Nate Gagne

Excited to share the news that Aegis Ventures portfolio company Ascertain has closed its Series A, led by Deerfield Management and Northwell Health, to accelerate time-to-impact of its agentic AI platform. Ascertain's agents are designed to transform healthcare operations so health systems, provider groups, and payers can spend more time, energy, and resources delivering the best care to patients. Congratulations Mark Michalski, Chris Mitchell, Eli Bernstein, Carlos D., Gregg Fergus, and the whole Ascertain team for your tireless efforts to make the company an early leader in helping shape the future healthcare workforce 👏 👏 👏   Benjamin Franklin famously said time is money. He probably would've qualified that insight with "a lot” had he worked in healthcare. Doctors spend 2x more time with paper than patients. Nurses spend a quarter of their time on codes instead of care. Healthcare administralia adds up to over a trillion dollars a year. Money is time, too. Costly, repetitive, manual processes cause errors and delays that needlessly increase the time patients and their families suffer. And they add unnecessary burden to care teams. The hybrid AI agent + people workforce of the future will reduce costs. More importantly, it will reimagine workflows to improve quality, experience, and outcomes for patients while enabling care teams to focus on care. We believe Ascertain is in the vanguard of this future. Hat tip to Aegis & Northwell, who co-created Ascertain. Shoutout to some of the human intelligence involved, who AI agents will never replace ... my partner John Beadle, Richard Mulry, David Feinberg, MD, John Noseworthy, M.D., Cortney Marcin, Edwidge J Thomas, DNP, FAAN, Kate O'Donnell, Marc d. Paradis, Greg Fitzgerald, Molly O'Neill, Nazar Al Jassar, Ryan Douglas, Mohona Paul, Samantha Violante, and many others. And I'm looking forward to working with Julian Harris, MD, MBA, @Moses Adubi, and the rest of the Deerfield team. #AI #Agents #Automation #HealthTech #Healthcare #Patients

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It had to be said! 🎯 Epic's stranglehold on healthcare IT has stifled innovation for too long and the writing is on the wall. The consolidation myth needs to die already. We were promised efficiency and lower costs, but what we got was bloated bureaucracies that prioritize profits over patients. The data doesn't lie: smaller, agile providers consistently outperform these healthcare monopolies on both outcomes and patient satisfaction. Time for a major reset in how we think about healthcare delivery.

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𝗛𝗲𝗮𝗹𝘁𝗵 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗿𝗮𝗺𝗽 𝘂𝗽 𝗱𝗶𝘃𝗲𝘀𝘁𝗶𝘁𝘂𝗿𝗲𝘀 𝘁𝗼 𝗿𝗲𝗳𝗼𝗰𝘂𝘀 𝗮𝗻𝗱 𝗳𝗿𝗲𝗲 𝗰𝗮𝗽𝗶𝘁𝗮𝗹 Health systems are stepping up divestitures and joint ventures to shore up finances ahead of looming reimbursement cuts. Non-core assets, such as labs, long-term care facilities, and real estate, are being sold or spun off, and some hospitals are being sold in markets where systems lack sufficient scale. The goal is to free up capital for reinvestment in ambulatory and specialty services.  - Ascension has exited markets like Binghamton, NY, and Michigan, selling hospitals where it lacked scale, while refocusing on ambulatory care with a $3.9B deal for 250 Amsurg surgery centers.  - OhioHealth sold select lab services to Quest Diagnostics, which can manage volumes more efficiently and reduce costs, freeing OhioHealth to channel capital into oncology and women’s health. Executives say these moves are less about distress and more about long-term strategy: simplifying operations, gaining cash reserves, and partnering with specialized operators. Analysts note that the trend reflects a broader rethink of what services health systems must own versus what can be outsourced or managed with partners.

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Transforming healthcare with AI requires industry. Industry requires capital investment. Capital investment requires return. Return requires revenue. Revenue requires reimbursement. Medicare (and transitively private insurance) reimbursement policy for clinical AI will define the incentives for the technologies we build and deploy over the next decade. Our existing fee for service codes are what the military would call cost-plus contracting. We pay for every nail, screw, and hour of labor and don't care if that was a good and efficient way to build the tank or not. Our CMS Innovation Center director, Abe Sutton, believes cost-plus is the wrong path for the future of American healthcare. ACCESS and VBC models pay for outcomes. When we have AI that can manage heart failure can we link payment to making people healthier? Doing so would unleash the might of American techno-capitalism on exactly the thing we care about in society, but there are devils in the details.

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In healthcare M&A, growth isn’t created at close — it’s created in integration. This piece is a strong reminder that value realization in healthcare lives in the details: systems, workflows, clinical alignment, revenue cycle, and culture. When integration is treated as a growth strategy, not a clean-up exercise, outcomes improve for patients, clinicians, and investors alike. Especially relevant as providers, PE sponsors, and health systems look to scale in a more regulated, margin-compressed environment. 🔗 https://lnkd.in/ekEH75gn Curious how others are thinking about integration as a growth lever, not just a risk to manage. #healthcare #MergersAndAcquisitions #GrowthStrategy #IntegrationStrategy #ValueCreation #DealMaking

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Anyone else noticing the massive data lakes growing in health systems? Is anyone else thinking that "data-centric" might become the new "patient-centric"? This article from Becker's illustrates how health systems (like Hartford Health Care) are turning into fast, deep data sources with real potential for driving insights far beyond the health system itself. Here's what jumped out for me: Hartford (with over 500 locations) is taking their digital front door and coupling it with a strong data-standardization push. Their goal is nothing less than delivering a patient experience similar to a streaming service or a travel booking sites. Which means exquisitely-tuned, patient-level predictive modeling. Well, who else could use that kind of insight? That's right. The manufacturers themselves. Could we use these clean, large data streams to: Feed agentic prediction and/insight agents? Measure the effect of our marketing initiatives? Drive new creative and strategies aimed at newly-identified barriers and drivers? We'd be less "data-informed" and more data-centric: Tracking signals, adjusting tactics, and measuring progress at the speed the world is spinning. The stories and faces that made up the patient-centric world will be digitized, ever-changing, almost infinitely-addressable murals. Transparency and compliance are going to be the foundation. At a minimum, working with grouped, de-identified data is going to be 𝘥𝘦 𝘳𝘪𝘨𝘦𝘶𝘳. And best practice probably includes (again, at a miniumum) working through a trusted data partner or licensed data provider (e.g., Symphony, IQVIA, Komodo, or a system’s research arm) under a clear DUA, and document the de-identification process. If we get it right, marketers could be delivering the same incredibly accurate, high-value experience your favorite streaming service does. Imagine that. At OEM Group, we're already imagining (and building) for THAT world. Read this! https://lnkd.in/ev3n-PUt And tell me: Am I crazy?

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Warning: Overgeneralization Ahead The range of AI expertise in healthcare is, in my view, broader than in any other industry. We’ve long relied on rigorous studies—FDA approvals, actuarial tables, sophisticated financial analyses for insurers—but AI adds layers of complexity that raw data alone can’t capture and relying on that expertise is sometimes misleading. Across sports data provides different levels of insight. In baseball, detailed stats offer deep insights into performance, but in football or basketball, what’s missing from the numbers can matter just as much as what’s recorded. The same is true in care delivery. Think for a second of two hardworking doctors. One that is average and the other that is very good. The very good doctor can look at the chart of the patient but never gets to see them; the average doctor has full access to the information and the patient. It’s not clear which doctor you should prefer without understanding your situation. It depends on the situation. Is it a fast-moving ICU crisis or a months-long mystery illness? How reliable and comprehensive is the data in the record—beyond column headers, what’s the quality of the observations? In many critical contexts—like the ICU—“stats” can lag behind reality. Seasoned doctors often say, “I just knew something was off.” Are they simply better clinicians, or are they picking up on patterns not encoded in the EHR? If we build AI without grappling with what data we’re missing—and what we’ll never capture in legacy systems—we’ll leave its true potential untapped. AI must learn to “see” and “hear” the patient: facial expression, breathing patterns, speech nuances, even subtle movements. Relying solely on today’s EHR data will certainly create value—but it will also miss the signals that matter most for patient care. PS - the below are the stats from two basketball players for the playoffs over a decade. Who are you taking?

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When CMS announced its pledges around creating a patient-centric health data ecosystem and reducing prior authorization burden, many wondered: who’s going to help make this happen? In my view, multistakeholder initiatives, whether the FHIR Accelerators or state-based initiatives, will be the bridge from aspiration to real-world progress. By aligning diverse voices—policymakers, providers, payers, vendors, and standards bodies—they create the building blocks that make pledges more than just promises. I took a closer look at how these initiatives are driving real-world progress in my latest blog. Link is in the comments (I've been told LinkedIn doesn't like outside links). I’d love to hear your thoughts.

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Introducing the Health Innovation Strategy Framework After two decades of building health startups, advising Fortune 500 life sciences firms, and designing care delivery programs at scale—I've distilled what works (and what fails) in transforming healthcare. 💡 That’s why I created the Health Innovation Strategy Framework—a blueprint to help healthcare leaders and organizations move beyond the buzzwords and into measurable outcomes. This framework is designed for: Health tech founders navigating go-to-market chaos Provider groups launching digital-first services Employers, payers & PBMs aiming to improve access, cost & experience Investors evaluating scalable models in a complex care ecosystem Organizations looking for the next best health innovation to partner, adopt or acquire 📊 Core pillars: •Innovation Culture and Infrastructure •Partnership Readiness •Product-Market Fit in Healthcare •Regulatory & Payer Navigation •Clinical Workflow Alignment •Patient Engagement •Sustainable Growth Strategy Here’s a quick look ⬇️ I’ll be diving into each of these in subsequent posts. 🔍 Want to see how this applies to your organization? 📬 DM me or contact me directly for a custom Innovation Readiness Assessment. Let’s build smarter, faster, and with real impact. #HealthcareInnovation #HealthTech #PartnershipStrategy #DigitalHealth #GoToMarket #ValueBasedCare #HealthEquity #LifeSciences #StrategicGrowth #HealthStrategy

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More data in health care does not always mean better outcomes. Most consumer data only appeals to the worried well, without considering the downstream impact on the health system. Real change requires real ROI - justified reimbursement, workflow changes, and overall cost reduction. Data is only valuable when it changes behavior, not just for patients, but for payers and providers too. The founders who win will connect consumer insight to system economics, where the real leverage lives.

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