Self-reported health conditions in the NAKO health study in comparison with claims data of statutory health insurances: Taking cardiovascular and metabolic diseases as an example


Project leadDr. Kathrin Günther

Approval date07.12.2023

Published date10.01.2024

SummarySeveral studies comparing data from self-reported questionnaires and claims data have shown that the level of agreement between the two data sources differs according to diagnosis, patient characteristics, and study design. The German National Cohort (GNC, NAKO health study) is the largest population-based cohort study in Germany providing the option to link primary data to secondary data such as health claims data. The linked dataset will include primary data from baseline and follow-up examinations and claims data from five years prior to the baseline survey as well as additional years of claims data that will be made available in the upcoming years. This will offer several opportunities to evaluate similarities and differences between both data sources and to also consider participant characteristics as well as different diagnosis periods. Claims data, especially those from the outpatient setting, tend to underestimate or overestimate the prevalence of many diseases, depending on the disease condition. Self-reported information may also not always be accurate, partly due to recall and social desirability bias. As planned in the GNC, six patient-reported endpoints will be validated with clinical records or physicians’ data to evaluate new cases and to estimate incidences and deaths. Besides this, many patient-reported endpoints, particularly those prevalent at the time of cohort entry, will be used for confounder adjustment in the GNC. For many conditions a comparison with health claims data may provide valuable insights for determining data sources that are most appropriate to guide endpoint validation processes and to be used for confounder adjustment within the GNC. This study aims to compare the level of agreement and to investigate factors associated with discrepancies between the collected primary data in the GNC and claims data of statutory health insurances, taking cardiovascular and metabolic diseases as an example.

Keywords agreement cardiovascular-diseases claims-data concordance metabolic-diseases primary-data secondary-data

InstitutionsLeibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Leibniz Institut für Präventionsforschung und Epidemiologie - BIPS, Otto-von-Guericke-Universität Magdeburg, Medizinische Fakultät, Institut für Sozialmedizin und Gesundheitsökonomie, Max-Delbrück-Centrum für Molekulare Medizin, Institut für Sozialmedizin und Gesundheitssystemforschung, Otto-von-Guericke-Universität Magdeburg, Max-Delbrück-Centrum für Molekulare Medizin (MDC)

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