[Different Regions, Differently Insured Populations? Socio-demographic and Health-related Differences Between Insurance Funds]

Gesundheitswesen. 2017 Jan;79(1):e1-e9. doi: 10.1055/s-0035-1564074. Epub 2015 Oct 22.
[Article in German]

Abstract

Objectives: Analyses of health insurance claims data are getting more important in public health and health services research. Since there are several different health insurance funds in Germany, the specific characteristics of regional and socio-demographic population covered by a single fund has to be considered. The aim of this study is to evaluate the differences in socio-demographic and health-related variables between health insurance funds. Methods: This study is based on the GEDA-Study 2009 and 2010, 2 representative cross-sectional telephone surveys (n=42 534). We included socio-economic factors as well as information on area of residence and health-related variables to health status, health behavior and cardiovascular diseases. Results: There are fewer privately insured persons in the eastern regions of Germany. Insurants of the public health insurances have a lower socio-economic status and many have a migration background. Similar results can be found for smoking, obesity and cardiovascular factors. These differences between funds were found in many regional analyses. Conclusions: Especially differences in socio-economic factors are constant between insurance funds and regions. Therefore, the results show that analyses of one single health insurance fund cannot be generalized to the whole population. To ensure precise estimates on health services, morbidity or quality monitoring, we need data sets that integrate more funds.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Cross-Sectional Studies
  • Germany / epidemiology
  • Health Care Rationing / statistics & numerical data*
  • Health Care Surveys
  • Health Services Accessibility / statistics & numerical data*
  • Health Status*
  • Humans
  • Insurance Coverage / statistics & numerical data*
  • Male
  • National Health Programs / statistics & numerical data*
  • Socioeconomic Factors
  • Transients and Migrants / statistics & numerical data*
  • Young Adult