AI, Misdiagnoses, and the Unsexy Work that Could Fix Healthcare with Matt Crowson, MD скачать в хорошем качестве

AI, Misdiagnoses, and the Unsexy Work that Could Fix Healthcare with Matt Crowson, MD

In this episode of Promptly Speaking, Sara and Dan speak with Matt Crowson, a fellowship trained ear surgeon who has spent the last decade working at the intersection of clinical medicine, data, and artificial intelligence. Matt explains why diagnostic error is far more common than most patients realize, using ear infections as a powerful and personal case study. He shares how a machine learning model he co-developed at Mass General achieved roughly 95% accuracy in diagnosing pediatric ear infections, compared to the average human accuracy, which is closer to 60 to 70%, and why that gap matters for both everyday care and global health. The conversation goes beyond diagnostics to focus on where AI is already making meaningful progress in healthcare today, particularly in reducing administrative burden through tools like ambient documentation and message triage. Together, they explore the barriers to AI adoption in healthcare, including privacy, liability, fragmented data systems, and regulation, as well as the growing role of clinicians in shaping AI products. The episode closes with practical advice for patients on how generative AI can be used responsibly right now to better understand medical bills, insurance documents, and care options, while acknowledging the real tradeoffs around data privacy and trust. 💡 Topics Covered: Why humans are surprisingly bad at diagnosing common conditions How AI can reduce diagnostic variability without replacing clinicians Pediatric ear infections as a global health problem AI in low-resource and rural healthcare settings Administrative burnout and “pajama time” for clinicians Ambient scribes and inbox triage as early AI wins Payers vs providers and how healthcare actually works Accountability and liability when AI is involved in care Why healthcare AI moves slower than other industries How patients can use generative AI today without over-trusting it ⏱ Timestamps: 00:00 Introduction to ear infections and AI in healthcare 00:44 Meet Matt Crowson: from ENT surgeon to AI advocate 01:36 Payers vs providers and how the healthcare system functions 02:39 AI and administrative burden in clinical work 04:55 Privacy, safety, and regulatory barriers to AI adoption 09:37 What a Chief Medical Officer does in an AI company 13:37 AI in rural healthcare and pediatric ear infection case study 26:35 Accountability and liability in AI-assisted care 26:51 The scalpel analogy and human responsibility 29:57 AI’s potential impact on healthcare costs 30:41 Generative AI and patient empowerment 36:10 What the future of AI in healthcare may realistically look like 36:40 How AI tools are implemented inside hospitals 38:35 Real-world AI deployments and auditing41:14 Vendor and healthcare system partnerships 42:01 Practical advice for patients using generative AI 45:07 Final reflections How to Find Matt: LinkedIn:   / matthewgcrowson   Follow Sara & Dan: Sara:   / saralynneroberts   Dan:   / danroberts27   Email: ⁠[email protected]⁠