Larry Schor

John Driscoll and I focused our post-JPM discussion on how GLP-1 use will transform in 2026, how AI is reshaping healthcare and whether the Chinese biotech surge is for real. #jpm2026

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Looking back at 10 years of episodic care—how did it work out? Worth the read from Becker's Healthcare “No improvement in outcomes, no improvement in access, no improvement in equity, and paying out more money than the savings … it just does not seem to me to be worth it, though conceptually it makes good sense,” Karen Joynt Maddox, MD, MPH, a professor at Washington University School of Medicine in St. Louis, said. "That dynamic created a problem for academic medical centers and safety-net hospitals treating more complex patients. A University of Florida study published in 2023 found that its CJR participation saved Medicare an estimated $16.4 million over five years while dramatically improving quality. Length of stay dropped 56%, readmissions fell from 17.7% to 5.1%, and complications decreased from 6.5% to 2%. Despite those results, the hospital was penalized more than $300,000 at the end of its participation. The authors attributed the penalty to benchmark changes and the removal of healthier patients from the CJR-eligible pool as joint replacements moved to outpatient settings."

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What if a merger wasn’t a finish line but a launchpad? In an insightful piece by Harvard Business Review, the CEO of Advocate Health outlines how scale, strategy, & partnerships are redefining healthcare innovation. Here are three key take-aways worth sharing: ✅ By bringing together two major health systems to create Advocate Health, leadership didn’t stop at consolidation—they used their 69 hospitals and 1,000 care sites as a “living laboratory” for transformation. ✅ Innovation for them isn’t about tech alone—it’s about who you co-build with. They’re rejecting passive vendor relationships in favor of deep partnerships where companies “design, iterate and build” alongside them. ✅ Purpose and equity are embedded in the strategy. The organization is leveraging its platform not just to experiment, but to extend specialist access into rural communities and build an AI-enabled “hospital room of the future.” If your organization is looking to scale innovation, the Harvard Business Review sets a clear reminder: it’s not enough to adopt technology—you must embed it into ecosystems of purpose, partnerships and people. #HealthcareLeadership #Partnerships #HealthcareInnovation #Business

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Healthcare SaaS companies operate in environments where precision and accountability matter. Revenue leadership influences more than top-line numbers. It shapes financial resilience, operational discipline, and the ability to build systems that last. Welcoming James Aylward as Chief Revenue Officer reflects that understanding as Knowwn continues its next phase of growth. Recently featured by The Associated Press. Read more: https://lnkd.in/eB4rs3Qe

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Nice quote from one of our Partners Andrew Brackin in TechCrunch: “This was one of the biggest use cases of ChatGPT,” Andrew Brackin, a partner at Gradient who invests in health tech, told TechCrunch. “So it makes a lot of sense that they would want to build a more kind of private, secure, optimized version of ChatGPT for these healthcare questions.” https://lnkd.in/gY3TV5VD

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At Optum, we’re excited to announce the launch of Crimson AI, powered by HealthTrust — a unified analytics platform co-developed hand-in-hand with HealthTrust Performance Group for its members. The platform integrates HealthTrust’s rich data assets with near real‑time insights, helping health systems optimize both clinical and financial performance.    Read more at: https://lnkd.in/eU46AnZv   #HealthcareInnovation #AIinHealthcare #Optum #CrimsonAI #HealthTrust #HealthSystemPerformance  

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The solution then, is to redesign the financial interest around medicine. that means get rid of the big insurers and automate administration and health and wellness. Like this. The coverage company should: 1.  Provide a data driven EMR.  2.  Integrate the coverage into the EMR. 3.  Pay for covered procedures as they are documented. 4.  Pay a reference-based price, we suggest 150% of Medicare, but ONE price. 5.  Separate the cost of the coverage service from the cost of the risk. 6.  Charge $10/month for the service, plus the true cost of the risk. 7.  Provide a health and wellness package that offers discounts for compliance; improving lab results. 8.  Provide and ERP style Hospital/Practice Management system to run the enterprise efficiently 9.  Provide a queueing system that eliminates linear, ‘workflow’ thinking That eliminates medical coding, verification, adjudication, pre-authorization, denials, delays, insurance networks, rate negotiations, sales/brokers/agents, money for a third-party EMR, skyscrapers in every major city, hundreds of thousands of employees, all the monkey business and reduces cost by about half for the patient and about a quarter for the hospital.  It also eliminates Epic/Cerner AND BUCAH. Sentia has this system in production, right now, today. Read the details: https://lnkd.in/gSzn8wez

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Healthcare angel investing has fundamentally changed over the past decade, and it’s worth examining what this means for the innovation ecosystem we’re all building. The sophistication gap between early-stage healthcare investing and traditional tech angel work has widened dramatically. We’re no longer talking about physician investors writing checks to colleagues based on clinical intuition. What’s emerged is something closer to translational research infrastructure that happens to deploy capital. The numbers tell part of the story: health and life sciences deals jumped from roughly 18% of angel activity in 2017 to 30% in 2023. But the real shift is qualitative, not quantitative. Successful healthcare angels today are building what I’d call epistemic infrastructure. They’re assembling expert panels spanning former FDA reviewers, health economists, and technical architects who can actually interrogate scientific claims and regulatory strategies. This isn’t due diligence theater. It’s the only way to price risk in domains where traditional VC pattern recognition breaks down completely. The technical bar has risen substantially, especially around AI-driven healthcare companies. Model provenance, external validation on out-of-distribution datasets, deployment architecture that actually integrates with clinical workflows—these aren’t nice-to-haves anymore. They’re baseline requirements. What fascinates me most is how regulation and reimbursement have shifted from back-office considerations to front-and-center product architecture decisions. Angels who grasp that regulatory clearance is a moat rather than friction are fundamentally outperforming. Understanding CPT code pathways, value-based care alignment, and international frameworks like Germany’s DiGA program isn’t optional anymore. Because healthcare timelines run five to seven years from angel investment to exit versus three to five for software, we’re seeing experiments with hybrid structures combining equity and revenue-based financing. These aren’t financial engineering tricks. They’re responses to the actual temporal dynamics of healthcare innovation. The most effective angels are functioning as translators between academic science, regulatory bureaucracy, and computational infrastructure. They’re not just funding companies. They’re architecting the connective tissue that determines which scientific discoveries actually reach patients. ----- Disclaimer: These thoughts and opinions are my own and do not reflect the views of my employer or any other entities. ----- Link to the full analysis in the comments below.

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🧠 Digital Health Insight According to Intuition Labs, over 71 million Americans (which is about 26 percent of the population) are expected to use remote patient monitoring services in 2025. RPM is no longer a fringe solution. It represents a systemic shift in how care is delivered, especially for chronic conditions and proactive wellness. The adoption of tools like connected scales, blood pressure cuffs, and wearable sensors opens the door for more personalized, continuous care. 💬 How can we scale and optimize remote monitoring solutions to help more people stay well and out of the hospital? Source: https://lnkd.in/d2wUEU2J #DigitalHealth #RemoteMonitoring #ChronicCare #HealthTech #PatientEngagement #PreventiveCare #Wearables #CareTransformation

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Dr. Travis Bias — this is an outstanding distillation of why AI in the revenue cycle is more than a tech upgrade; it’s a structural shift in how value is created in care delivery. Your perspective from rules-based systems to machine learning to generative and now agentic AI — directly tackles two of the biggest sources of economic friction: clinical documentation inefficiency and revenue-cycle inaccuracy. What resonated most is your focus on capturing the full complexity of a patient’s story at the point of care. From a health-economics standpoint, improving first-pass accuracy reduces denials, shortens A/R cycles (A/R: account receivables), and aligns reimbursement more closely with true resource use — real system-level gains. At the same time, agentic AI is measurably reducing after-hours EHR burden and burnout, shifting clinician time back toward higher-value cognitive and patient-facing activities. That’s not just a workflow win; it’s a human-capital investment with major downstream cost implications. As a former UCSF health economics student from your course of Comparative Healthcare Systems, it’s inspiring to see these principles executed at operational scale. Excited to watch how this next generation of AI reshapes the economic backbone of care delivery.

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