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ACTIVE NOT RECRUITING
NCT06561230

Leveraging EA8191 to Assess AI-Augmented EHR Abstraction

Sponsor: University of Pennsylvania

View on ClinicalTrials.gov

Summary

The goal of this prospective study is to assess the performance of AI (artificial intelligence) augmentation (compared against historical controls) to identify oncology patients who meet inclusion criteria for a clinical trial. The study staff will leverage a natural language processing (NLP)-based AI algorithm that rank-orders patients most likely to meet inclusion criteria for a trial. We hypothesize that this collaborative Human+AI workflow can improve the efficiency, accuracy, and diversity of trial prescreening.

Official title: Leveraging a Penn-based Cancer Trial (EA8191) to Assess the Prospective Performance of Artificial Intelligence Augmented Electronic Health Record (EHR) Data Abstraction for Clinical Trial Patient Screening and Selection

Key Details

Gender

MALE

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

300

Start Date

2025-04-04

Completion Date

2026-08

Last Updated

2026-03-12

Healthy Volunteers

No

Conditions

Interventions

OTHER

Chart review

Patients eligible for prescreening will be identified using structured criteria (e.g., anyone with an appointment in the upcoming 2 months with a relevant provider). All individual charts will be de-identified. De-identified EHRs will then be transferred to Mendel's secure data abstraction platform, where trial eligibility criteria will be abstracted. Patients will be rank-ordered by number of eligibility criteria met, with patients meeting the most eligibility criteria at the top of the queue. The study team will then review eligibility criteria and flag eligible patients.

Locations (1)

University of Pennsylvania

Philadelphia, Pennsylvania, United States