Conducting large-scale epidemiologic studies requires powerful software for electronic data capture, data management, data quality assessments, and participant management. There is also an increasing need to make studies and the data collected findable, accessible, interoperable, and reusable (FAIR). However, reusable software tools from major studies, underlying such needs, are not necessarily known to other researchers.
View Article and Find Full Text PDFThe German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19-74 years were recruited and examined in 18 study centres in Germany.
View Article and Find Full Text PDFBackground: No standards exist for the handling and reporting of data quality in health research. This work introduces a data quality framework for observational health research data collections with supporting software implementations to facilitate harmonized data quality assessments.
Methods: Developments were guided by the evaluation of an existing data quality framework and literature reviews.
Purpose: A less favourable galenic profile of generic formulations of the beta-blocker metoprolol raised the concern of a higher risk for serious cardiovascular (CV) events. We assessed hospital admission rates for CV diseases and prescription prevalences of various drugs using claims data of statutory health insurances (SHIs) to compare the incidence of serious CV events among users of original and generic metoprolol. Index events included hospitalization due to myocardial infarction, hypertensive crisis and stroke.
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