[The future development of dementia diseases in Germany-a comparison of different forecast models].
Die zukünftige Entwicklung von Demenzerkrankungen in Deutschland – ein Vergleich unterschiedlicher Prognosemodelle.
Dementia patients
Demographic change
Forecast
Health insurers data
Markov model
Journal
Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
ISSN: 1437-1588
Titre abrégé: Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz
Pays: Germany
ID NLM: 101181368
Informations de publication
Date de publication:
Aug 2019
Aug 2019
Historique:
pubmed:
28
6
2019
medline:
1
8
2019
entrez:
28
6
2019
Statut:
ppublish
Résumé
Dementia is one of the most frequent diseases of people aged 65 and older. As a result of the upcoming demographic transition, a significant increase is expected to the current number of around 1.7 million dementia patients. A precise estimate of this increase is especially important for decision-makers and payers to the health-care system. This study examined the effects of different assumptions on the future frequency of disease using a time-discrete Markov model with population-related and disease-specific components. Based on health insurers' administrative data from AOK Baden-Württemberg, we determined age- and gender-specific prevalence rates, incidence rates, and mortality differences of dementia patients and combined them with demographic components from German population statistics. As a result, our Markov model showed a 20 to 25% higher number of dementia patients in 2030, compared to the results of the status quo projection applied in most previous studies, with the assumption of constant prevalence rates over time. Hence, our results indicate that even in the medium term payers will have to face significant increases in dementia-related health expenditures. By 2060, the number of dementia patients in Germany would rise to 3.3 million assuming a further increase to life expectancy and constant incidence rates over time. The assumption of a compression of the morbidity would reduce this number to 2.6 million.
Identifiants
pubmed: 31243489
doi: 10.1007/s00103-019-02981-3
pii: 10.1007/s00103-019-02981-3
doi:
Types de publication
Comparative Study
Journal Article
Langues
ger
Sous-ensembles de citation
IM