Vrabková Iveta, Lee Sabrina
Department of Public Economics, Faculty of Economics, VSB-Technical University of Ostrava, Sokolská třída 33, 702 00, Ostrava 1, Czech Republic.
Health Econ Rev. 2023 Jan 25;13(1):7. doi: 10.1186/s13561-022-00414-7.
A good health care system and, especially, the provision of efficient hospital care are the goals of national and regional health policies. However, the scope of general hospital care in the 16 federal states in Germany varies considerably from region to region. The objectives of this paper are to evaluate the technical efficiencies of all general hospitals of the 16 federal states for the period from 2015 to 2020, to find out the relation between the exogenous factors and score of efficiency, and also the influence of the COVID-19 pandemic on the results of the technical efficiency of hospital care in the German states.
A two-step approach was used. First, an input-oriented Data Envelopment Analysis model with constant returns to scale and variable returns to scale was applied for the 6-year period from 2015 to 2020. The calculation of technical efficiency according to the input-oriented DEA model contains the three components-total technical efficiency (TTE), pure technical efficiency (PTE) and scale efficiency (SE). In the second stage, the influence of exogenous variables on the previously determined technical efficiency was evaluated by applying the tobit regression analysis.
Although the level of average technical efficiency of about 90% is high, total technical efficiency deteriorated steadily from 2015 to 2020. Its lowest point at around 78%, was in the year 2020. The deterioration of the average technical efficiency is notably influenced by the lower results in the years 2019 and 2020. The decomposition of technical efficiency also revealed that the deterioration of overall average efficiency was influenced by both pure technical efficiency (PTE) and scale efficiency (SE). Based on the tobit regression analysis performed, it was possible to conclude that the change in the efficiency score can be explained by the influence of exogenous factors only from 6.4% for overall efficiency and from 7.1% for scale efficiency.
The results of the analysis of the overall technical efficiency reveal that the aggregated data of all general hospitals of all 16 federal states show a steadily worsening total technical efficiency every year since 2015. Although, especially, the deterioration of the year 2020 with the occurrence of COVID-19 pandemic, contributes to a deteriorated efficiency average, the deterioration of the efficiency values, based on the analysis performed, is also observable between the years 2016 and 2019. Considering the output generated, for inefficient units and the relevant policy authorities in the hospital sector, it can be recommended that the number of beds and in particular the number of physicians, should be reduced as inputs. Based on this study, it is also recommended that decisions to increase the efficiency of general hospitals should be made with consideration of exogenous factors such as the change in the number of general hospitals or the population density in the respective state, as these had explanatory value in connection with the increase in efficiency values. Due to the wide variation in the size of the federal states, the recommendation is more appropriate for federal states with low population density.
一个良好的医疗保健系统，尤其是高效的医院护理服务，是国家和地区卫生政策的目标。然而，德国16个联邦州的综合医院护理范围在不同地区差异很大。本文的目的是评估2015年至2020年期间16个联邦州所有综合医院的技术效率，找出外部因素与效率得分之间的关系，以及新冠疫情对德国各州医院护理技术效率结果的影响。
采用两步法。首先，应用具有规模报酬不变和规模报酬可变的面向投入的数据包络分析模型，对2015年至2020年的6年期间进行分析。根据面向投入的数据包络分析模型计算技术效率，包括三个组成部分——总体技术效率（TTE）、纯技术效率（PTE）和规模效率（SE）。在第二阶段，通过应用托比特回归分析评估外部变量对先前确定的技术效率的影响。
尽管约90%的平均技术效率水平较高，但总体技术效率在2015年至2020年期间稳步下降。其最低点约为78%，出现在2020年。2019年和2020年较低的结果对平均技术效率的下降有显著影响。技术效率的分解还表明，总体平均效率的下降受到纯技术效率（PTE）和规模效率（SE）的共同影响。基于所进行的托比特回归分析，可以得出结论，效率得分的变化仅能由外部因素的影响解释6.4%的总体效率和7.1%的规模效率。
总体技术效率分析结果表明，自2015年以来，16个联邦州所有综合医院的汇总数据显示总体技术效率逐年稳步恶化。尽管特别是2020年新冠疫情的出现导致效率平均水平下降，但根据分析，效率值的恶化在2016年至2019年期间也很明显。考虑到产出情况，对于效率低下的单位以及医院部门的相关政策当局，建议减少床位数量，尤其是医生数量作为投入。基于本研究，还建议在考虑提高综合医院效率的决策时，应考虑外部因素，如各州综合医院数量的变化或人口密度，因为这些因素与效率值的提高具有解释价值。由于联邦州规模差异很大，该建议更适用于人口密度较低的联邦州。
