From Interview #99
With Stephen Speicher, MD, MS
Dr. Stephen Speicher, Senior Medical Director at Flatiron Health, offers a thought-provoking look into how artificial intelligence may become a requirement—not just an option—in future value-based care models. In this clip, he explores whether insurers might eventually mandate AI use in clinical decision-making as a condition for reimbursement, especially if AI demonstrates measurable improvements in patient outcomes. While the cost of AI today often falls on the healthcare provider, Speicher suggests a future where insurers not only pay attention to AI utilization but actively incentivize or even demand it. This shift could redefine how 'value' is operationalized in value-based healthcare, raising new questions about reimbursement, care quality, and access. His insights offer a forward-looking framework for understanding the evolving intersection of health tech and reimbursement models.
From Interview #99
With Dr. Stephen Speicher
Dr. Stephen Speicher, Head of Clinical Oncology and Safety at Flatiron Health, shares insights on the evolving dynamics of informed consent in the age of artificial intelligence. As AI tools become increasingly embedded in clinical workflows, Speicher discusses whether patients should be informed, opt out, or share responsibility in these decisions. He addresses the ambiguity surrounding consent for ambient AI tools and the ethical dilemmas clinicians face when transparency meets technological complexity. The conversation underscores that as AI shifts toward becoming a standard of care, questions of healthcare informed consent and patient privacy become not only technical but deeply human. Speicher provides a thoughtful, systems-level view of this important intersection of AI and informed consent.
From Interview #100
With Dr. Bertalan Mesko
Dr. Bertalan Mesko, Director of The Medical Futurist Institute, reveals how vision writing and the concept of “future selves” can dramatically impact our present-day decisions. In this segment, he shares how imagining yourself in future scenarios—whether as a parent, professional, or even a teenager with braces—can create emotional alignment and long-term motivation. Vision writing isn't a rigid forecasting tool, but a narrative-driven method to make future thinking more personal and actionable. Healthcare professionals and digital health strategists may find particular value in the psychological dimension of foresight, as it supports not just innovation planning but also behavior change—an underutilized lever in organizational and patient transformation.
From Interview #98
With Jordan Johnson, MSHA
In this short but insightful exchange, Jordan Johnson, MSHA, founder of Bridge Oncology, explains why predictive AI combined with wearable technology could radically shift the foundation of medicine. Historically, medicine has focused on treating symptoms that patients report. But with real-time data from wearables and the pattern recognition power of AI, healthcare is inching toward predicting disease progression before symptoms surface. Johnson and Dr. Sanjay Juneja explore how CMS policies, remote patient monitoring, and machine learning create a new paradigm in preventive care. This conversation exemplifies how predictive AI in healthcare and advances in wearable tech are not just tools—they’re catalysts for structural transformation.
From Interview #84
With Dr. Alister Martin
Dr. Alister Martin, CEO of A Healthier Democracy and Assistant Professor at Harvard Medical School, discusses how AI can improve emergency room efficiency by identifying high-need patients—often called 'frequent flyers'—and connecting them with essential social services. Through a process called benefit stacking, AI streamlines applications for multiple assistance programs, addressing root causes like housing instability and utility costs. Martin cites evidence from randomized controlled trials showing that small, targeted financial support can dramatically reduce ER visits, cut Medicaid costs, and relieve hospital financial strain.
From Interview #80
With Dr. Azra Raza
Dr. Azra Raza, Professor of Medicine at Columbia University, argues that stage one cancer detection is already too late. She critiques current screening methods—which generate millions of false positives and cost billions annually—and advocates for continuous health monitoring from birth. Raza envisions implantable stents equipped with sensors and chips that can detect abnormal cells in real time, transmitting alerts to a patient’s phone. Coupled with AI and machine learning, this approach could enable detection at the 'first cell stage,' revolutionizing cancer prevention and patient outcomes.
From Interview #86
With Dr. Euan Ashley
In this conversation, Dr. Euan Ashley explains how wearable devices can identify atrial fibrillation (AFib), a major risk factor for stroke, before symptoms occur. By monitoring the intervals between heartbeats, these devices detect the irregular rhythm characteristic of AFib, alerting users to seek medical evaluation. Unlike traditional detection methods—which require short-term clinical monitoring—wearables provide continuous, long-term observation, making it possible to catch AFib early, even years before it might be detected in a clinic. Ashley notes that while sophisticated AI can enhance diagnostics, detecting AFib requires only identifying regular versus irregular rhythms.
From Interview #80
With Dr. Azra Raza
Dr. Azra Raza discusses the transformative potential of continuous AI-driven health monitoring to detect diseases like cancer before symptoms arise. She describes implantable devices capable of screening the entire bloodstream every 18 days for abnormal cells and molecular biomarkers, enabling intervention at the earliest possible stage. While FDA approval for these devices is pending, point-of-care technologies already allow high-frequency testing for illness signatures at home. Raza highlights the urgency of funding these innovations, emphasizing that early detection could shift healthcare from reactive treatment to true prevention.
From Interview #76
With Dr. Debra Patt
Dr. Debra Patt, Chair of the AI Taskforce at the American Society of Clinical Oncology (ASCO), discusses the organization’s guidelines for responsible AI use in cancer care. While ASCO recognizes AI’s potential to improve decision-making, Patt emphasizes transparency, bias awareness, and keeping physicians central in care delivery. She illustrates with a clinical example how AI recommendations may overlook patient-specific factors, reinforcing the need for human oversight. AI can offer valuable nudges or decision-support suggestions, but ultimate care choices must remain personalized and patient-centered.
From Interview #96
With Emily Lewis
In this information-packed interview, Emily Lewis shares a compelling vision for the future of AI in patient care. Drawing from her work in machine learning and generative AI, Lewis highlights how these tools are not just enhancing clinician efficiency but reshaping how patients engage with their own health. She explains how multimodal AI applications, from avatars to audio interfaces, can personalize communication based on learning preferences. Lewis emphasizes AI’s potential to foster equitable partnerships between patients and clinicians. The conversation also explores patient education, self-care, and the structural hurdles of deploying AI across institutions. With attention to AI for patient engagement and AI-driven personalized care, Lewis offers a deeply insightful look into the systems and safeguards necessary for responsible AI implementation.
From Interview #83
With Pelu Tran
In this insightful discussion, Pelu Tran explores the practical role of artificial intelligence in enhancing clinician productivity and navigating the widespread inefficiencies in healthcare. Drawing from Ferrum Health’s platform, Tran explains how AI enables faster diagnosis, supports care coordination, and amplifies provider capacity—particularly in overburdened fields like radiology. He also highlights the real cost of AI adoption, pointing to the significant resources required to integrate AI into existing healthcare systems. This conversation sheds light on the evolving impact of AI for healthcare productivity and reframes the debate: it’s not just about quality vs. efficiency—it’s about enabling clinicians to sustain care at scale.
From Interview #80
With Dr. Azra Raza
In this compelling interview, Dr. Azra Raza challenges the traditional focus of oncology, arguing that early cancer detection should be the central pillar of cancer research and treatment. Sharing her personal journey as an immigrant and oncologist, Dr. Raza critiques the widespread reliance on animal models and late-stage therapies, advocating instead for the study of human tissue and the identification of disease at its earliest stages. Her lifelong work in hematologic malignancies, particularly myelodysplastic syndromes, underscores the urgency of this shift. By focusing on “the first cell” rather than the last, she highlights how early intervention could dramatically reduce suffering and improve survival—raising critical questions about current priorities in cancer care and the persistent challenges in cancer treatment.
From Interview #82
With David Norris
Can AI replace doctors—or is it here to restore what’s been lost in medicine? David Norris, CEO of Affineon Health, tackles this provocative question with depth and clarity. Far from eliminating physicians, Norris argues that AI solutions are essential for addressing physician burnout, streamlining administrative tasks, and reviving the human relationship between doctors and patients. He illustrates how AI, like Affineon’s $2.50/day AI assistant, can triage clinical inboxes, flag clinically significant lab trends, and bring 10 years of patient history into a three-second review—freeing doctors to focus on what matters most. This conversation is a must-watch for anyone curious about how AI is reshaping the future of care.
From Interview #91
With Dr. Spencer Dorn
In this in-depth conversation, Dr. Spencer Dorn, Vice Chair and Professor of Medicine at the University of North Carolina, explores the evolving role of AI scribes in healthcare. He examines their ability to reduce clinician burnout, improve patient experience, and integrate into EHR systems. Dr. Dorn discusses both the potential for clinical decision support and the limitations of current AI scribe technology, including contextual awareness, coding accuracy, and ROI considerations. He also reflects on broader AI risks, from critical thinking erosion to the impact on patient-clinician relationships, offering a nuanced roadmap for responsible adoption.
From Interview #82
With David Norris
In this full interview, David Norris, Co-Founder and CEO at Affineon Health, shares how AI is revolutionizing healthcare administration by reducing the overwhelming burden of lab result management, documentation, and communication. Norris discusses how AI agents can triage clinical inboxes, prioritize urgent results, and even engage patients directly, allowing providers to focus on meaningful patient care rather than administrative overload. He highlights the impact on burnout reduction, the potential for preventive interventions, and how AI tools can level up both physicians and advanced practice providers by surfacing actionable insights from vast longitudinal data. This conversation offers practical solutions for integrating AI into healthcare workflows.