Data Quality in Medical Research
Authors: Michael Nonnemacher, Jürgen Stausberg and Daniel Nasseh
Publisher: Medizinisch Wissenschaftliche Verlagsgesellschaft
DOI: 10.32745/9783954663743
Open Access Version | Cite | Download Citation [in German]

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The benefits of cohort studies and registries in patient-oriented collaborative research depend mainly on the quality of the data collected. Health services and quality research depend on scientifically validated methods and procedures to ensure high data quality. This guideline contains corresponding recommendations for the management of data quality in registries, cohort studies, and data repositories. The guideline was developed and refined as part of TMF projects. The 2nd edition provides a significantly more expanded set of indicators than the 1st edition and describes their application using examples for different types of empirical research projects. An up-to-date literature review and analysis round off the guideline. The guideline is, therefore, an important part of the range of measures for improving and ensuring data quality in medical research. It is aimed at those responsible for data management and quality assurance in cohort studies and registries and the heads of corresponding projects.
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Citation
Nonnemacher, M., Stausberg, J., Nasseh, D., Datenqualität in der medizinischen Forschung. Leitlinie zum adaptiven Management von Datenqualität in Kohortenstudien und Registern. 2. Aufl. 2014, Medizinisch Wissenschaftliche Verlagsgesellschaft, Berlin, https://www.mwv-open.de/books/m/10.32745/9783954663743.
2nd, updated and expanded edition, 244 pages, September 2014
€ 59.95 [D], ISBN: 978-3-95466-121-3
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