Mitakos Athanasios, Mpogiatzidis Panagiotis
Department of Midwifery, School of Health Sciences, University of Western Macedonia, 50200 Ptolemaida, Greece;
J Mark Access Health Policy. 2024 Dec 10;12(4):388-402. doi: 10.3390/jmahp12040030. eCollection 2024 Dec.
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.
本研究运用数据包络分析（DEA）和层次分析法（AHP），评估了2020年新冠疫情期间希腊公立医院的效率。面对医疗服务需求增加带来的前所未有的压力，这些医院必须迅速做出调整，同时在支持当地经济方面发挥关键作用，这类似于旅游业对农村经济的影响。该研究表明，尽管以结果为导向的模型（BCC）平均效率得分83%，规模报酬不变模型（CCR）平均效率得分65%，但在疫情压力下仍出现了规模无效率。层次分析法通过纳入定性标准和决策者偏好，提供了一个有价值的视角，但与数据包络分析的定量结果相关性不大。本研究强调了运用综合方法制定更全面评估的重要性，以适应危机时期医疗行业的复杂挑战。
