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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

Overview of attention for article published in Population Health Metrics, July 2016
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2 tweeters

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Title
Expansion or compression of long-term care in Germany between 2001 and 2009? A small-area decomposition study based on administrative health data
Published in
Population Health Metrics, July 2016
DOI 10.1186/s12963-016-0093-1
Pubmed ID
Authors

Daniel Kreft, Gabriele Doblhammer

Abstract

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. 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. 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. 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.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 18%
Unspecified 2 12%
Student > Master 2 12%
Student > Ph. D. Student 2 12%
Student > Bachelor 1 6%
Other 4 24%
Unknown 3 18%
Readers by discipline Count As %
Social Sciences 2 12%
Unspecified 2 12%
Business, Management and Accounting 2 12%
Economics, Econometrics and Finance 2 12%
Computer Science 1 6%
Other 4 24%
Unknown 4 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 July 2016.
All research outputs
#6,702,975
of 11,333,579 outputs
Outputs from Population Health Metrics
#172
of 263 outputs
Outputs of similar age
#131,089
of 266,286 outputs
Outputs of similar age from Population Health Metrics
#6
of 11 outputs
Altmetric has tracked 11,333,579 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 263 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.4. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,286 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.