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The Beat AML® Master Trial is transforming treatment for people with acute myeloid leukemia (AML), already improving survival for patients enrolled in a Beat AML study vs. standard chemotherapy. Read this case study to learn how a proven EHR-to-EDC system has enabled the success of this impactful trial.
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Unlocking the potential of EHR-to-EDC technology in clinical research holds numerous benefits for sponsors, CROs, and sites. This Q&A with Flatiron Health's Senior Product Manager Mariel Boyd explores those benefits, as well as the technology's ability to handle trial-specific and unstructured data.
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To address the urgent need for improved screening processes for oncological clinical trials, Flatiron Health has unveiled an innovative service designed to enhance patient screening by integrating structured EHR data with machine learning and human analysis. In this interview, Anosheh Afghani, Medical Director at Flatiron Health unpacks the methodology behind this service and discusses recent research that supports its impact on efficiency in the screening process.
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EHR adoption has had a massive impact on patient safety, workflow efficiency, and more. Despite these improvements, they haven't lived up to their potential to serve as a potential data source for clinical researchers looking to analyze large datasets. Learn how delegating the bulk of the screening process to specialized health data companies can help unlock the potential of EHR data for clinical research.
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Set your next oncological clinical trials up for success using high-quality real-world data (RWD) to anticipate and confront potential problems early on. Explore how an RWD-backed protocol design can help assess your trial's feasibility, improve patient representation and eligibility, and more.
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This study challenges exclusionary approaches to clinical trials, particularly cancer trials, that underrepresent certain populations, limiting the generalizability of research advancements. It does this by evaluating the effect of broadened eligibility criteria using a nationwide electronic health record-derived de-identified database.
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