“Mayo Clinic clinicians are starting to explore how they might use healthcare-specific large language models – accessed through a generative artificial intelligence chat application – to enhance patient care and improve clinical decisions.
Where ChatGPT and [other LLMs] may only produce relevant, evidence-based answers in healthcare a fraction of the time, California-based Atropos Health said its federated healthcare data network can offer healthcare users detailed, accurate RWE to even the most obscure medical questions because it’s based only on [high-quality] real-world data.”
Dr. Peter Noseworthy, chair of cardiac electrophysiology at Mayo Clinic speaks with Healthcare IT News about their work with Atropos Health and the testing of ChatRWD™. He leads control trials and research using national datasets for the health system. “This is a way to interact with real-world data in real-time and then surface those insights at the point of care,” Noseworthy says.
“We could get at that with clinical trials, but that’s a slow process and patients are highly selected.” Further, he notes, “rare or unusual presentations of disease or rare conditions or rare confluence of conditions are not well characterized in clinical trials, but they’re present in a large data sample.”
Through strategic partnerships with innovative companies like Atropos Health, healthcare organizations like Mayo Clinic can accelerate the adoption of AI-powered platforms to analyze complex data sets and unlock new insights. The collaborative approach with healthcare technology companies who purpose-built technologies for healthcare and are committed to deploying AI responsibly will expand the integration of real-world data into evidence-based precision medicine. By leveraging advanced technologies like Atropos Health’s large language models, clinical decision-making and patient outcomes can be improved.