Piloting an automated clinical trial eligibility surveillance and provider alert system based on artificial intelligence and standard data models.

Journal: BMC medical research methodology
Published Date:

Abstract

BACKGROUND: To advance new therapies into clinical care, clinical trials must recruit enough participants. Yet, many trials fail to do so, leading to delays, early trial termination, and wasted resources. Under-enrolling trials make it impossible to draw conclusions about the efficacy of new therapies. An oft-cited reason for insufficient enrollment is lack of study team and provider awareness about patient eligibility. Automating clinical trial eligibility surveillance and study team and provider notification could offer a solution.

Authors

  • Stéphane M Meystre
    Department of Biomedical Informatics, University of Utah, Salt Lake City, USA.
  • Paul M Heider
    Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC, USA.
  • Andrew Cates
    Medical University of South Carolina, Charleston, SC, USA.
  • Grace Bastian
    Medical University of South Carolina, Charleston, SC, USA.
  • Tara Pittman
    Medical University of South Carolina, Charleston, SC, USA.
  • Stephanie Gentilin
    Medical University of South Carolina, Charleston, SC, USA.
  • Teresa J Kelechi
    Medical University of South Carolina, Charleston, SC, USA.