Practical AI in Healthcare

Steven Labkoff, MD and Leon Rozenblit, JD, PhD
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AI promises to transform healthcare—but real, scalable impact remains rare. Practical AI in Healthcare cuts through the noise to showcase real-world use cases delivering business value today. Hosted by senior leaders— former VPs of life science technology groups, clinical informatics professionals from top-tier organizations, and a former Big Four consultant—each episode features candid conversations with the people making AI work inside the healthcare enterprise

  1. 4 dgn geleden

    S1, E44 - Reflections #6: After Five Episodes, What Still Has to Be Human?

    In their sixth Reflections episode, Steve and Leon look back across five conversations (Sarah Rossetti, Jeff Smith of ONC, Hugo Campos, Fred Bennett, and Zak Kohane) and decide, deliberately, not to force a single grand theme. What surfaces anyway is one question asked five ways: as AI gets genuinely capable, what still has to be human, and what makes it trustworthy? They cover Rossetti's CONCERN system that models the nurse instead of the patient, ONC giving AI agents patient-like data rights, the tension between patient empowerment and black boxes you don't understand, the Minimum Trustable Product, and Kohane's method for measuring the values a healthcare AI actually acts on. A practical tour of where good is starting to look real.

    49 min.

  2. 28 jun

    S1, E43 - Isaac "Zak" Kohane, MD, PhD (Chair, Biomedical Informatics, Harvard Medical School; founding Editor-in-Chief, NEJM AI)

    A quiet war is underway over who controls your health data in the age of AI, and the front-runners aren't the usual suspects. Dr. Isaac "Zak" Kohane, Chair of Biomedical Informatics at Harvard Medical School and founding editor of NEJM AI, traces the line from SMART on FHIR (the accidental standard he helped create in 2009) to today's battle for the doctor-facing AI layer, where companies like OpenEvidence are outrunning the EHR incumbents. He also unveils his Human Values Project, which measures the values embedded inside clinical AI models, and warns how easily payers and pharma could tune them. A two-act conversation about freeing data and guarding values.

    58 min.

  3. 21 jun

    S1, E42 - Live with Fred Bennett, Founder & CEO, PatientTalker

    For its first-ever live episode, recorded before an audience at New York Tech Week, Practical AI in Healthcare sits down with Fred Bennett, founder and CEO of PatientTalker — an ambient-AI app built for the patient rather than the clinician. (Steve Labkoff is a disclosed advisor to the company.) Bennett traces the idea to his father's cardiology visit, where three family members left with three different memories of the same conversation. The discussion covers why patients are the forgotten end-user of clinical AI, how to build a "minimum trustable product," the honest question of who pays for patient-first tools, and why the technology is rarely the hard part.

    59 min.

  4. 14 jun

    S1, E41 - Hugo Campos: Patient-Directed AI

    Patient advocate Hugo Campos spent more than a decade fighting for access to the data from his own implanted defibrillator. When the system wouldn't budge, he stopped trying to reform it and started building around it. In this episode, Hugo shows how he used agentic AI coding tools to create OpenKP, an open-source app that liberates his records from inside Kaiser Permanente, despite calling himself a non-coder. He and the hosts unpack the line between institutional AI and patient-directed AI, the discipline of having two AIs check each other, and why he believes "critical AI health literacy" now matters more than knowing how to code. https://practicalaiinhealthcare.com/

    52 min.

  5. 7 jun

    S1, E40 - Jeff Smith — AI Regulation, Transparency & Innovation from the Government Perspective

    What happens when the rules for getting AI into clinical care are written by someone who has spent his career inside both the advocacy world and the government? In this episode, we talk with Jeff Smith of ONC at HHS, the first government official on Practical AI in Healthcare. Smith walks us through ONC's proposed HTI-5 rule, including a striking move to treat AI agents as "users" with the same data-access rights as clinicians, and a new question about whether blocking data from being written back into the EHR is itself information blocking. We also dig into the limits of what a regulator can actually do, and why the real work is coordination across agencies rather than control from any one of them. https://practicalaiinhealthcare.com/ https://www.youtube.com/@PracticalAIinHealthcare

    44 min.

  6. 31 mei

    S1, E39 - Sarah Rossetti, RN, PhD: Nursing Informatics & the CONCERN Early Warning System

    On National Nurses Day, Practical AI in Healthcare welcomes its first nurse: Sarah Rossetti, RN, PhD, of Columbia University. Her CONCERN early warning system takes an unusual approach to predicting patient deterioration. Instead of modeling a patient's vital signs and labs, it models the nurse's documentation behavior, since the frequency and timing of charting reflect clinical concern long before the numbers move. In a 74-unit randomized trial of more than 60,000 patients, published in Nature Medicine, CONCERN was associated with a 35.6% reduction in instantaneous mortality risk. Rossetti and the hosts unpack the method, the counterintuitive rise in ICU transfers, equity safeguards, and what ambient AI means for the signal. https://practicalaiinhealthcare.com/episodes/#S1E39 More on Sarah Rossetti's work: https://www.dbmi.columbia.edu/profile/sarah-collins-rossetti/

    53 min.

  7. 24 mei

    S1, E38 - Reflections 5: How Specialized Does AI Have to Be to Actually Work?

    In their fifth Reflections episode, Steve and Leon look back across six conversations (Matt Truppo at Sanofi, Ted Shortliffe, Barry Chaiken, David Hidalgo-Gato, and Danny van Leeuwen) to ask a sharper question: how specialized does AI have to be to actually work? The throughline is depth. The LLM is a commodity, and so, increasingly, is the generalist agent. What stays scarce is specialization in a workflow, the revival of symbolic methods like knowledge graphs, the literacy that separates an AI's ~95% solo accuracy from the under-35% people get using it themselves, and leaders willing to use themselves as the test rig. After 37 episodes, the technology is no longer the question. The specificity of the work around it is.

    35 min.

  8. 17 mei

    S1, E37 - Danny van Leeuwen, MPH, RN, Health Hats: Patient's POV on AI Tools

    Danny van Leeuwen is a nurse of 50 years, a multiple sclerosis patient, host of the Health Hats podcast, and a serial member of national outcomes panels at CMS, AHRQ, PCORI, and the National Academy of Medicine. He has tried more than 100 health apps and uses five. In this episode, he explains how he uses AI to interrogate his own chart, surface symptom patterns, and prepare for clinical encounters, and he shares his Three T's and Two C's framework for evaluating any digital health technology: Time, Trust, Talk, Control, Connection. The conversation covers what patients want from AI, what they do not, and why pain, fear, and cognition still escape the data.

    42 min.
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Info

AI promises to transform healthcare—but real, scalable impact remains rare. Practical AI in Healthcare cuts through the noise to showcase real-world use cases delivering business value today. Hosted by senior leaders— former VPs of life science technology groups, clinical informatics professionals from top-tier organizations, and a former Big Four consultant—each episode features candid conversations with the people making AI work inside the healthcare enterprise

Informatie

  • Maker
    Steven Labkoff, MD and Leon Rozenblit, JD, PhD
  • Jaren actief
    2025 - 2026
  • Afleveringen
    45
  • Beoordeling
    Veilig
  • Copyright
    © Steven Labkoff, MD and Leon Rozenblit, JD, PhD
  • Website van aflevering
    Practical AI in Healthcare

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