MedicalResearch.com Interview with: Nina Bickell, MD, MPH Associate Director of Community Engaged and Equity Research Co-Leader of the Cancer Prevention and Control Program Co-Director of the Center for Health Equity and Community Engaged Research The Tisch Cancer Institute Icahn School of Medicine at Mount Sinai   MedicalResearch.com: What is the background for this study? Response: Recruiting diverse patients to clinical trials is essential to advance cancer treatments, yet accrual remains low. Efficient recruitment requires the ability identify patients at treatment decision points and determine eligibility for open clinical trials – a time and personnel intensive undertaking. We developed an automated Regular Expressions technology to identify, classify and match patients to clinical trials and overcome the limitations of more resource-intensive technologies like Natural Language Processing (NLP). We created a screener, parser and matcher to: use the electronic health record to identify patients at treatment decision points based on progress notes and imaging reports and classify their cancer type, stage and receptor status; extract and categorize breast, liver and lung cancer trial data based on cancer type, stage, and receptor status from the National Cancer Institute's ClinicalTrials.gov database; pair eligible patients with relevant trials based on stage and receptor status. (more…)