Document Type : Research Note
Authors
1
esfarayen university of technology
2
Esfarayen University Of Technology, esfarayen, Iran
10.24200/j65.2024.64305.2402
Abstract
Hospitals are one of the key parts of the health system that is responsible for providing services to patients. The optimal allocation of hospital beds is one of the important issues that play a significant role in the financial and clinical performance of hospitals. Therefore, in this article, an algorithm in six main steps, including data collection, simulation, scenario definition, simulation model execution, calculation of the importance degree of output variables, and ranking of scenarios, has been developed using a computer simulation approach and considering the bed-sharing policy among different hospital departments. The main criteria considered in this study include patient rejection (PR), the percentage of resource utilization (RU), and considering the length of the queue (LQ). Due to the nature of uncertainty in the problem, a fuzzy DEMATEL method has been used for ranking scenarios. Finally, the best scenarios have been identified from the total scenarios considered, which can be taken into account by hospital managers in decision-making to improve the overall performance of their medical unit using optimal scenario assumptions. The presented algorithm has been investigated on a case study and its results have been analyzed and reviewed. The considered case study hospital has two inpatient departments. The first department is designated for triage patients and first-type clinic patients, while the second department is for second-type clinic patients. In the conducted case study, the weights of each decision criterion are 0.33, 0.09, 0.27, and 0.30 respectively. A total of 36 scenarios have been defined for the case study. In the end, based on the developed model, scenario number 20 has been chosen as the best scenario. In this scenario, the percentage of patient rejection for triage is 10%, the resource utilization percentage is 70%, and the average number of people waiting in line for first and second-type clinic patients is 19.73 and 1.27, respectively
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