gms | German Medical Science

Gesundheit – gemeinsam. Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH)

08.09. - 13.09.2024, Dresden

Visualising Data Models of Patient Registries and Clinical Studies – a Method for Quality Check of EDC Systems

Meeting Abstract

  • Beatrice Coldewey - Institute of Medical Informatics, Medical Faculty of RWTH Aachen University, Aachen, Germany
  • Philipp Honrath - Department of Neurology, Epilepsy Section, RWTH Aachen University, Aachen, Germany
  • Stefan Wolking - Department of Neurology, Epilepsy Section, RWTH Aachen University, Aachen, Germany
  • Anna Niemeyer - TMF – Technology, Methods and Infrastructure for Networked Medical Research, Berlin, Germany
  • Rainer Röhrig - Institute of Medical Informatics, Medical Faculty of RWTH Aachen University, Aachen, Germany
  • Yvonne Weber - Department of Neurology, Epilepsy Section, RWTH Aachen University, Aachen, Germany
  • Myriam Lipprandt - Institute of Medical Informatics, Medical Faculty of RWTH Aachen University, Aachen, Germany

Gesundheit – gemeinsam. Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH). Dresden, 08.-13.09.2024. Düsseldorf: German Medical Science GMS Publishing House; 2024. DocAbstr. 6

doi: 10.3205/24gmds013, urn:nbn:de:0183-24gmds0131

Veröffentlicht: 6. September 2024

© 2024 Coldewey et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Introduction: The configuration of electronic data capture (EDC) systems has a relevant impact on data quality in studies and patient registries. The objective was to develop a method to visualise the configuration of an EDC system to check the completeness and correctness of the data definition and rules.

Methods: Step 1: transformation of the EDC data model into a graphical model, step 2: Checking the completeness and consistency of the data model, step 3: correction of identified findings. This process model was evaluated on the patient registry EpiReg.

Results: Using the graphical visualisation as a basis, 21 problems in the EDC configuration were identified, discussed with an interdisciplinary team, and corrected.

Conclusion: The tested methodological approach enables an improvement in data quality by optimising the underlying EDC configuration.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.