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

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.

Methods

To address this need for an automated solution, we conducted an observational pilot study of our TAES (TriAl Eligibility Surveillance) system. We tested the hypothesis that an automated system based on natural language processing and mach

SUBMITTER: Meystre SM 

PROVIDER: S-EPMC10088225 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature