Efficiency assessment of medical diagnostic laboratories using undesirable sustainability indicators: A network data envelopment analysis approach

Document Type : Article

Authors

1 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

3 Department of Industrial Engineering, Faculty of Engineering, KHATAM University, Tehran, Iran

Abstract

Assessing the performance of health systems assists health decision-makers to ensure the accountability for their decisions. Medical diagnostic laboratories are one of the most important and sectors in the healthcare system of all countries. Thus, an assessment of the performance of medical diagnostic laboratories is of particular importance. This paper aims to propose a network data envelopment analysis (NDEA) model to assess the performance of medical diagnostic laboratories and decomposing the efficiency of the system with intricate internal structure based on sustainable development indicators. In addition, the proposed model is designed according to the internal structure of the medical diagnostic laboratory, which includes three main laboratory processes (the pre-test, the test and the post-test) with a combination of additional inputs and outputs (including both desirable and undesirable). The proposed model is a multiplicative DEA approach to estimate and decompose the efficiencies of system. Thus, a heuristic method is used as a suitable solution to convert a multiplicative NDEA approach into an equivalent linear program. The performance proposed model is shown through a real study in Iran. The computational results demonstrate the applicability of the proposed model in determining the most efficient laboratory using undesirable sustainability indicators.

Keywords

References

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Scientia Iranica
Volume 29, Issue 3
Transactions on Industrial Engineering (E)
May and June 2022
Pages 1646-1661

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History

  • Receive Date: 10 May 2019
  • Revise Date: 04 June 2020
  • Accept Date: 20 July 2020

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