Marc Harrison

Commercial medical-cost pressure remains stubbornly elevated, reinforcing the need for stronger utilization and cost-driver analytics. CVS/Aetna told investors this week that medical-cost growth remains “high trend,” particularly outside Medicare. That builds on the employer-cost trend data we flagged previously and suggests the pressure is persisting rather than normalizing (Investor's Business Daily). Why it matters: Organizations that cannot decompose trend into unit cost, utilization, site of care, pharmacy/specialty drugs, risk mix, and high-cost claimants will increasingly struggle to price accurately, negotiate effectively, or manage risk contracts. Executive lens: Healthcare/Medical Economics + Finance + Enterprise Analytics. Action/question: Do you have a single economic view that connects claims/utilization drivers to pricing, contracting, margin, and intervention ROI—or are finance, actuarial, and analytics still operating from separate versions of the truth? That operating-model question is increasingly important. The market is rewarding leaders who can bridge finance, medical economics, actuarial/risk, analytics, and AI-enabled decision support, not simply own one of those functions in isolation. Contact VBC Advisor LLC for analysis, strategy, and recommendations!

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Musings from a Long-Term Independent Operator Part 2️⃣ : Incentives Matter More Than Strategy If you operate long enough in healthcare, you learn something simple: Incentives drive behavior more reliably than mission statements. A 2023 analysis published in JAMA Health Forum examined leveraged buyouts in healthcare and highlighted two important structural realities: 💸 Most of the debt from leveraged buyouts is tied to the acquired entity — limiting long-term financial risk to the private equity firm. 💸 Companies acquired through leveraged buyout (across industries) are approximately 10 times more likely to go bankrupt. In healthcare, this dynamic has been exemplified by cases such as Hahnemann Hospital in Philadelphia. Hospital systems and employer-sponsored primary care are different models. But the lesson is structural, not sector-specific: When financial risk sits primarily at the operating level — and return expectations sit at the ownership level — stability can shift. Employer-sponsored primary care emerged to correct misaligned incentives: 💰 Volume-based reimbursement 🚫 Fragmented care delivery 🖇️ Administrative overhead 🤷‍♂️ Lack of accountability It was built to restore alignment between care delivery and outcomes. The question isn’t whether capital belongs in healthcare. The question is whether the structure of that capital strengthens or weakens long-term alignment. Ownership structure influences: ⏰ Time horizon ⚕️ Investment in care teams 📈 Cultural priorities ✳️ Risk tolerance In healthcare, incentives shape behavior. Behavior shapes care. #HealthcareLeadership #HealthcareEconomics #PrivateEquityInHealthcare #HealthcarePolicy #ValueBasedCare #HealthcareStrategy #EmployerSponsoredHealthcare #HealthcareOwnership

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A “Big, Beautiful Bill” With Big Implications: What the Federal Shift Toward Value-Based Care Really Means The Federal Government’s new “big, beautiful bill” on value-based care is more than legislation — it’s a clear signal that the era of fragmented, volume-driven medicine is giving way to a coordinated, outcome-centered model. This isn’t a small adjustment. It’s a national reset. The bill reinforces several realities that are already reshaping healthcare: ✅ Value-based care is becoming the foundation of future reimbursement. Systems that prepare now will lead in quality, sustainability, and patient outcomes. ✅ Infrastructure for coordination and prevention is no longer optional. Digital integration, care pathways, and population health strategies will define performance. ✅ Financial stewardship and clinical excellence now move together. Better outcomes, fewer complications, and stronger cost control become mutually reinforcing goals. ✅ Data transparency becomes a powerful differentiator. Organizations that embrace clear, meaningful metrics will build trust and outperform peers. ✅ The patient journey — not the billable encounter — becomes the center of policy and practice. This “big, beautiful bill” isn’t just sweeping in scope; it opens the door for health systems to rethink how value is created, measured, and delivered. The future belongs to organizations that can align culture, capital, and clinical operations with this shift — and do so with intention, creativity, and compassion. Because the transition to value isn’t just mandated policy. It’s the path to a stronger, more equitable, and more sustainable healthcare system.

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Fixing payment systems is not just a kidney care problem. A recent NEJM AI paper outlines how reimbursement failures are blocking the impact of health AI. I think we can learn a thing or two from their recommendations. Here's what I wrote about the perspective piece by Eric Topol, MD and colleagues: "The authors argue that despite major advances in AI, health care remains one of the least transformed sectors because economic and regulatory frameworks have not kept pace. Even FDA-cleared AI tools struggle to gain traction due to outdated reimbursement pathways, CPT code bottlenecks, and fragmented incentives. The paper outlines specific reforms to align payment models with AI cost structures and reduce integration overhead, while also calling for a forward-looking regulatory framework for generative AI. The authors frame the issue as an ethical one: failing to modernize payment systems prevents tools that could reduce clinician workload, shorten wait times, and improve patient care from reaching patients." Read their perspective here: 👉🏻 https://lnkd.in/eb699sHR *** Sounds familiar, right? If you had to pick 3-4 examples of technologies or tools that have been limited by / or had to navigate the kidney care reimbursement landscape (i.e. TPNIES, TDAPA, the "bundle"), what would you choose? I'm planning to write a piece on this and will create a similar visual to help show how a similar might look for kidney care. Drop your thoughts and suggestions below!👇🏻

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What comes after the CMS Hospital at Home framework? As health systems continue to build hospital-at-home programs, new care models are emerging beyond the traditional CMS framework. At CHIME’s Hospital at Home Technology Summit, Stanford Health Care leaders Ron Li, Sophia Loo and Gretchen Brown will explore what these models look like in practice, and what it takes to deliver high-acuity care safely beyond the hospital walls. Join the conversation on the technology, clinical workflows and operational strategies shaping the next generation of hospital at home. Tuesday, September 22 | 12–4 PM ET | Virtual Register for the Hospital at Home Technology Summit: https://hubs.ly/Q04x5gMY0 #HospitalAtHome #HospitalAtHomeTechnology #DigitalHealth

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No company scales in healthcare alone. Founders may have a strong product, compelling vision, and early customer traction, but sustainable growth often relies on effective integration with the broader ecosystem of providers, payers, consultants, channel partners, EHRs, and strategic collaborators. A well-designed partner program does more than generate leads. It can build trust in a relationship-driven industry, shorten sales cycles, expand market reach, and improve implementation and adoption. In healthcare, companies that align with surrounding workflows, technologies, and stakeholders often gain momentum more quickly. Successful founders prioritize partnerships from the outset, incorporating them into growth strategies with intention, structure, and a clear focus on mutual value. In a crowded market, your ecosystem can serve as a key differentiator. Are you thinking about partnerships as part of your growth strategy?

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Why healthcare is so expensive isn’t mysterious. It’s structural. I recently joined Robert Tercek and Brett King of The Futurists to talk about why U.S. healthcare costs keep exploding – and why fragmentation is the real failure. We’ve built a system where: - Care is frequently split across siloed providers - Information technology has multiplied fragmentation instead of reducing it - Managed care tries to optimize by managing the utilization of the “average patient,” even though ~5% of people drive ~50% of total cost Those patients are medically and socially complex. They move across hospitals, clinics, behavioral health, social services, first responders, and sometimes, the police – each with a different system and a different care plan. The result: Conflicting instructions, unsafe medication overlap, preventable hospitalizations. Meanwhile, public programs don’t pay cost, and private premiums quietly subsidize inefficiency. An estimated ~25% of healthcare spend can be chalked up to needless red tape and coordination failures. This isn’t a “more apps” problem. It’s an infrastructure problem. At Precognitive and PHM Advisors, we think of this as applying FinTech-style infrastructure to healthcare, social, and public services – an intelligence layer that can finally support one person, one story, one care plan. Our resources aren’t infinite and every dollar wasted is one not spent truly advancing the health and wellbeing of our communities. AI’s real job is helping systems behave like systems and enable Systems That Care. 🎧 Listen to the conversation here: https://lnkd.in/e6fnUW7S

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OneImaging, a Miami-based startup rolling out a new radiology platform, has raised $38 million in Series A financing, the company announced Tuesday. Founded in 2022, OneImaging seeks to simplify radiology appointments for patients and providers, connecting them with a nationwide network of accredited centers. The company claims it can reduce radiology costs by up to 80%, also delivering transparent pricing and “seamless” reimbursement.

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Something to note from Menlo Ventures's incredible AI in healthcare report....their data confirm what many of us in health systems already feel coming: AI adoption will INCREASE administrative volume before it reduces it. Payers expect, in the next 12–36 months: 63% major jump in call volume 50% more codes per claim 40%+ higher claim volume 38% more prior auths 31% more appeals + resubmissions When documentation gets easier, volume is going to skyrocket. Implications we’re already planning against: - AI adoption doesn’t remove work inherently; it redistributes it across the ecosystem. Workflow redesign is critical. - Providers need guardrails to prevent over-generation of documentation and requests. More noise helps noone. - Startups must show cross-stakeholder ROI, not siloed productivity gains... - Health systems need a system-wide AI playbook, or every local win creates a downstream backlog. This next 2-3 years will either widen payer–provider tension or force real alignment. I'm not counting on the latter. Curious how others are preparing.

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