Details
Original language | English |
---|---|
Number of pages | 20 |
Journal | European Journal of Health Economics |
Early online date | 25 Nov 2024 |
Publication status | E-pub ahead of print - 25 Nov 2024 |
Abstract
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.
Keywords
- C23, I11, I18, Long-term care, Nursing home, Regional variation, Spatial panel data models
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Economics, Econometrics and Finance (miscellaneous)
- Medicine(all)
- Health Policy
Sustainable Development Goals
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In: European Journal of Health Economics, 25.11.2024.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Regional variation in the utilization of nursing home care in Germany
AU - Herr, Annika
AU - Lückemann, Maximilian
AU - Saric-Babin, Amela
N1 - Publisher Copyright: © The Author(s) 2024.
PY - 2024/11/25
Y1 - 2024/11/25
N2 - 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.
AB - 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.
KW - C23
KW - I11
KW - I18
KW - Long-term care
KW - Nursing home
KW - Regional variation
KW - Spatial panel data models
UR - http://www.scopus.com/inward/record.url?scp=85210180814&partnerID=8YFLogxK
U2 - 10.1007/s10198-024-01732-9
DO - 10.1007/s10198-024-01732-9
M3 - Article
AN - SCOPUS:85210180814
JO - European Journal of Health Economics
JF - European Journal of Health Economics
SN - 1618-7598
ER -