Volume 3, Issue 3 (10-2020)                   Iran J Health Insur 2020, 3(3): 170-177 | Back to browse issues page

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Moghaddas Z, Vaez-Ghasemi M, Valizadeh Palang Sarae F. Efficiency Evaluation of a Series Network with Output Trade-offs in Data Envelopment Analysis in Hospital Case. Iran J Health Insur. 2020; 3 (3) :170-177
URL: http://journal.ihio.gov.ir/article-1-157-en.html
1- Department of Mathematics and Statistics, Qazvin Branch, Islamic Azad University, Qazvin, Iran , moghaddas.sahar@gmail.com
2- Department of Mathematics, Rasht Branch, Islamic Azad University, Rasht, Iran
3- Department of Industrial Management, Rash Branch, Islamic Azad University, Rasht, Iran
Abstract:   (1560 Views)
Introduction:  Hospitals, as one of the main organizations providing health services, have a special sensitivity and importance in the economy and health. Full attention to the efficiency of the hospital as the largest and most costly operational unit of the health system is of particular importance, so the evaluation of hospitals is one of the most important issues for health policy makers.
Methods: Data Envelopment Analysis (DEA) is a method for evaluating the efficiency and productivity of decision units. If a network is composed of interdependent steps to generate outputs. Therefore, in this study, we have evaluated the relative efficiency of hospitals with output weight constraints for those outputs that have non-linear values. Equivalently, in the cover form, the give-and-take principle is used to take into account the output constraints. In this way, an ascending weight sequence is considered for larger output values of nonlinear value. This study is examined in a secret network. In this study, using the network data envelopment analysis approach, a system performance evaluation model has been designed that considers the relationship between weights as a reliable area in the evaluation.
Results: In this article, the efficiency of 10 hospitals is examined with a new approach, of which only the fourth hospital has obtained an efficiency score of 1. An important feature is the change in the type of classification of efficient and inefficient units in the findings. The results showed that the proposed method is more accurate because by considering nonlinear pricing, it reduces the error that results from linear pricing in evaluations.
Conclusion: The resulting efficient and inefficient units are different from the previous classical methods, so different policies for the units must be considered by managers.
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Type of Study: Research | Subject: General
Received: 2020/09/7 | Revised: 2020/12/23 | Accepted: 2020/12/9 | ePublished: 2020/12/14

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