Herr Annika, Lückemann Maximilian, Saric-Babin Amela
Institute of Health Economics (IHE), Leibniz Universität Hannover, CHERH Und CINCH, Königsworther Platz 1, 30167, Hannover, Germany.
CINCH, Universität Duisburg-Essen, Duisburg, Germany.
Eur J Health Econ. 2025 Jul;26(5):757-776. doi: 10.1007/s10198-024-01732-9. Epub 2024 Nov 25.
Approximately 32 percent of individuals aged over 64 years old, with care needs, are residing in nursing homes in Germany. However, this percentage exhibits significant regional disparities, ranging from under 15 percent in certain counties to over 50 percent in others. The purpose of this study is to elucidate the underlying factors explaining this regional variation in nursing home utilization. We employed comprehensive administrative data encompassing the entire elderly care-dependent population and all nursing homes. Our analytical approach involves the use of linear regression models at the county level, accounting for an extensive array of control variables and fixed effects. Additionally, we analyzed regional dependencies by applying spatial lag models. In summary, our model successfully predicts up to 73 percent of the observed regional variation in nursing home utilization. Key factors include care needs, the presence of informal care support and the supply of professional care. Spatial dependencies can be detected but exhibit a minor influence on these variations controlling for care needs. Noteworthy, enabling factors, such as a region's wealth or rurality, have a very limited impact in a country with a generous social insurance system that covers care for those with limited financial resources.
在德国，约32%有护理需求的64岁以上老人居住在养老院。然而，这一比例存在显著的地区差异，某些县低于15%，而其他县则超过50%。本研究的目的是阐明导致养老院利用率地区差异的潜在因素。我们使用了涵盖所有老年护理依赖人群和所有养老院的综合行政数据。我们的分析方法包括在县一级使用线性回归模型，并考虑大量控制变量和固定效应。此外，我们通过应用空间滞后模型分析了地区依赖性。总之，我们的模型成功预测了高达73%的观察到的养老院利用率地区差异。关键因素包括护理需求、非正式护理支持的存在以及专业护理的供应。可以检测到空间依赖性，但在控制护理需求的情况下，其对这些差异的影响较小。值得注意的是，在一个拥有慷慨社会保险制度、为经济资源有限者提供护理的国家，诸如地区财富或农村性质等促成因素的影响非常有限。
