@inproceedings{437fbfecba434b09ba2178b96122ef9b,
title = "Esource-enabled vs. Traditional clinical trial data collection methods: A site-level economic analysis",
abstract = "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.",
keywords = "Clinical trial, Data collection, ESource, Economic analysis, HL7 FHIR",
author = "Eisenstein, {Eric L.} and Garza, {Maryam Y.} and Mitra Rocca and Gordon, {Gideon S.} and Meredith Zozus",
note = "Publisher Copyright: {\textcopyright} 2020 European Federation for Medical Informatics (EFMI) and IOS Press.; 30th Medical Informatics Europe Conference, MIE 2020 ; Conference date: 28-04-2020 Through 01-05-2020",
year = "2020",
month = jun,
day = "16",
doi = "10.3233/SHTI200304",
language = "English (US)",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "961--965",
editor = "Pape-Haugaard, {Louise B.} and Christian Lovis and Madsen, {Inge Cort} and Patrick Weber and Nielsen, {Per Hostrup} and Philip Scott",
booktitle = "Digital Personalized Health and Medicine - Proceedings of MIE 2020",
}