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Facilitating Study and Item Level Browsing for Clinical and Epidemiological COVID-19 Studies.
Schmidt, Carsten Oliver; Darms, Johannes; Shutsko, Aliaksandra; Löbe, Matthias; Nagrani, Rajini; Seifert, Bastian; Lindstädt, Birte; Golebiewski, Martin; Koleva, Sofiya; Bender, Theresa; Bauer, Christian Robert; Sax, Ulrich; Hu, Xiaoming; Lieser, Michael; Junker, Vivien; Klopfenstein, Sophie; Zeleke, Atinkut; Waltemath, Dagmar; Pigeot, Iris; Fluck, Juliane.
  • Schmidt CO; University Medicine of Greifswald.
  • Darms J; ZB MED - Information Centre for Life Sciences.
  • Shutsko A; ZB MED - Information Centre for Life Sciences.
  • Löbe M; University of Leipzig.
  • Nagrani R; Leibniz Institute for Prevention Research and Epidemiology - BIPS.
  • Seifert B; Leibniz Institute for Prevention Research and Epidemiology - BIPS.
  • Lindstädt B; ZB MED - Information Centre for Life Sciences.
  • Golebiewski M; Heidelberg Institute for Theoretical Studies.
  • Koleva S; McGill University Health Centre.
  • Bender T; University Medical Center Göttingen.
  • Bauer CR; University Medical Center Göttingen.
  • Sax U; University Medical Center Göttingen.
  • Hu X; Heidelberg Institute for Theoretical Studies.
  • Lieser M; Heidelberg Institute for Theoretical Studies.
  • Junker V; Heidelberg Institute for Theoretical Studies.
  • Klopfenstein S; Berlin Institute of Health.
  • Zeleke A; University Medicine of Greifswald.
  • Waltemath D; University Medicine of Greifswald.
  • Pigeot I; Leibniz Institute for Prevention Research and Epidemiology - BIPS.
  • Fluck J; ZB MED - Information Centre for Life Sciences.
Stud Health Technol Inform ; 281: 794-798, 2021 May 27.
Article in English | MEDLINE | ID: covidwho-1247808
ABSTRACT
COVID-19 poses a major challenge to individuals and societies around the world. Yet, it is difficult to obtain a good overview of studies across different medical fields of research such as clinical trials, epidemiology, and public health. Here, we describe a consensus metadata model to facilitate structured searches of COVID-19 studies and resources along with its implementation in three linked complementary web-based platforms. A relational database serves as central study metadata hub that secures compatibilities with common trials registries (e.g. ICTRP and standards like HL7 FHIR, CDISC ODM, and DataCite). The Central Search Hub was developed as a single-page application, the other two components with additional frontends are based on the SEEK platform and MICA, respectively. These platforms have different features concerning cohort browsing, item browsing, and access to documents and other study resources to meet divergent user needs. By this we want to promote transparent and harmonized COVID-19 research.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort 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

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort 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