Ami Bhatt, MD

Happy Diwali! Come celebrate with me if you are here this afternoon. Fun to end #AHA26 #ScientificSessions26 with a TED talk.

Join me at AHA Scientific Sessions for The Heart of AI: Gen AI in Cardiology, a conversation about how generative AI is shaping clinical practice from supporting busy clinicians to helping patients navigate new tools. Looking forward to joining Dr. Annabelle Volgman, with Dr. Shikha Jain moderating, for this WIMS x Healio AI event on Friday, November 6. Hope to see you there! RSVP: luma.com/66saskzk

Is a consistent sleep schedule important to heart health? #DigitalHealth #WearableHealth #PreventiveCare newsroom.heart.org/news/is-a…

Eligible U.S. healthcare professionals receive 50% off a WHOOP Life annual membership, verified through ID.me. For healthcare professionals managing long shifts, disrupted sleep, and demanding schedules, WHOOP provides continuous insight into key metrics that help you better understand your body and improve your health over time. ⬇️ Get 50% off WHOOP Life ⬇️ whoop.com/us/en/healthcare-p…

Promising findings for women in perimenopause: A new study suggests that creatine combined with twice-weekly resistance training may improve sleep consistency and brain oxygenation. Proud to see WHOOP used to track sleep and menopause-related symptoms in this research! link.springer.com/article/10…

Payers are no longer just financing healthcare. They are starting to compete in it. That's the shift most people are missing. Cardiovascular disease is one of the largest drivers of cost volatility, at a time when overall medical costs are still rising 7 to 8% annually. So payers are doing what the system has not done well: moving earlier. They are investing heavily in predictive analytics, AI-driven risk scoring, and continuous monitoring to identify high-risk patients before events happen. This isn't theoretical. It's a market now valued in the tens of billions and growing fast. And according to a January 2026 Health Affairs study (doi: 10.1377/hlthaff.2025.00897), we are now watching a parallel build-out take shape: payers using AI to accelerate approvals and denials, providers using AI to counter, appeal, and optimize reimbursement, and patients caught in the middle. So here is the uncomfortable truth: we didn't fix the system. We gave both sides faster tools. At the same time, we have never been better at predicting cardiovascular risk. AI can forecast deterioration, stratify populations, and model cost and outcomes at scale. But prediction is no longer the bottleneck. Execution is. The next phase of payer strategy is not about building better models. It is about choosing what kind of system they want to create. One path: AI that scales friction. Faster decisions, faster denials, faster appeals. The other: AI that actually coordinates care, triggers intervention, and prevents events. Because right now, most risk signals go nowhere. They sit in dashboards, disconnected from clinical workflows, incentives, and patient behavior. That is the failure. Not the model. The system. If payers close that gap, they don't just manage cost better. They become the first real infrastructure for preventive, continuous cardiovascular care. If they don't, AI will simply make a fragmented system run faster. Not better.

My eye doctor gave me a cardiovascular risk score from my retinal scan. New data from ACC.26: an AI system analyzing routine eye exam images identified elevated heart disease risk with 91% sensitivity. Matched the standard cardiologist risk calculator. One in four participants had elevated risk. Most did not know. The infrastructure for detection already exists. The question is whether we have built the infrastructure for what comes next. A risk score without a clear pathway is not care. It is a notification. acc.org/About-ACC/Press-Rele…