Welcome to the Empowered Patient Podcast with Karen Jagoda. This show is a window into the latest innovations in applying generative AI, novel therapeutics and vaccines, and the changing dynamics in the medical and healthcare environment. One focus is on how providers, pharmaceutical companies, and payers are empowering patients. In addition, conversations are often about how providers, care facilities, pharmaceutical companies, and payers are being empowered by technology to improve patient outcomes and reduce friction across the healthcare landscape.
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- Virtual and digital health
- Use of AI, ML, and LLM in healthcare and drug discovery, development, trials
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- Precision and stratified medicine
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The audience includes life science leaders, researchers, medical professionals, patient advocates, digital health entrepreneurs, patients, caregivers, healthcare solution providers, students, journalists, and investors.
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Jun 19, 2025
David Sontag, CEO and Co-Founder of Layer Health, describes the environment of chart reviews in healthcare and how AI and large language models can be used to analyze a patient's medical record to extract key clinical details. Applying natural language processing to medical records has been challenging due to the complexity of the language and the longitudinal nature of the data. This large language approach from Layer can enhance clinical decision-making, quality measurement, regulatory compliance, and patient outcomes.
David explains, "Every patient will have experienced a chart review at some point. Whether it's when they've come home from a medical visit and go to their electronic medical record to look at the notes written by their providers. Or it's been experienced in the patient room, in the doctor’s room, watching a clinician review the past medical records to try to get a better context of what's going on with that patient, so that's from the patient’s perspective."
"The same thing happens everywhere else in healthcare. So, chart review is the process of analyzing a patient's medical record to extract key clinical details. You can imagine going through clinical notes, lab results, imaging reports, and medical history, trying to create that complete and accurate picture of the patient's health. And it's used everywhere for measuring quality, for improving the financial performance of health system providers, and for regulatory compliance."
"Some aspects of natural language understanding from patients' medical records have been attempted for well over a decade, and these approaches have been typically very surface-level. So look at a single note, try to answer a relatively simplistic question from that note, but the grand challenge has always been one of how do we mimic the type of reasoning that a physician would do where they would be looking at a patient's longitudinal medical record across many notes trying to piece together data from not just from the unstructured but also the structured data."
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