Literature DB >> 23334292

[How "representative" are SHI (statutory health insurance) data? Demographic and social differences and similarities between an SHI-insured population, the population of Lower Saxony, and that of the Federal Republic of Germany using the example of the AOK in Lower Saxony].

J Jaunzeme1, S Eberhard, S Geyer.   

Abstract

Using data obtained from a statutory health insurance (AOK) in the federal state of Lower Saxony, this study examined whether there were differences between the insured population compared with that of Lower Saxony (Niedersachsen) and of Germany with respect to social structural characteristics. Data for the comparisons were provided by the statistical office of Germany, and all datasets were coded according to the same criteria. The differences in gender distribution and age distribution between the AOK, Lower Saxony, and Germany were small. The share of employed individuals among the insured compared with those of Lower Saxony and Germany did not differ for males, but it was lower in women. In the insured population a higher proportion of individuals had lower qualification levels than in Lower Saxony or in Germany; the number of individuals with higher qualifications was, however, sufficient to permit statistical analyses. There were differences in the distributions of social structural characteristics between the health insurance population on the one hand and the populations of Lower Saxony and of Germany on the other. Due to the high number of cases, it is nevertheless possible to analyze associations between social structural variables, health impairments, and patterns of health care utilization.

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Year:  2013        PMID: 23334292     DOI: 10.1007/s00103-012-1626-9

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


  33 in total

1.  Expansion or compression of multimorbidity? 10-year development of life years spent in multimorbidity based on health insurance claims data of Lower Saxony, Germany.

Authors:  Juliane Tetzlaff; Denise Muschik; Jelena Epping; Sveja Eberhard; Siegfried Geyer
Journal:  Int J Public Health       Date:  2017-03-10       Impact factor: 3.380

2.  Adjusting selection bias in German health insurance records for regional prevalence estimation.

Authors:  Ralf Thomas Münnich; Jan Pablo Burgard; Joscha Krause
Journal:  Popul Health Metr       Date:  2019-08-27

3.  Computed Tomography in Germany.

Authors:  Roman Pokora; Lucian Krille; Steffen Dreger; Choonsik Lee; Christian Günster; Hajo Zeeb; Maria Blettner
Journal:  Dtsch Arztebl Int       Date:  2016-10-28       Impact factor: 5.594

4.  Mental health of the adult population in Germany during the COVID-19 pandemic. Rapid Review.

Authors:  Elvira Mauz; Sophie Eicher; Diana Peitz; Stephan Junker; Heike Hölling; Julia Thom
Journal:  J Health Monit       Date:  2022-02-03

5.  Epidemiology and use of compression treatment in venous leg ulcers: nationwide claims data analysis in Germany.

Authors:  Kristina Heyer; Kerstin Protz; Gerd Glaeske; Matthias Augustin
Journal:  Int Wound J       Date:  2016-05-19       Impact factor: 3.315

6.  Are spouses' socio-economic classifications interchangeable? Examining the consequences of a commonly used practice in studies on social inequalities in health.

Authors:  Denise Muschik; Jelena Jaunzeme; Siegfried Geyer
Journal:  Int J Public Health       Date:  2015-10-07       Impact factor: 3.380

7.  The Frequency and Timing of Recurrent Stroke: An Analysis of Routine Health Insurance Data.

Authors:  Jona T Stahmeyer; Sarah Stubenrauch; Siegfried Geyer; Karin Weissenborn; Sveja Eberhard
Journal:  Dtsch Arztebl Int       Date:  2019-10-18       Impact factor: 5.594

8.  Healthcare costs associated with breast cancer in Germany: a claims data analysis.

Authors:  Kristine Kreis; Marika Plöthner; Torben Schmidt; Richard Seufert; Katharina Schreeb; Veronika Jahndel; Sylke Maas; Alexander Kuhlmann; Jan Zeidler; Anja Schramm
Journal:  Eur J Health Econ       Date:  2020-01-02

9.  [Healthcare expenditure and the impact of age: a detailed analysis for survivors and decedents].

Authors:  Jona T Stahmeyer; Sascha Hamp; Jan Zeidler; Sveja Eberhard
Journal:  Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz       Date:  2021-07-13       Impact factor: 1.513

10.  Development of comorbidities in type 2 diabetes between 2005 and 2017 using German claims data.

Authors:  Batoul Safieddine; Stefanie Sperlich; Jelena Epping; Karin Lange; Siegfried Geyer
Journal:  Sci Rep       Date:  2021-05-27       Impact factor: 4.379

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