Oncology Trials: A New Approach To Improve Accuracy And Alleviate Burden Associated With Patient Screening
An interview with Flatiron Medical Director Dr. Anosheh Afghahi

In recent years, advancements in targeted therapies have transformed cancer treatment, yet patient recruitment for clinical trials remains a significant challenge, particularly in community oncology. At the ASCO Quality Care Symposium, Flatiron Health unveiled an innovative service designed to enhance patient screening for clinical trials by integrating structured electronic health record (EHR) data with machine learning and human analysis.
Dr. Anosheh Afghahi emphasized the urgent need for improved screening processes, as under 10% of eligible patients currently participate in trials, limiting access to cutting-edge treatments. The new service utilizes structured EHR data to identify potential candidates, applies machine learning to analyze unstructured data, and involves human abstraction to assess medical information, leading to more accurate and efficient candidate selection. This multi-faceted approach not only streamlines the screening process but also aims to increase diversity among trial participants. Initial results indicate substantial reductions in patient pools at each screening stage, suggesting a promising path forward for enhancing trial participation rates. Ongoing collaboration between Flatiron and cancer care sites is pivotal for optimizing the service, which aspires to improve both patient outcomes and representation in oncology research.
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