期刊
SCIENTIA IRANICA
卷 29, 期 3, 页码 1646-1661出版社
SHARIF UNIV TECHNOLOGY
DOI: 10.24200/sci.2020.53534.3288
关键词
Network data envelopment analysis; Sustainable development; Medical diagnostic laboratories; Efficiency evaluation; Additional data (desirable and undesirable)
The current study proposed a Network Data Envelopment Analysis (NDEA) model to assess the performance of medical diagnostic laboratories and evaluate the system's efficiency. The model, based on the internal structure of the laboratories, used a multiplicative Data Envelopment Analysis approach and a heuristic method to convert it into an equivalent linear program. The applicability of the proposed model was confirmed in a real study conducted in Iran.
The current study aims to assess the performance of health systems to assist health decision-makers. Medical diagnostic laboratories are one of the most important sectors in the healthcare system of all countries. This is the reason why assessment of the performance of medical diagnostic laboratories is of particular importance. To this end, this study proposed Network Data Envelopment Analysis (NDEA) model to assess the performance of the medical diagnostic laboratories and evaluate the efficiency of the system based on sustainable development indicators. The proposed model was designed based on the internal structure of the medical diagnostic laboratory comprised of three main laboratory processes including the pre-test, test, and post-test with a combination of both desirable and undesirable additional inputs and outputs. The proposed model is a multiplicative Data Envelopment Analysis (DEA) approach used for estimating and decomposing the efficiency of the system under study. In addition, a heuristic method was used as a suitable solution to convert a multiplicative NDEA approach into an equivalent linear program. In this study, the evaluation criteria were obtained using fuzzy TOPSIS-Delphi method. The performance of the proposed model was evaluated in a real study conducted in Iran. The computational results confirmed the applicability of the proposed model in determining the most efficient laboratory based on the undesirable sustainability indicators. (C) 2022 Sharif University of Technology. All rights reserved.
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