Volume 23, Issue 2 (6-2020)                   jha 2020, 23(2): 28-39 | Back to browse issues page


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Bahmani A, Mohammadi Bidhandi H. Capacity planning in the hospital queueing network with blocking: simulation-based optimization approach. jha 2020; 23 (2) :28-39
URL: http://jha.iums.ac.ir/article-1-3165-en.html
1- M.Sc. Student, Faculty of Industrial Engineering, Islamic Azad University - South Tehran Branch, Tehran, Iran.
2- Assistant Professor, Faculty of Industrial Engineering, Islamic Azad University - South Tehran Branch, Tehran, Iran. , h_mohammadi@azad.ac.ir
Abstract:   (2397 Views)
Introduction: Hospital administrators have always faced the challenge of providing the best possible health services in a resource-limited environment. The patient flow throughout the hospital is affected by lack of the capacities that can lead to bed-blocking among the hospital units. In this research, the patient flow in the hospital is modeled as an open queueing network with blocking. Then, the hospital capacity planning is implemented to reduce the blocking using a simulation-based optimization approach in such a way that the total cost will not exceed from the accessible budget.
Methods: This research is an applied research in terms of purpose, which is a descriptive-survey research in terms of data collection method. The data were collected during the first six months of the year 1396 in the selected hospital of Lorestan province. The research process is a combination of the bi-objective mathematical modeling and discrete-event simulation.
Results: By analyzing the simulation results of the current situation, 43 scenarios were proposed to improve patient flow in the hospital units. Then, nine Pareto-optimal scenarios were determined by using the mathematical model on the simulation results of the proposed scenarios.
Conclusion: In order to facilitate the selection of the optimal scenario by hospital administrators, the Pareto-optimal scenarios were classified and analyzed in two categories. The integration of the simulation model with the proposed mathematical model can lead to developing a practical approach for capacity planning and improvement of patient flow which can be used by other hospitals.
Full-Text [PDF 1112 kb]   (1028 Downloads)    
Type of Study: Research | Subject: Health Services Management
Received: 2019/12/23 | Accepted: 2020/06/30 | Published: 2020/06/30

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