Do read this fantastic piece from Andy Slavitt and Toyin Ajayi on why we must not leave out underserved populations from the wave of healthcare AI transformation that is just starting.
From Toyin Ajayi and me. Should AI be used to care for underserved populations? The Guardian piece says no. We say unequivocally yes. https://lnkd.in/gkeg9-U2
Andy Slavitt and Townhall CEO of using AI for care of underserved. Thoughtful piece. We need to continue the work.
From Toyin Ajayi and me. Should AI be used to care for underserved populations? The Guardian piece says no. We say unequivocally yes. https://lnkd.in/gkeg9-U2
Great reminder that bias did not start with AI. Human bias cannot be audited. AI bias can be audited and certainly easier to correct or reduce.... Exciting dialogue...
Here’s a question I think we’ll all be grappling with the implications of in 2026: Should AI be used with low-income populations in a healthcare setting? A few weekends ago, an opinion piece in The Guardian argued that we should not. It argued that the challenges posed by AI, such as algorithmic bias, risk widening the class divide. Martin Cech and I were chatting with Andy Slavitt the other week when he mentioned that he’d answer differently – that we absolutely should be using it in these settings, and it is important that we do so. I was excited to hear that Andy teamed up with Toyin Ajayi to pen a rebuttal to the piece, arguing for the thoughtful implementation of AI in these settings. We’ve published their rebuttal on HTN today at the link below, which also includes a link to the original opinion piece from The Guardian as well: 🔗 https://lnkd.in/g9BYf-zC
🤔A few years ago…we suggested that the AI future in coding was going to be a battle waged between computers with providers using AI to assist in maximizing coding (upcoding) and insurers using AI to use AI to thwart same. ✅The future is today. Now if we could just get ride of doctors and patients we could really get things done! https://lnkd.in/gbfT2z2v
💡 AI is rapidly moving from concept to real-world healthcare transformation. I recently came across this update on AI agents being introduced to support healthcare workflows: 🔗 https://lnkd.in/gCAdfiWW ❓ What really stood out to me is how quickly AI is evolving within healthcare systems. We’re now seeing it move beyond administrative support into areas like: • Identifying patterns in patient data • Supporting early detection of diseases • Enhancing decision-making across workflows It’s honestly both fascinating and a bit surprising to see how AI is beginning to recognize disease patterns—something that traditionally relied heavily on clinical expertise alone. 👉 The real impact of AI lies in how effectively data is leveraged to drive smarter, more timely decisions. But it also raises an important question: Can healthcare professionals fully rely on AI, or should it remain a support tool alongside clinical judgment? From a Healthcare Business Analyst perspective, it’s interesting to see how integrating data, workflows, and technology is shaping more efficient and responsive healthcare systems. #AI #HealthcareAnalytics #BusinessAnalysis #DigitalHealth #DataDriven #HealthcareInnovation
"I believe that physicians won't be replaced by AI, but physicians will be replaced by physicians who see AI as an enabler and thought partner," says Michael Kopko ’09, CEO of Pearl Health. How can #AI empower medical professionals? This CBS alum aims to find out: https://lnkd.in/eJJf8Cx9
Global Conversations 2026 | AI in Healthcare: Governing the Future We Are Building I had the privilege of attending my first Global Conversations session of 2026, where Dr. David Hoffert Director of AI Policy at Epic Systems, the world’s largest Electronic Health Records provider, He led this intellectually practically grounded discussions on AI policy in Health care Four themes stood out. First, AI’s real value in healthcare is not robot doctors. It is restoring the human dimension of medicine. AI scribing tools that let physicians look patients in the eye again, predictive models catching serious illness years early, and smart summaries unlocking intelligence buried in decades of records. The economic and social value accumulation is enormous: fewer physician departures, more preventive care, lower system costs, better patient outcomes. This is already happening. And it is only the beginning. Second, AI bias is not a technical glitch. It is a governance failure. Dr. Hoffert described a model trained predominantly on majority-population data that concluded Black patients needed less healthcare. not because they did, but because historical inequality had reduced their access to it. The AI learned the wrong lesson from flawed data. This pattern repeats across organ donation algorithms, insurance systems, and financial platforms. Data representativeness is not a diversity checkbox. It is a prerequisite for accuracy, fairness, and institutional trust. Third, privacy frameworks must match how AI is actually being used today. When individuals input sensitive health data into general-purpose AI platforms, existing protections do not follow. The regulatory gap is real and being actively exploited. The governing principle must be clear: it is the nature of the data that triggers the obligation, not the identity of who holds it. Fourth, international cooperation on AI safety cannot be optional. Without a shared baseline on risks and values, the race to accumulate AI capability will consistently outpace the frameworks meant to govern it. When Dr. Hoffert asked the room strict oversight or space to innovate? my answer was this: AI is a powerful tool, and its capacity for value creation is deeply needed by every society. But like every invention before it, be it cars, the airplane, the pharmaceutical it must be carefully analysed, evaluated, and regulated. Not to kill innovation, but to ensure it serves us and not turn into a poisson. Regulation and innovation are not opposites. Intelligently designed, regulation is what makes durable innovation possible. Thank you Dr. David Hoffert and Gustavo Piga for organising this insightful seminar. #AIPolicy #AIGovernance #HealthcareAI #AIBias #DataPrivacy #GlobalConversations #HealthEquity #Innovation #PublicPolicy #ValueCreation #InternationalCooperation
🎤 We gave AI a voice in healthcare. 👂 We forgot to give it ears. Healthcare is one of the few industries where the system knows more about you than you know about yourself — your risk score, your gaps in care, your likelihood of a hospital visit next quarter. And yet, for all that it knows going in, the feedback loop is almost entirely broken on the way out. Whether the care was received. Whether the intervention changed behavior. Whether the denial created a downstream gap that quietly compounded. Whether the member who disengaged did so because life got in the way — or because the system stopped feeling worth the effort. None of that signal makes it back. The model that acted never learns from what it caused. We gave AI a voice in healthcare. We forgot to give it ears. suchithra ravi and I are releasing a three-part series on the feedback loop imperative in payer-side AI — what it means to build systems that close the loop between action and outcome, between intervention and lived experience, between what the AI decided and what actually happened to the person it decided about. The gap isn't a technical limitation. It's a design choice that was never questioned. We think it's time to question it. Teaser is live. https://lnkd.in/gV6BWQ6G #healthcare #healthcareai #feedbackloop #aifeedback #ai
AI is intensifying the ongoing challenges associated with itemized billing in healthcare. This article provides a clear overview of the current trend. The question remains: will this lead to a greater shift towards capitation payment models, or will the excitement surrounding AI distract from the need to simplify our itemized payment structures
At BeMe Health I made it a priority to reach out to native and rural teens to make sure they had access to behavioral health services. There’s a huge need in those, and so many other communities.