Cincinnati Children's AI system reduces patient screening time by 34%

Cincinnati Children's Hospital Medical Center researchers developed an artificial intelligence-powered system that can automatically screen the EHR to identify eligible patients for clinical trials, according to a study published in JMIR Medical Informatics.

The automated clinical trial eligibility screener analyzes EHR data such as patient demographics and clinical assessments as well as information from clinical notes, including the patients' clinical conditions, symptoms and treatments. The data is then matched with eligibility requirements to evaluate whether a patient is suitable for a specific clinical trial.

To test ACTES, researchers integrated it into the clinical research coordinators' workflow in the pediatric emergency department at Cincinnati Children's Hospital Medical Center. During the one-year trial period, the system screened EHR data for the current ED patients and recommended potential candidates for clinical trials.

Results of the trial showed ACTES reduced patient screening time by 34 percent compared to manually screening EHRs. The system also boosted patient enrollment by 11.1 percent and improved the number of patients screened by 14.7 percent.

While ACTES was able to help streamline patient screenings, the research team concluded that the system needs to be tested in other studies because it was only tested in a single clinical department for this study.

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