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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

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A comparative study demonstrated that prevalence figures on multimorbidity require cautious interpretation when drawn

Hendrik van den Bussche¹, Ingmar Schäfer, Birgitt Wiese

¹Institute of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, D-20246 Hamburg, Germany. bussche@uke.de

Journal of Clinical Epidemiology

|December 22, 2012

Summary

Comparing chronic disease prevalence in elderly populations across databases reveals significant discrepancies, especially for disease combinations. Conclusions drawn from single databases may be unreliable.

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Area of Science:

Gerontology
Epidemiology
Health Services Research

Background:

Prevalence of chronic diseases and multimorbidity in the elderly is a growing concern.
Accurate data is crucial for effective healthcare planning and resource allocation.
Comparability of different data sources for epidemiological studies is often assumed but not well-established.

Purpose of the Study:

To assess the comparability of chronic disease and multimorbidity prevalence between two distinct elderly patient databases.
To evaluate how differences in data sources impact the reported prevalence of individual diseases and their combinations.
To determine the reliability of conclusions drawn from single databases regarding elderly multimorbidity.

Main Methods:

Comparison of prevalence data from a cohort study (n=3,189) using physician interviews and a German health insurance claims database (n=70,031).
Both databases included elderly patients (65-85 years) and defined multimorbidity by ≥3 chronic conditions from an identical list of 46 diseases.
Analysis focused on individual disease prevalence, median number of conditions, and prevalence of disease combinations (triads, quartets).

Main Results:

Individual disease prevalence was approximately one-third lower in claims data compared to interview data, though rank order was similar.
The median number of chronic conditions differed by 1 (mean 6.7 vs. 5.7).
Prevalence differences for disease combinations were substantial, increasing to nearly 100% for triads and 170% for quartets.

Conclusions:

Significant discrepancies exist in chronic disease and multimorbidity prevalence reporting between chart-supported interviews and claims data.
Small differences in individual disease prevalence accumulate, leading to large divergences when analyzing disease combinations.
Conclusions on the prevalence of complex chronic disease patterns in the elderly should be drawn cautiously when relying on a single data source.