Literature DB >> 31243489

[The future development of dementia diseases in Germany-a comparison of different forecast models].

Valeska Milan1,2, Stefan Fetzer3.   

Abstract

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.

Entities:  

Keywords:  Dementia patients; Demographic change; Forecast; Health insurers data; Markov model

Mesh:

Year:  2019        PMID: 31243489     DOI: 10.1007/s00103-019-02981-3

Source DB:  PubMed          Journal:  Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz        ISSN: 1436-9990            Impact factor:   1.513


  4 in total

1.  Healing, surviving, or dying? - projecting the German future disease burden using a Markov illness-death model.

Authors:  Valeska Milan; Stefan Fetzer; Christian Hagist
Journal:  BMC Public Health       Date:  2021-01-11       Impact factor: 3.295

2.  Use of a quantitative data report in a hypothetical decision scenario for health policymaking: a computer-assisted laboratory study.

Authors:  Pamela Wronski; Michel Wensing; Sucheta Ghosh; Lukas Gärttner; Wolfgang Müller; Jan Koetsenruijter
Journal:  BMC Med Inform Decis Mak       Date:  2021-01-28       Impact factor: 2.796

3.  Future prevalence of type 2 diabetes-A comparative analysis of chronic disease projection methods.

Authors:  Dina Voeltz; Thaddäus Tönnies; Ralph Brinks; Annika Hoyer
Journal:  PLoS One       Date:  2022-03-07       Impact factor: 3.240

4.  Potential of prevention strategies for the modifiable risk factor type 2 diabetes with relation to the future number of dementia patients in Germany- a multi-state projection through 2040.

Authors:  Anne Fink; Achim Doerre; Ilja Demuth; Gabriele Doblhammer
Journal:  BMC Neurol       Date:  2022-04-26       Impact factor: 2.903

  4 in total

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