Artificial Intelligence (AI)-Enhanced Pretreatment Peer-review Process to Improve Patient Safety in Radiation Oncology

This prospective study will test artificial intelligence (AI) and machine learning (ML) decision support tools. This tool is designed to help doctors, physicists and other staff during pre-treatment peer review, a step where treatment plans are checked before a patient begins care. The system highlights summaries showing how different providers may vary in their treatment planning (provider-variability summaries) and points out the best signals or warning signs to look for (optimal cues). By drawing attention to these patterns and cues, the tool aims to help reviewers spot possible treatment-planning mistakes earlier, reduce the chance of errors, and improve overall patient safety.

NCT Number	NCT07463833
Lead Sponsor	UNC Lineberger Comprehensive Cancer Center Collaborators: Agency for Healthcare Research and Quality (AHRQ)
Conditions	Cancer, Prostate Cancer
Enrollment	207 participants
Start Date	2026-06-22
Primary Completion	2027-07 (estimated)
Study Completion	2027-07 (estimated)
Updated on ClinicalTrials.gov	2026-06-23