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. 2019 Jun 27;4(2):50-63.
doi: 10.25646/5988. eCollection 2019 Jun.

Secondary data in diabetes surveillance - co-operation projects and definition of references on the documented prevalence of diabetes

Christian Schmidt  1 , Christin Heidemann  1 , Alexander Rommel  1 , Ralph Brinks  2 , Heiner Claessen  3   4 , Jochen Dreß  5 , Bernd Hagen  6 , Annika Hoyer  2 , Gunter Laux  7 , Johannes Pollmanns  8 , Maximilian Präger  9   10 , Julian Böhm  9   10 , Saskia Drösler  8 , Andrea Icks  3   4 , Stephanie Kümmel  11 , Christoph Kurz  9   10 , Tatjana Kvitkina  3   4 , Michael Laxy  9   10 , Werner Maier  9   10 , Maria Narres  3   4 , Joachim Szecsenyi  7   11 , Thaddäus Tönnies  2 , Maria Weyermann  8 , Rebecca Paprott  1 , Lukas Reitzle  1 , Jens Baumert  1 , Eleni Patelakis  1 , Thomas Ziese  1
Affiliations

Secondary data in diabetes surveillance - co-operation projects and definition of references on the documented prevalence of diabetes

Christian Schmidt et al. J Health Monit. .

Abstract

In addition to the Robert Koch Institute's health surveys, analyses of secondary data are essential to successfully developing a regular and comprehensive description of the progression of diabetes as part of the Robert Koch Institute's diabetes surveillance. Mainly, this is due to the large sample size and the fact that secondary data are routinely collected, which allows for highly stratified analyses in short time intervals. The fragmented availability of data means that various sources of secondary data are required in order to provide data for the indicators in the four fields of action for diabetes surveillance. Thus, a milestone in the project was to check the suitability of different data sources for their usability and to carry out analyses. Against this backdrop, co-operation projects were specifically funded in the context of diabetes surveillance. This article presents the results that were achieved in co-operation projects between 2016 and 2018 that focused on a range of topics: from evaluating the usability of secondary data to statistically modelling the development of epidemiological indices. Moreover, based on the data of the around 70 million people covered by statutory health insurance, an initial estimate was calculated for the documented prevalence of type 2 diabetes for the years 2010 and 2011. To comparably integrate these prevalences over the years in diabetes surveillance, a reference definition was established with external expertise.

Keywords: DIABETES MELLITUS; DIABETES SURVEILLANCE; EPIDEMIOLOGY; PUBLIC HEALTH; SECONDARY DATA.

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Conflict of interest statement

Conflicts of interest The authors declared no conflicts of interest.

Figures

Figure 1
Figure 1
Data model of diabetes surveillance Own diagram
Figure 2
Figure 2
Hospitalisations and amputations over time (age standardised rates) for diabetes mellitus in Germany according to gender Source: Diagnosis-Related Groups Statistic (DRG statistic) 2005 to 2016
Figure 3
Figure 3
Comparison of the documented prevalence of type 2 diabetes mellitus for the years 2010 and 2011 according to gender Source: Data transparency ordinance data (DaTraV)
See this image and copyright information in PMC

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References

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