A probabilistic projection of beneficiaries of long-term care insurance in Germany by severity of disability

Datos Bibliográficos

ID21378091
AutoresPatrizio Vanella (0000-0002-6736-6774, Leibniz University Hannover, autor de correspondencia), Moritz Hess (0000-0003-4095-6448, University of Bremen), Christina Benita Wilke (0000-0002-2024-3953, FOM University of Applied Sciences for Economics and Management)
Año2020
Volumen54
Número3
Páginas943-974
Fecha de publicación2020-06-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaQuality & Quantity (JOURNAL)
Identificadores de la revistaISSN: 0033-5177 • E-ISSN: 1573-7845
EditorialSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s11135-020-00968-w
OpenAlexW3003157717
IdiomaEN
Citas recibidas5
Referencias citadas33

Demographic aging puts social insurance systems under immense pressure as frailty risks increase with age. The statutory long-term care insurance in Germany (GPV), whose society has been aging for decades due to low fertility and decreasing mortality, faces massive future pressure. The present study presents a stochastic outlook on long-term care insurance in Germany until 2045 by forecasting the future number of frail persons who could claim insurance services by severity level with theory-based Monte Carlo simulations. The simulations result in credible intervals for age-, sex- and severity-specific care rates as well as the numbers of persons for all combinations of age, sex and severity by definition of the GPV on an annual basis. The model accounts for demographic trends through time series analysis and considers all realistic epidemiological developments by simulation. The study shows that increases in the general prevalence of disabilities, especially for severe disabilities, caused by the demographic development in Germany are unavoidable, whereas the influence of changes in age-specific care risks does not affect the outcome significantly. The results may serve as a basis for estimating the future demand for care nurses and the financial expenses of the GPV

Actuarial science · Affect (linguistics) · Economics · Fertility · Political science · Population · Population projection · Probabilistic logic · Sociology · Statutory law · Term (time) · Computer Science · Demography · Global Health Care Issues · Insurance, Mortality, Demography, Risk Management · Medicine · Psychology · Social and Demographic Issues in Germany · Gerontology