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Expansion or compression of long-term care in Germany between 2001 and 2009? A small-area decomposition study based on administrative health data
BACKGROUND: Studies state profound cross-country differences in healthy life years and its time trends, suggesting either the health scenario of expansion or compression of morbidity. A much-discussed question in public health research is whether the health scenarios are heterogeneous or homogeneous...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944474/ https://www.ncbi.nlm.nih.gov/pubmed/27418881 http://dx.doi.org/10.1186/s12963-016-0093-1 |
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author | Kreft, Daniel Doblhammer, Gabriele |
author_facet | Kreft, Daniel Doblhammer, Gabriele |
author_sort | Kreft, Daniel |
collection | PubMed |
description | BACKGROUND: Studies state profound cross-country differences in healthy life years and its time trends, suggesting either the health scenario of expansion or compression of morbidity. A much-discussed question in public health research is whether the health scenarios are heterogeneous or homogeneous on the subnational level as well. Furthermore, the question arises whether the morbidity trends or the mortality trends are the decisive drivers of the care need-free life years (CFLY), the life years with care need (CLY), and, ultimately, the health scenarios. METHODS: This study uses administrative census data of all beneficiaries in Germany from the Statutory Long-Term Care Insurance 2001–2009. We compute the CFLY and CLY at age 65+ for 412 counties. The CFLY and CLY gains are decomposed into the effects of survival and of the prevalence of care need, and we investigate their linkages with the health scenarios by applying multinomial regression models. RESULTS: We show an overall increase in CFLY, which is higher for men than for women and higher for severe than for any care need. However, spatial variation in CFLY and in CLY has increased. In terms of the health scenarios, a majority of counties show an expansion of any care need but a compression of severe care need. There is high spatial heterogeneity, with expansion-counties surrounding compression-counties and vice versa, which is mainly caused by divergent trends in the prevalence of care need. We show that mortality is responsible for the absolute changes in CFLY and CLY, while morbidity is the decisive driver that determines the health scenario of a county. CONCLUSION: Combining regionalized administrative data and advanced statistical methods permits a deeper insight into the complex relationship between health and mortality. Our findings demonstrate a compression of life years with severe care need, which however, depends on the region of residence. To attenuate regional inequalities, more efforts are needed that improve health by medical and infrastructural interventions and by the exchange of insights in the efficiency of small- and large-area policy measures between the vanguard and the rearguard counties. In future research, the underlying latent mechanisms should be investigated in more detail. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12963-016-0093-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4944474 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49444742016-07-15 Expansion or compression of long-term care in Germany between 2001 and 2009? A small-area decomposition study based on administrative health data Kreft, Daniel Doblhammer, Gabriele Popul Health Metr Research BACKGROUND: Studies state profound cross-country differences in healthy life years and its time trends, suggesting either the health scenario of expansion or compression of morbidity. A much-discussed question in public health research is whether the health scenarios are heterogeneous or homogeneous on the subnational level as well. Furthermore, the question arises whether the morbidity trends or the mortality trends are the decisive drivers of the care need-free life years (CFLY), the life years with care need (CLY), and, ultimately, the health scenarios. METHODS: This study uses administrative census data of all beneficiaries in Germany from the Statutory Long-Term Care Insurance 2001–2009. We compute the CFLY and CLY at age 65+ for 412 counties. The CFLY and CLY gains are decomposed into the effects of survival and of the prevalence of care need, and we investigate their linkages with the health scenarios by applying multinomial regression models. RESULTS: We show an overall increase in CFLY, which is higher for men than for women and higher for severe than for any care need. However, spatial variation in CFLY and in CLY has increased. In terms of the health scenarios, a majority of counties show an expansion of any care need but a compression of severe care need. There is high spatial heterogeneity, with expansion-counties surrounding compression-counties and vice versa, which is mainly caused by divergent trends in the prevalence of care need. We show that mortality is responsible for the absolute changes in CFLY and CLY, while morbidity is the decisive driver that determines the health scenario of a county. CONCLUSION: Combining regionalized administrative data and advanced statistical methods permits a deeper insight into the complex relationship between health and mortality. Our findings demonstrate a compression of life years with severe care need, which however, depends on the region of residence. To attenuate regional inequalities, more efforts are needed that improve health by medical and infrastructural interventions and by the exchange of insights in the efficiency of small- and large-area policy measures between the vanguard and the rearguard counties. In future research, the underlying latent mechanisms should be investigated in more detail. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12963-016-0093-1) contains supplementary material, which is available to authorized users. BioMed Central 2016-07-13 /pmc/articles/PMC4944474/ /pubmed/27418881 http://dx.doi.org/10.1186/s12963-016-0093-1 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Kreft, Daniel Doblhammer, Gabriele Expansion or compression of long-term care in Germany between 2001 and 2009? A small-area decomposition study based on administrative health data |
title | Expansion or compression of long-term care in Germany between 2001 and 2009? A small-area decomposition study based on administrative health data |
title_full | Expansion or compression of long-term care in Germany between 2001 and 2009? A small-area decomposition study based on administrative health data |
title_fullStr | Expansion or compression of long-term care in Germany between 2001 and 2009? A small-area decomposition study based on administrative health data |
title_full_unstemmed | Expansion or compression of long-term care in Germany between 2001 and 2009? A small-area decomposition study based on administrative health data |
title_short | Expansion or compression of long-term care in Germany between 2001 and 2009? A small-area decomposition study based on administrative health data |
title_sort | expansion or compression of long-term care in germany between 2001 and 2009? a small-area decomposition study based on administrative health data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944474/ https://www.ncbi.nlm.nih.gov/pubmed/27418881 http://dx.doi.org/10.1186/s12963-016-0093-1 |
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