An Integrated Fuzzy Clustering Cooperative Game Data Envelopment Analysis Model with application in Hospital Efficiency

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  • Hashem Omrani
  • Khatereh Shafaat
  • Ali Emrouznejad

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Hospitals are the main sub-section of health care systems and evaluation of hospitals is one of the most important issue for health policy makers. Data Envelopment Analysis (DEA) is a nonparametric method that has recently been used for measuring efficiency and productivity of Decision Making Units (DMUs) and commonly applied for comparison of hospitals. However, one of the important assumption in DEA is that DMUs must be homogenous. The crucial issue in hospital efficiency is that hospitals are providing different services and so may not be comparable. In this paper, we propose an integrated fuzzy clustering cooperative game DEA approach. In fact, due to the lack of homogeneity among DMUs, we first propose to use a fuzzy C-means technique to cluster the DMUs. Then we apply DEA combined with the game theory where each DMU is considered as a player, using Core and Shapley value approaches within each cluster. The procedure has successfully been applied for performances measurement of 288 hospitals in 31 provinces of Iran. Finally, since the classical DEA model is not capable to distinguish between efficient DMUs, efficient hospitals within each cluster, are ranked using combined DEA model and cooperative game approach. The results show that the Core and Shapley values are suitable for fully ranking of efficient hospitals in the healthcare systems.



Original languageEnglish
Pages (from-to)615-628
JournalExpert Systems with Applications
Early online date31 Jul 2018
Publication statusPublished - 30 Dec 2018

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Creative Commons Attribution 4.0 International (CC BY 4.0)


  • Data Envelopment Analysis, Fuzzy C-means, Core and Shapley value, Hospital efficiency

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