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希腊公共部门初级卫生服务的效率:来自自举DEA/FDH估计量的证据。

Efficiency of Primary Health Services in the Greek Public Sector: Evidence from Bootstrapped DEA/FDH Estimators.

作者信息

Flokou Angeliki, Aletras Vassilis H, Miltiadis Chrysovalantis, Karaferis Dimitris Charalambos, Niakas Dimitris A

机构信息

School of Social Sciences, Hellenic Open University, 26335 Patra, Greece.

Department of Business Administration, University of Macedonia, 54636 Thessaloniki, Greece.

出版信息

Healthcare (Basel). 2024 Nov 8;12(22):2230. doi: 10.3390/healthcare12222230.

DOI:10.3390/healthcare12222230
PMID:39595428
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11593388/
Abstract

Strengthening primary healthcare (PHC) is vital for enhancing efficiency and improving access, clinical outcomes, and population well-being. The World Health Organization emphasizes the role of effective PHC in reducing healthcare costs and boosting productivity. With growing healthcare demands and limited resources, efficient management is critical. Building on this point, this study aimed to evaluate the efficiency of PHC units across Greece, focusing on Health Centers (HCs) and Local Health Units (ToMYs). The objective was to assess their efficiency levels and identify factors contributing to observed inefficiencies. This study explores a novel research area by being the first to assess the efficiency of restructured primary healthcare facilities in Greece, utilizing 2019 data-the first year operational data became available for the newly established ToMY facilities following recent healthcare reforms. We applied a comprehensive suite of non-parametric methods, including Data Envelopment Analysis (DEA) under variable, constant, increasing, and decreasing returns to scale (VRS, CRS, IRS/NDRS, DRS/NIRS) assumptions, along with the Free Disposal Hull (FDH) model, all oriented toward output maximization. Efficiency scores were refined using bootstrapping to calculate 95% confidence intervals, and efficient units were ranked via the super-efficiency model. Outliers were identified and removed through the data cloud algorithm. For the first time at this scale, the final sample included the vast majority of PHC facilities in Greece-234 Health Centers and 94 Local Health Units-with inputs categorized into three human resource types: medical, nursing/paramedical, and administrative/other staff. Outputs encompassed scheduled visits, emergency visits, and pharmaceutical prescription visits. This diverse and comprehensive application of DEA methods represents a novel approach to evaluating PHC efficiency in Greece, with potential relevance to broader healthcare contexts. The analysis revealed significant inefficiencies and differences in technical efficiency between HCs and ToMYs. HCs could nearly double their outputs (VRS score: 1.92), while ToMYs could increase theirs by 58% (VRS score: 1.58). Scale efficiency scores were closer, with HCs slightly more aligned with their optimal scale (1.17 vs. 1.20 for ToMYs). There is significant potential to improve efficiency in PHC, with variations depending on unit characteristics and regional differences. This evaluation provides a foundation for policymakers to identify areas for improvement and enhance the overall performance of healthcare services in Greece.

摘要

加强初级卫生保健(PHC)对于提高效率、改善可及性、临床结局和民众福祉至关重要。世界卫生组织强调有效的初级卫生保健在降低医疗成本和提高生产力方面的作用。随着医疗需求不断增长而资源有限,高效管理至关重要。基于这一点,本研究旨在评估希腊各地初级卫生保健单位的效率,重点关注健康中心(HCs)和地方卫生单位(ToMYs)。目的是评估它们的效率水平,并确定导致观察到的低效率的因素。本研究通过率先评估希腊重组后的初级卫生保健设施的效率,探索了一个新的研究领域,利用2019年的数据——这是最近医疗改革后新成立的ToMY设施可获得的第一年运营数据。我们应用了一套全面的非参数方法,包括在可变、恒定、递增和递减规模报酬(VRS、CRS、IRS/NDRS、DRS/NIRS)假设下的数据包络分析(DEA),以及自由处置壳(FDH)模型,所有这些都以产出最大化为导向。效率得分通过自举法进行细化,以计算95%置信区间,并通过超效率模型对有效单位进行排名。通过数据云算法识别并剔除异常值。在这个规模上首次进行的研究中,最终样本包括了希腊绝大多数的初级卫生保健设施——234个健康中心和94个地方卫生单位——投入分为三类人力资源类型:医疗、护理/辅助医疗和行政/其他工作人员。产出包括预约就诊、急诊就诊和药物处方就诊。DEA方法的这种多样且全面的应用代表了一种评估希腊初级卫生保健效率的新方法,可能与更广泛的医疗背景相关。分析揭示了健康中心和地方卫生单位之间存在显著的低效率以及技术效率差异。健康中心的产出几乎可以翻倍(VRS得分:1.92),而地方卫生单位的产出可以提高58%(VRS得分:...

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