SCIENTIFIC HUB

Follow the evidence.

SCIENTIFIC LITERATURE · MED

Epidemiology of Parkinson's Disease in Germany Between 2016 and 2021 Based on Statutory Health Insurance Claims Data.

Brain Behav · 2025-11-01

DOI: 10.1002/brb3.71027PMID: 41194477

Open accessResearch Support, Non-U.S. Gov't; research-article; Journal ArticleOriginal source ↗

Research overview

The text below is the source article’s original abstract under a verified reuse license. cc by

IntroductionParkinson's disease (PD) is a fast-growing neurodegenerative disease causing a high burden on national health systems. There is a lack of contemporary, reliable epidemiological data for PD in Germany. The aim of this study was to estimate the incidence and prevalence of PD in Germany for the years 2016-2021.MethodsThis is a secondary data analysis of anonymized health claims data from a subset of German statutory health insurances (SHIs) for the years 2016-2021. Data were then extrapolated to represent the full SHI population.ResultsFrom 2016 to 2021, PD prevalence in the study population increased from 494 to 511 patients per 100,000 (p = 0.0067). Incident patients showed no change overall but notably decreased from 2019 to 2020. In contrast, PD prevalence in the extrapolated cohort declined significantly during the same period, dropping from 575 to 501 patients per 100,000 (p ConclusionsPD prevalence increased in the study population but declined in the extrapolated cohort, while incidence remained stable overall in the study population, yet decreased in the extrapolated cohort. This study provides key insights into the epidemiology of PD in Germany, highlighting the influence of methodology and the need for ongoing monitoring to inform healthcare planning.

Scientific assessment

01

Research question

Assess the question within the original study’s scope.

02

Methods & sample

Check the source article for study design and sample details.

03

Key findings

An editorially approved findings summary is not yet published for this record.

04

Limitations

Generalizability, bias and clinical meaning require separate assessment.

Methods, samples and clinical conclusions are not inferred from bibliographic metadata.