of patients. We present a methodology that uses system simulat...

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Bibliographic Details
Published inEuropean journal of operational research Vol. 198; no. 3; pp. 936 - 942
Main Authors Ahmed, Mohamed A., Alkhamis, Talal M.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.11.2009
Elsevier
Elsevier Sequoia S.A
SeriesEuropean Journal of Operational Research
Subjects
Applied sciences
Decision support system
Decision support systems
Decision theory. Utility theory
Design optimization
Exact sciences and technology
Firm modelling
Health services
Health services Stochastic optimization Simulation Decision support system
Hospitals
Impact analysis
Operational research and scientific management
Operational research. Management science
Optimization
Queuing theory. Traffic theory
Simulation
Stochastic optimization
Studies
Workforce planning
Kuwait
Simulation
Decision support system
Stochastic optimization
Health services
Staff management
Health service
Modeling
Waiting time
Optimization
Stochastic programming
Emergency department
Optimal allocation
Budget
Hospital
Service quality
Nurse
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Summary:This paper integrates simulation with optimization to design a decision support tool for the operation of an emergency department unit at a governmental hospital in Kuwait. The hospital provides a set of services for different categories of patients. We present a methodology that uses system simulation combined with optimization to determine the optimal number of doctors, lab technicians and nurses required to maximize patient throughput and to reduce patient time in the system subject to budget restrictions. The major objective of this decision supporting tool is to evaluate the impact of various staffing levels on service efficiency. Experimental results show that by using current hospital resources, the optimization simulation model generates optimal staffing allocation that would allow 28% increase in patient throughput and an average of 40% reduction in patients’ waiting time.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2008.10.025