Vasudev Bailey

FORCING CHANGE IN SITE OF CARE McKinsey & Company's recent paper on the forces pressuring healthcare, including the possibility of margin compression of up to 13 percentage points for health systems, does a good job of putting numbers around what most operators already feel. Two of the biggest drivers they mention are policy shifts in reimbursement and rising utilization driven by an aging population. The cohort of 70+ year old Americans will grow the fastest over the next 5 years, and it is well established that older patients have more complex needs, more chronic disease, and more touchpoints within the healthcare system. Layer that on top of continued clinical workforce shortages, and the supply-demand gap widens further. From my perspective, optimizing for site of care is the most important lever we have to address this challenge. We can’t quickly reduce how much care older patients need, but we can change where and how services are delivered. Supporting aging patients in lower-cost settings like the home, ambulatory sites, and virtual environments is no longer just a preference or convenience, it’s a necessity. This is where the conversation around site-neutral payments becomes so relevant. CMS is moving quickly in this direction, and hospital outpatient departments (HOPDs) are squarely in the crosshairs. The shift will undoubtedly clamp down further on hospital margins, but it shouldn’t be surprising. We’ve been talking about the demise of HOPD reimbursement for years, and the health systems that will fare best are the ones who are working towards aligning their approach with where patients can be treated safely, efficiently, and at lower cost, rather than relying on legacy reimbursement structures to fill the gap. And just like it doesn’t make sense to try to replicate a hospital or nursing home environment in a patient’s home, we also shouldn’t try to carry the same clinical staffing model into every care setting. Yes, there are non-negotiables when it comes to patient safety and clinical expertise, but there’s also a meaningful opportunity to rethink how teams are built. That means clinicians at every level working at the top of their licenses, thoughtfully involving family members and community resources, and using technology to surround these sites of care with non-clinical operational support. From my health system days, I understand why rising costs, margin pressure, and site-neutral payments feel like threats. While painful, I’m hopeful they can also serve as a positive forcing function, pushing us toward care models that are better aligned with our aging population and the realities of today’s workforce.

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Why Now Is the Best Time Ever to Invest in Healthcare AI Startups By Andy Reid, Managing Partner, M3A Healthcare Ventures We are entering a once-in-a-generation window for investing in Healthcare AI—one where timing, technology, and major shifts in care are aligning to create outsized opportunities for early-stage venture capital. At M3A Healthcare Ventures, we believe this is the moment to invest boldly. 1. Healthcare Is Ripe for Disruption—And It Has To Be U.S. healthcare costs are projected to hit $7.2 trillion by 2031, yet outcomes lag behind every other developed nation. Workforce shortages, and fractured data systems create inefficiencies that AI is uniquely positioned to solve. • 25% of U.S. healthcare spending is administrative waste. • 90% of hospitals face staffing shortages in key roles. • Doctors spend 2 hours on documentation for every 1 hour with patients. AI isn’t a “nice to have” anymore. It’s becoming a critical tool for cost control, productivity, and quality improvement. 2. We’ve Entered the Platform Shift Era Apple Intelligence, OpenAI, and other foundation models have catalyzed a new generation of startups. In healthcare, this means real-time ambient documentation, predictive care, smart inventory management, and even AI-generated clinical trial design—all happening today. This is akin to investing in SaaS in 2006 or mobile apps in 2011. Except this time, the TAM is $4 trillion larger. 3. Buyers Are Ready—and They’re Buying Just five years ago, hospitals were wary of AI. Today, they’re budgeting for it. Health systems, ASCs, pharma, and insurers are deploying capital to integrate AI that: • Shortens revenue cycles • Boosts clinician efficiency • Reduces preventable readmissions • Enhances training and education with immersive tools In short: the demand isn’t theoretical—it’s contractually real. 4. Healthcare AI Has Multiple High-Value Exit Paths M&A activity is accelerating, and healthcare AI companies are being acquired by: • Strategics like Stryker (e.g., $130M for care.ai) • PE-backed rollups seeking operational efficiency • Big Tech, which is aggressively moving into healthcare These aren’t just tech exits. They’re life sciences, SaaS, and data infrastructure exits rolled into one—often with 3–5x higher revenue multiples. 5. We Have the Talent, Data, and Infrastructure The convergence of: • Open health data regulations (ONC Cures Act) • AI-native medical founders trained in both tech and care delivery • Decreasing costs and better modeling We finally have a clear runway to build and scale. The Next MedTech Unicorns Will Be AI-First The next wave will be built on data, AI, and automation. Investors who move now will back the next Teladoc, Intuitive, or Epic—except leaner, faster, and born in the AI-native era. #HealthcareAI #HealthTech #VentureCapital #DigitalHealth #AIinHealthcare #MedTech #ArtificialIntelligence #StartupInvestment #HealthTechStartups #VCFunding #AIStartup

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Last week at JPM — when everyone was talking about the future of healthcare — I moderated a panel focused on a fundamental question: how does the healthcare workforce actually scale in an AI-driven world? We dug into this with Carl Madi, Prabhjot Singh, MD PhD, and Ahmed Omar — and a few themes kept resurfacing:' • If healthcare spends more on labor than any other input, why are our most highly trained clinicians still buried in non-clinical work? • If AI can already handle documentation, triage, and pattern recognition, what should “entry-level” clinical work look like going forward? • Does AI compress years of clinical experience — and if so, how should supervision, trust, and team design evolve? • And the uncomfortable one: does AI actually reduce costs, or does it just help systems squeeze more output from the same people? What stood out is that the hardest shifts ahead aren’t technical — they’re economic, regulatory, and deeply human. Curious to hear from this community: What part of healthcare work do you think we’ll look back on in five years and ask, “Why were humans doing that?”

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Dual signals in global medtech innovation: FDA clears first at‑home brain stimulation device and AI smart dialysis manufacturing wins regulatory nod — a tectonic shift in therapeutic tech This week’s Medtech headlines spotlight regulatory validation of distributed therapeutic devices and AI‑enabled hardware moving toward scale. The U.S. FDA approved Flow Neuroscience’s FL‑100 — the first at‑home neurostimulation device for adults with moderate‑to‑severe depression — based on a mid‑stage study showing ~58% remission at 10 weeks, underscoring a broader shift of regulated therapy outside clinic walls. Simultaneously, Lords Mark Industries’ Renalyx AI‑based smart haemodialysis machines secured a national licence in India and CE marking, signaling global market access for AI‑driven critical care devices.   #MedTech #RegulatoryNews #AIinHealthcare #Innovation https://lnkd.in/gimCRHFf

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#AmTech Weekly Roundup: Ambience Healthcare raised $243 million in Series C funding from Oak HC/FT, Andreessen Horowitz, OpenAI, Kleiner Perkins, Optum Ventures, and Town Hall Ventures. Ambience is building AI documentation software to record patient appointments, generate comprehensive medical notes, and standardize coding/authorization workflows.   Michael Ng, Nikhil Buduma    Reveal Technology raised $30 million in Series B funding from Ballistic Ventures, Shield Capital, Booz Allen Hamilton, and others. Reveal’s two main offerings are 3D mappings generated from drone videos and mobile biometrics. They are deployed with the US Army, Special Operations Command, Marine Corps, and other NATO forces.   Garrett Smith    Prophet Security raised $30 million in Series A funding from Accel and Bain Capital Ventures. Prophet is applying agentic AI to Security Operations Centers (SOCs), or hubs for cybersecurity defenses within an organization.  Kamal Shah, Vibhav Sreekanti #VC #HealthTech #Healthcare #Defense #Cybersecurity

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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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LLMs just achieved superhuman performance in medical diagnosis. there's this recent study from harvard that shows o1-preview doing better at correct diagnosis when compared to other models and the clinicians themselves "There was substantial agreement between the two physicians evaluating the quality of o1-preview’s differential diagnosis (agreement on 120/143 cases [84%]" they went further and tested it on emergency room triage decision, treatment management reasoning, and then on real-world ICU admission calls "In all experiments - both vignettes and emergency room second opinions - the LLM displayed superhuman diagnostic and reasoning abilities" quite crazy but if you think about it, medicine requires pattern recognition across thousands of conditions, nuanced reasoning under pressure, and years of specialized training. Is it really that surprising that AI can exceed human expert performance here? maybe not?

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🚨 Big news from the frontlines of healthcare innovation: Ellipsis Health just announced a $45M funding round led by Salesforce Ventures, Khosla Ventures, and CVS Health Ventures—and it’s making headlines in the Wall Street Journal. We’ve been proud backers of Ellipsis Health at E12 Ventures because they’ve taken a bold, contrarian approach: instead of chasing efficiency at the cost of patient experience, they’ve built an emotionally intelligent AI that brings humanity back to healthcare. Meet Sage — the AI Care Manager trained on millions of real clinical conversations and powered by Ellipsis’ proprietary Empathy Engine. It delivers 24/7 support to patients with complex needs — the same patients who typically slip through the cracks because of capacity constraints and staffing shortages. This is a huge leap forward. Instead of forcing trade-offs between quality and scale, Sage shows we can have both. It’s not just automating workflows — it’s reimagining what scalable, empathetic care looks like. Strategic investors across the ecosystem — payers (CVS), platforms (Salesforce), and deep tech VCs (Khosla) — all recognize the same thing: emotionally intelligent AI is the next frontier in healthcare. Congrats to the Ellipsis team — thrilled to be on this journey with you. #AI #HealthcareInnovation #EllipsisHealth #EmpathyEngine #VentureCapital #DigitalHealth #E12Ventures https://lnkd.in/giVckKyq

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