Grant: PJT PA: ICR - Lev. AI to trans. canc. rese. - AI to accel. Breast Can. Research

Breast cancer is the most common cancer among women in Canada, with approximately 30,000 new diagnoses each year. Many patients are referred to specialized breast centers for assessment, diagnosis, and treatment. These centers manage very high volumes of referrals, and clinic staff must manually review referral letters, imaging reports, and pathology results to decide how urgently each patient needs to be seen. This process is time-consuming, resource-intensive, and can contribute to delays in care. Delays in diagnosis and treatment can increase patient anxiety and may worsen health outcomes, particularly for patients who already face barriers to accessing care, such as those living in rural or underserved communities. There is a need for new tools that can support health care teams to manage referrals more efficiently and fairly. This project will develop and test an automated digital system that uses artificial intelligence to help prioritize breast referrals based on clinical information contained in medical documents. The system will extract key health information and assist clinicians in assigning urgency levels, while maintaining clinical oversight. We will evaluate whether this system can reduce staff workload, shorten wait times for patients, and improve access to timely care. The long-term goal is to create a scalable tool that improves the efficiency, equity, and quality of breast cancer care across Canadian health systems.