Esource-enabled vs. Traditional clinical trial data collection methods: A site-level economic analysis

Eric L. Eisenstein, Maryam Y. Garza, Mitra Rocca, Gideon S. Gordon, Meredith Zozus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


Directly extracting data from site electronic health records for updating clinical trial databases (eSource) can reduce site data collection times and errors. We conducted a study to determine clinical trial characteristics that make eSource vs. traditional data collection methods more and less economically attractive. The number of patients a site enrolls, the number of study data elements, study coordinator data collection times, and the percent of study data elements that can be extracted via eSource software all impact eSource economic attractiveness. However, these factors may not impact all clinical trial designs in the same way.

Original languageEnglish (US)
Title of host publicationDigital Personalized Health and Medicine - Proceedings of MIE 2020
EditorsLouise B. Pape-Haugaard, Christian Lovis, Inge Cort Madsen, Patrick Weber, Per Hostrup Nielsen, Philip Scott
PublisherIOS Press
Number of pages5
ISBN (Electronic)9781643680828
StatePublished - Jun 16 2020
Event30th Medical Informatics Europe Conference, MIE 2020 - Geneva, Switzerland
Duration: Apr 28 2020May 1 2020

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Conference30th Medical Informatics Europe Conference, MIE 2020


  • Clinical trial
  • Data collection
  • ESource
  • Economic analysis
  • HL7 FHIR

ASJC Scopus subject areas

  • Health Information Management
  • Health Informatics
  • Biomedical Engineering


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