Journal of Clinical and Translational Science (Jan 2023)

Remote and semi-automated methods to conduct a decentralized randomized clinical trial

  • Teresa Cafaro,
  • Patrick J. LaRiccia,
  • Brigid Bandomer,
  • Helen Goldstein,
  • Tracy L. Brobyn,
  • Krystal Hunter,
  • Satyajeet Roy,
  • Kevin Q. Ng,
  • Ludmil V. Mitrev,
  • Alan Tsai,
  • Denise Thwing,
  • Mary Ann Maag,
  • Myung K. Chung,
  • Noud van Helmond

DOI
https://doi.org/10.1017/cts.2023.574
Journal volume & issue
Vol. 7

Abstract

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Abstract Introduction: Designing and conducting clinical trials is challenging for some institutions and researchers due to associated time and personnel requirements. We conducted recruitment, screening, informed consent, study product distribution, and data collection remotely. Our objective is to describe how to conduct a randomized clinical trial using remote and automated methods. Methods: A randomized clinical trial in healthcare workers is used as a model. A random group of workers were invited to participate in the study through email. Following an automated process, interested individuals scheduled consent/screening interviews. Enrollees received study product by mail and surveys via email. Adherence to study product and safety were monitored with survey data review and via real-time safety alerts to study staff. Results: A staff of 10 remotely screened 406 subjects and enrolled 299 over a 3-month period. Adherence to study product was 87%, and survey data completeness was 98.5% over 9 months. Participants and study staff scored the System Usability Scale 93.8% and 90%, respectively. The automated and remote methods allowed the study maintenance period to be managed by a small study team of two members, while safety monitoring was conducted by three to four team members. Conception of the trial to study completion was 21 months. Conclusions: The remote and automated methods produced efficient subject recruitment with excellent study product adherence and data completeness. These methods can improve efficiency without sacrificing safety or quality. We share our XML file for researchers to use as a template for learning purposes or designing their own clinical trials.

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