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Transfer of Clinical Drug Data to a Research Infrastructure on OMOP - A FAIR Concept.
Reinecke, Ines; Zoch, Michéle; Wilhelm, Markus; Sedlmayr, Martin; Bathelt, Franziska.
  • Reinecke I; Institute for Medical Informatics and Biometry at Carl Gustav Carus Faculty of Medicine at Technische Universität Dresden, Germany.
  • Zoch M; Institute for Medical Informatics and Biometry at Carl Gustav Carus Faculty of Medicine at Technische Universität Dresden, Germany.
  • Wilhelm M; Institute for Medical Informatics and Biometry at Carl Gustav Carus Faculty of Medicine at Technische Universität Dresden, Germany.
  • Sedlmayr M; Institute for Medical Informatics and Biometry at Carl Gustav Carus Faculty of Medicine at Technische Universität Dresden, Germany.
  • Bathelt F; Institute for Medical Informatics and Biometry at Carl Gustav Carus Faculty of Medicine at Technische Universität Dresden, Germany.
Stud Health Technol Inform ; 287: 63-67, 2021 Nov 18.
Article in English | MEDLINE | ID: covidwho-1526753
ABSTRACT
Generating evidence based on real-world data is gaining importance in research not least since the COVID-19 pandemic. The Common Data Model of Observational Medical Outcomes Partnership (OMOP) is a research infrastructure that implements FAIR principles. Although the transfer of German claim data to OMOP is already implemented, drug data is an open issue. This paper provides a concept to prepare electronic health record (EHR) drug data for the transfer to OMOP based on requirements analysis and descriptive statistics for profiling EHR data developed by an interdisciplinary team and also covers data quality issues. The concept not only ensures FAIR principles for research, but provides the foundation for German drug data to OMOP transfer.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pharmaceutical Preparations / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2021 Document Type: Article Affiliation country: SHTI210815

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pharmaceutical Preparations / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2021 Document Type: Article Affiliation country: SHTI210815