Evaluating the Performance of Health Supply Chains Using Network Data Envelopment Analysis Model under Uncertainty Conditions in Selected Tehran Hospitals

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Objective
Objective

The objective of this research is to expand the models of Network Data Envelopment Analysis with approaches to uncertainty for evaluating the performance of supply chains.

Method

The method used in this research is descriptive and, in terms of outcome, falls under applied research. From a strategic research perspective, it is descriptive and cross-sectional retrospective based on an analytical approach, conducted through fieldworkand a survey method in the research community. A census method was employed.

Findings

In this study, Razi Hospital, with a score of 0.99, has the highest average efficiency in outpatient services, while Sina Hospital, with a score of 0.139, has the lowest level of average outpatient efficiency among multi-specialty hospitals. Additionally, Yas Hospital, with an average efficiency of 0.99 in inpatient sections, has the highest efficiency, whereas Razi Hospital with a score of 0.58 has the lowest efficiency. Bahrami Hospital among children's hospitals is in a better condition.

Conclusion

Based on the findings of the research, it was determined that the use of the fuzzy Network Data Envelopment Analysis model with variables such as the number of doctors, thenumber of healthcare workers, active beds, total inpatient days, the number of outpatient visits, and the number of inpatients, can compare the performance of selected decision-making units providing services in the studied medical centers from the perspective of inputs and outputs and across the entire health service supply chain. In the long term, it serves as a suitable tool for officials and policymakers of the selected centers for continuous performance evaluation of these services.

Language:
English
Published:
Journal of Innovation Management and Organizational Behavior, Volume:3 Issue: 2, Summer 2023
Pages:
61 to 72
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