Implementing an automated monitoring process in a digital, longitudinal observational cohort study

Abstract:

Clinical data collection requires correct and complete data sets in order to perform correct statistical analysis and draw valid conclusions. While in randomized clinical trials much effort concentrates on data monitoring, this is rarely the case in observational studies- due to high numbers of cases and often-restricted resources. We have developed a valid and cost-effective monitoring tool, which can substantially contribute to an increased data quality in observational research.

Citation: Arthritis Research & Therapy 23(1):181

Date Published: 2021

URL: https://doi.org/10.1186/s13075-021-02563-2

Registered Mode: imported from a bibtex file

Authors: Lisa Lindner, Anja Weiß, Andreas Reich, Siegfried Kindler, Frank Behrens, Jürgen Braun, Joachim Listing, Georg Schett, Joachim Sieper, Anja Strangfeld, Anne C. Regierer

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Citation
Lindner, L., Weiß, A., Reich, A., Kindler, S., Behrens, F., Braun, J., Listing, J., Schett, G., Sieper, J., Strangfeld, A., & Regierer, A. C. (2021). Implementing an automated monitoring process in a digital, longitudinal observational cohort study. In Arthritis Research & Therapy (Vol. 23, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s13075-021-02563-2
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Created: 21st Jul 2025 at 06:44

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