MedTrace Logo

Assessing the Performance of Artificial Intelligence (AI)-Augmented Electronic Health Record (EHR) Data Abstraction for Clinical Trial Patient Screening

NCT06561217 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 355

Last updated 2025-07-25

Study results available
· View outcomes & findings →

Summary

Identifying eligible patients is a key process in the clinical trial enterprise. Currently, this process relies on time-intensive manual chart review, creating a rate-limiting step for trial participation. The integration of AI technology into the trial screening process has potential to improve participation rates. This study aims to assess the performance (accuracy, efficiency) of AI-augmented patient identification and inform optimal integration into clinical research screening processes.

Conditions

Interventions

OTHER

Chart review

Chart review

Sponsors & Collaborators

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-08-18
Primary Completion
2024-07-12
Completion
2024-07-12

Countries

  • United States

Study Locations

More Related Trials

Entities

Diseases
Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06561217 on ClinicalTrials.gov