How Artificial Intelligence Can Improve Clinical Trial Recruitment
Research By Yizhao Ni, PhD
Post Date: August 12, 2019 | Publish Date: July 25, 2019
Feeling harried when recruiting patients for clinical trials as they visit the hospital emergency department for care? This tool—the Automated Clinical Trial Eligibility Screener© (ACTES)—might improve your odds of success.
Compared to manually screening electronic health records (EHRs) to identify study candidates, this tool reduced patient screening time by 34 percent and improved patient enrollment by 11.1 percent. The system also improved the number of patients screened by 14.7 percent and those approached by 11.1 percent, according to details published online in JMIR Medical Informatics.
“By leveraging natural language processing and machine learning technologies, ACTES was able to quickly analyze different types of data and automatically determine patients’ suitability for clinical trials.”
The software was pilot-tested in 2015. The new study evaluated the tool in real time in a busy emergency department, where clinical research coordinators recruited patients for six pediatric clinical trials.
|Original title:||A Real-Time Automated Patient Screening System for Clinical Trials Eligibility in an Emergency Department: Design and Evaluation|
|Published in:||JMIR Medical Informatics|
|Publish date:||July 25, 2019|