Operational Efficiency of Public Hospitals in Greece During the COVID-19 Pandemic: A Comparative Analysis Using DEA and AHP Models.

Q2 Medicine Journal of market access & health policy Pub Date : 2024-12-10 eCollection Date: 2024-12-01 DOI:10.3390/jmahp12040030

Athanasios Mitakos, Panagiotis Mpogiatzidis

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Abstract

This study evaluates the efficiency of public hospitals in Greece during the COVID-19 epidemic in 2020, using Data Envelopment Analysis (DEA) and the Analytical Hierarchy Process (AHP). Faced with unprecedented pressure from increased demand for medical services, these hospitals had to adapt quickly while playing a crucial role in supporting local economies, similar to the effect of tourism on rural economies. This study reveals that, despite average efficiency scores of 83% for result-oriented models (BCC) and 65% for constant return models (CCR), inefficiencies of scale emerged under the pressures of the pandemic. The AHP, by incorporating qualitative criteria and decision-makers' preferences, offers a valuable perspective but shows little correlation with DEA's quantitative results. This research emphasizes the importance of utilizing integrated methods to formulate a more comprehensive assessment, adapted to the complex challenges of the healthcare sector during crisis periods.

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新冠肺炎大流行期间希腊公立医院运营效率：基于DEA和AHP模型的比较分析

本研究采用数据包络分析（DEA）和层次分析法（AHP）对2020年新冠肺炎疫情期间希腊公立医院的效率进行了评估。面对医疗服务需求增加带来的前所未有的压力，这些医院必须迅速适应，同时在支持地方经济方面发挥关键作用，类似于旅游业对农村经济的影响。这项研究表明，尽管结果导向模型（BCC）的平均效率得分为83%，不变回报模型（CCR）的平均效率得分为65%，但在大流行的压力下，规模效率低下出现了。AHP通过结合定性标准和决策者的偏好，提供了一个有价值的视角，但与DEA的定量结果几乎没有相关性。这项研究强调了利用综合方法制定更全面评估的重要性，以适应危机期间医疗保健部门的复杂挑战。

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