Enhancing healthcare performance analysis: an empirical validation of the integrated entropy-additive ratio assessment (IEARAS) method

Anil Gurjar and Anupam Ghosh

International Journal of Productivity and Performance Management, 2026, vol. 75, issue 9, 3023-3046

Abstract: PurposeThis study aims to assess and validate the “integrated entropy-additive ratio assessment” (IEARAS) method and demonstrate its robustness in evaluating healthcare system performance. The Charnes, Cooper and Rhodes (CCR) and slacks-based measure (SBM) models used to measure performance (1) assign unequal weights for identical variables across different decision-making units (DMUs); (2) yield an efficiency score of 1 for multiple DMUs; and (3) are sensitive to sample size. These aspects reduce the suitability of data envelopment analysis (DEA) models for assessing performance.Design/methodology/approachTo assess the robustness and validity of the IEARAS method, we simultaneously applied the CCR and SBM models, using three distinct datasets of district hospitals (DHs) from different healthcare systems. The robustness of IEARAS is assessed across the different dataset and variable selection scenarios.FindingsAnalysis and results demonstrate that while DEA models are sensitive to sample size and variable count, the IEARAS method remains consistent and robust across all scenarios. The reliability of IEARAS across various scenarios, with a high value of Kendall's tau and Spearman's rho, further validates that IEARAS proves to be aligned with CCR and SBM and yet can address the limitations of DEA models.Originality/valueEntropy-ARAS integration with CCR and SBM validation has received limited attention. This study advances the methodological literature by proposing a generalizable, non-frontier-based benchmarking framework that reduces sensitivity to sample size and weight variability. Additionally, the IEARAS framework provides policymakers and hospital administrators with a scalable and transferable tool for comparative performance evaluation across regions and healthcare systems, thereby enhancing its generalizability beyond the sampled datasets.

Keywords: ARAS; DEA; Entropy; Healthcare; Performance; SBM-DEA (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijppmp:ijppm-03-2025-0214

DOI: 10.1108/IJPPM-03-2025-0214

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