Comparing manual and AI-assisted patient screening for heart failure trials
Manual Versus AI-Assisted Clinical Trial Screening Using Large-Language Models
Brigham and Women's Hospital · NCT06588452
This study is testing whether using AI to help screen patients for heart failure trials is better than doing it by hand.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 4500 (estimated) |
| Ages | 18 Years to 90 Years |
| Sex | All |
| Sponsor | Brigham and Women's Hospital (other) |
| Locations | 1 site (Boston, Massachusetts) |
| Trial ID | NCT06588452 on ClinicalTrials.gov |
What this trial studies
This observational study aims to compare the effectiveness of manual patient screening versus AI-assisted screening using large language models for determining eligibility in heart failure clinical trials. Participants will be identified from the Mass General Brigham Electronic Data Warehouse and randomized into either the manual review arm or the AI-assisted review arm. The study seeks to validate the RECTIFIER AI tool, which has shown promise in enhancing the accuracy and efficiency of clinical trial screening by automating data extraction from electronic health records. By addressing the inefficiencies of traditional manual screening, this study could lead to more effective patient enrollment processes.
Who should consider this trial
Good fit: Ideal candidates for this study are individuals with a documented diagnosis of heart failure who have been seen by a Mass General Brigham provider within the last 24 months.
Not a fit: Patients with specific heart failure conditions that exclude them from the study, such as those with LVEF below 50% or above 50% who are intolerant to certain medications, may not benefit.
Why it matters
Potential benefit: If successful, this study could significantly streamline the patient screening process, reducing costs and time while improving enrollment accuracy.
How similar studies have performed: Previous studies have shown success with AI-assisted screening approaches, indicating potential for this method to improve clinical trial processes.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Documented diagnosis of heart failure (e.g., ICD-9 codes 428 ICD-10 codes I50 or Problem list in the electronic health record) * Most recent left ventricular ejection fraction (LVEF) assessed within the past 24 months * Seen Mass General Brigham provider within the last 24 months Exclusion Criteria: * LVEF \<50% currently prescribed or intolerant to an evidence-based beta-blocker, ARNI, MRA, and SGLT2i at least 50% goal dose * LVEF\>50% currently prescribed or intolerant to SGLT2i * Systolic blood pressure (SBP) \<90 mmHg at last measure
Where this trial is running
Boston, Massachusetts
- Brigham and Women's Hospital — Boston, Massachusetts, United States (RECRUITING)
Study contacts
- Study coordinator: Ozan Unlu, MD
- Email: ounlu@bwh.harvard.edu
- Phone: 617-732-7144
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Comparing Manual and AI Patient Screening in Heart Failure