How does age affect the care dependency risk one year after stroke? A study based on claims data from a German health insurance fund.
BACKGROUND
The objective of this study is to investigate the effect of age on care dependency risk 1 year after stroke. Two research questions are addressed: (1) How strong is the association between age and care dependency risk 1 year after stroke and (2) can this association be explained by burden of disease?


METHODS
The study is based on claims data from a German statutory health insurance fund. The study population was drawn from all continuously insured members with principal diagnoses of ischaemic stroke, hemorrhagic stroke, or transient ischaemic attack in 2007 who survived for 1 year after stroke and who were not dependent on care before their first stroke (n = 2864). Data were collected over a 1-year period. People are considered to be dependent on care if they, due to a physical, mental or psychological illness or disability, require substantial assistance in carrying out activities of daily living for a period of at least 6 months. Burden of disease was assessed by stroke subtype, history of stroke, comorbidities as well as geriatric multimorbidity. Regression models were used for data analysis.


RESULTS
21.6 % of patients became care dependent during the observation period. Post-stroke care dependency risk was significantly associated with age. Relative to the reference group (0-65 years), the odds ratio of care dependency was 11.30 (95 % CI: 7.82-16.34) in patients aged 86+ years and 5.10 (95 % CI: 3.88-6.71) in patients aged 76-85 years. These associations were not explained by burden of disease. On the contrary, age effects became stronger when burden of disease was included in the regression model (by between 1.1 and 28 %).


CONCLUSIONS
Our results show that age has an effect on care dependency risk that cannot be explained by burden of disease. Thus, there must be other underlying age-dependent factors that account for the remaining age effects (e.g., social conditions). Further studies are needed to explore the causes of the strong age effects observed.
Department of Medical Sociology and Rehabilitation Science, Charité-Universitätmedizin Berlin, Luisenstr. 57, D-10117, Berlin, Germany. susanne.schnitzer@charite.de.
Susanne
S
Schnitzer
Department of Medical Sociology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, D-20246, Hamburg, Germany. o.knesebeck@uke.de.
Olaf
O
von dem Knesebeck
Central Research Institute of Ambulatory Health Care in Germany, Herbert-Lewin-Platz 3, D-10623, Berlin, Germany. MKohler@zi.de.
Martin
M
Kohler
Department of Structural Advancement and Quality Management in Health Care, Technische Universität Berlin, Steinplatz 2, D-10623, Berlin, Germany. dirk.peschke@tu-berlin.de.
Dirk
D
Peschke
Department of Medical Sociology and Rehabilitation Science, Charité-Universitätmedizin Berlin, Luisenstr. 57, D-10117, Berlin, Germany. adelheid.kuhlmey@charite.de.
Adelheid
A
Kuhlmey
Department of Medical Sociology and Rehabilitation Science, Charité-Universitätmedizin Berlin, Luisenstr. 57, D-10117, Berlin, Germany. liane.schenk@charite.de.
Liane
L
Schenk
D000203:Activities of Daily Living; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D003858:Dependency, Psychological; D005260:Female; D005607:Fraud / Q000191:economics* / Q000639:trends; D005858:Germany / Q000453:epidemiology; D006801:Humans; D007345:Insurance Claim Review / Q000191:economics* / Q000639:trends; D007348:Insurance, Health / Q000191:economics* / Q000639:trends; D008297:Male; D012307:Risk Factors; D020521:Stroke / Q000175:diagnosis / Q000191:economics* / Q000453:epidemiology*