Matteo Zanella

My 7 biggest takeaways from The Permanente Medical Group, Inc. experience using AI Scribes after 1 year. This is particularly interesting given the switch from Nabla to Abridge after the decision to go enterprise-wide with AI Scribes by Kaiser Permanente. 1️⃣  72% of physicians used the AI Scribe at least once among a sample of 10,000+ physicians who were given access Also, at the end of 2024 the adoption curve was still trending up, so it may not have plateaued just yet. 2️⃣ 34% of physicians used AI Scribes in at least 100 patient encounters… but that means the other 38% of physicians who tried it only used it for an average of less than 0.38 patient encounters per work day (< 100 encounters / 260 work days) In other words, usage is driven by the top cohort of users. This is what will drive the argument from health systems from why the pricing model should not be “per user” and why the enterprise license should be at a fraction of the original “per user” costs. Ambient vendors will argue that the “per user” pricing already baked in this distribution of usage among possible users, and this is still a fraction of what hiring human scribes for every clinician would cost. 3️⃣ Highest physician adoption was among mental health (42%), primary care (32%) and emergency medicine (32%), based on % adoption by clinicians in each specialty. No real surprises here. 4️⃣ The top 33% of physicians who tried the AI Scribe (“High Users”) were responsible for an overwhelming 89% of the total usage of the AI scribe. In fact, High Users also were the ones who needed it the most - as pre-AI Scribe they tended to be physicians with more time spent in the EHR per appointment and fewer patient visits per day. Not provided: did High Users end up now doing more patient visits per day than before? 5️⃣By the end of 2024, High Users spent even less time in notes than Low Users and Non-Users (i.e. didn’t try AI scribes even once) → High Users went from 4.5 minutes/note to 2.5 minutes/note → Low Users went from 3.75 minutes/note to 2.9 minutes/note → Non-Users went from 3.75 minutes/note to 3.4 minutes/note Will data showing that maybe they could save 30 seconds per note motivate the Non-Users to become Users? I’d guess No. 6️⃣ 57% of patients experienced no difference in time physicians spent looking at a computer screen (caveat: small n=118 sample) This was surprising. Begs the question: were some physicians weren’t looking at a screen much normally during a visit, or whether they just couldn’t shake the habit? 7️⃣ Adoption of AI Scribes were mostly agnostic to the vendor Although the total physician adoption essentially doubled after switching vendors, the team felt that this was related more to: → The positive experience of Vendor 1’s pilot → Increased awareness and support provided over 2024 → Implementation of EHR integration with Vendor 2 Hard to tell how KP truly felt about this or if they were just being nice. Full article in the comments 👇

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There's a new question in every health tech buying cycle that didn't exist 18 months ago: "Is this already on the roadmap of our foundation model vendor?" As we discussed in our 2026 healthcare predictions, we are entering a moment where the end user, clinicians and operators included, can increasingly build software themselves using agentic coding environments. In practice, this shows up when a CIO asks whether a proposed point solution is meaningfully different from what their existing foundation model could deliver with internal prompts, guardrails, and a few weeks of engineering time. This shift is quietly reshaping the competitive calculus. Startups selling into healthcare enterprises no longer compete only with the EHR vendor’s roadmap. They also compete with what a foundation model provider can plausibly ship for that customer, often faster and at lower marginal cost. Importantly, while the moat around building software is eroding, the moat around running software in healthcare is not. Healthcare enterprises are not set up to independently handle deep workflow integration, continuous iteration, reliability at scale, and governance across clinical, legal, and regulatory dimensions. That operational gap is where durable companies are still built. We expect this dynamic to introduce real friction into buying cycles for point solutions with thin moats. At the same time, it expands opportunity for companies with defensible data assets, deep workflow entrenchment, and true platform potential. Artera and Atropos Health are two strong examples from Breyer Capital's portfolio, both highlighted in the article. Special thanks to Brian Gormley for featuring our perspective in today's The Wall Street Journal piece on OpenAI and Anthropic's entry into healthcare. Jim Breyer Daniel Breyer Andre Esteva, PhD Brigham Hyde

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Part 3 (Achieving Key Outcomes) of our piece on Tech-enabled Services model is out now. Check it out and pls share feedback, thx to all who participated in producing this final part Sam Holliday Stephen Grinich "A frequent mistake among emerging companies is prematurely celebrating enterprise contracts without establishing a strong mechanism for patient activation. Despite securing lists of eligible patients from payers, actual activation rates can fall far short of expectations, resulting in disappointing revenue and potential financial strain — especially if operations were expanded in anticipation of higher engagement. If a company fails to engage this population effectively, both the overall contract value and the business’s efficiency and profitability can be severely impacted. In our experience, patient activation and engagement rates can run the gamut between 5% and 75%, with most companies achieving rates between 10–40% of an eligible population. To determine effectiveness, the activation / engagement rate must be evaluated against the enterprise customer’s goals and the financial model of the business. Some Medicaid health plan partners may be very satisfied with 5–10% activation and enrollment rates, while a risk-bearing provider partner or Medicare Advantage plan looking to close care gaps may be appalled by a 50% activation rate. Finally, the Revenue and LTV / CAC of a business will be defined by a company’s engagement / activation rate so this will drive the ultimate revenue potential and profitability of the model." https://lnkd.in/gWNANCkn

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Andreessen Horowitz is one of the world’s most influential venture capital firms Partners David Haber, Julie Yoo, and Daisy Wolf describe companies operating at the intersection of fintech and healthtech as "payvidors"—businesses that not only deliver care but also solve the question of how patients and providers pay for it.This thinking sits at the very center of HealthCap Africa’s investment thesis. We focus on healthtech and fintech because we see, every day, that healthcare delivery is meaningless without the ability to pay for it. A diagnostic lab, a hospital, or a telehealth platform can only scale sustainably when patients have access to financial tools—insurance, credit, payments, or savings—that make care affordable and accessible. That is why our team combines deep subject-matter expertise across both sectors. We back the entrepreneurs building at this frontier: health innovators who improve quality of care, and fintech disruptors who unlock access to it. Together, these companies create the infrastructure for healthier, longer lives across Africa and beyond. 📖 Read David Haber and his team’s excellent piece on payvidors here: https://lnkd.in/dvMJ_KtZ

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Those “direct-to-physician” CDS AI tools like OpenEvidence and DoximityGPT? They're now going after health systems too. My 5 thoughts on how this will all play out: First, the gist of what was announced: → Sutter Health will integrate OpenEvidence with Epic, allowing physicians to access the AI medical search engine directly within the patient chart → UC San Diego Health is rolling DoximityGPT - their AI medical search engine - across the organization, while also making its AI scribe tool available My 5 thoughts on all this: 1/ This move to compete in the enterprise was 100% inevitable. Especially for OpenEvidence that just raised $250M at a $12B valuation, the only way to justify that valuation is to keep rapidly increasing revenue growth - and they can’t do that without increasing their Total Addressable Market beyond individual physicians. If they are truly already used by 40% of US physicians, then revenue growth is going to plateau if they don’t grow into adjacent markets. 2/ Is the Sutter Health integration of OpenEvidence and Epic just an embedded view for easy access? Or is there true data integration where a doctor can ask a question and OpenEvidence already has full context about the patient, and thus can produce a personalized answer? From the press release it sounds like just an embedded view for now, but full data integration for personalized CDS - the holy grail - seems inevitable. We know Evidently, AvoMD and others have already done this so it’s a matter of when, not if. 3/ What will be the business model? I suspect it will switch from an ad-model to a SaaS model. Health systems typically avoid ads to doctors and will also require more significant professional services for integrations, training, account management, etc and thus also cost more. 4/ How will this all work when EHRs are pushing doctors to use their own AI clinical assistants (e.g. Epic Art)? Unlike the growing competition between EHRs and AI scribes, I suspect Epic will allow companies like OpenEvidence, Doximity and UpToDate to just directly connect into Art - so doctors can access the same CDS experience. Chat itself is now a universal form factor, and as long as you’re selling licenses, the CDS companies don’t care what the access point is. As for Epic, they want to be a “software factory” and not a clinical guidelines/content factory - so I predict Epic will release a Toolbox category for CDS AI to integrate with Art. 5/ This will put major pricing pressure on UpToDate - however, UpToDate will have a head start on integrating with EHR AI assistants like Epic Art, given their longstanding partnerships with the EHRs. If I were UpToDate, I would be doing a mad dash to be the first to get AI CDS into Art and figure out a revenue share that incentivizes Epic to promote their product.

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Huge news from CMS for anyone building in tech-enabled care delivery & focused on chronic conditions. Yesterday, CMMI released a new outcomes-based payment model that some industry insiders are calling the biggest tailwind for digital health since COVID. It has major implications for companies managing chronic conditions, remote monitoring, virtual care, and value-based models. I spent time digging into the details with Jared Augenstein and Randi Seigel, who have been in the weeds on the ACCESS model since it dropped. Their insights helped me unpack: • How outcomes will actually be measured • Which digital health companies are best positioned • Who won’t qualify (and why) • What still isn’t clear about payment rates and targets • How this could impact PCPs, beneficiaries, and infrastructure vendors • Where the fraud and compliance risks live If you're working in digital health, chronic care, RPM, MSK, metabolic health, or infrastructure…this one is worth a read. Full breakdown here: https://lnkd.in/erSbFkd3

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Two healthcare axioms can explain much about effectively serving patients: Care delivery isn’t just local, it’s personal; and no company can succeed without partners. I knew when I co-founded Sprinter Health in 2021 with Cameron Behar that we would have to find a way to work within the existing ecosystem while offering a better patient experience, or we wouldn’t make much of a mark.  Cameron and I both shared a technology background, so we spent most of our formative conversations trying to figure out how to use tech to be useful, without it overshadowing the patient interaction or becoming performative. I'm pleased to announce a $55M Series B round led by Holly Maloney and General Catalyst – GC initially led our Seed round in 2021, and they were the right partner to help us push harder on our mission as we really started to scale. Holly and the GC team share our passion to expand access to care for people who need it most, all while improving outcomes and delivering real value to health plans and providers.  We’re also grateful to our participating investors from Andreessen Horowitz Bio + Health, the Regents of the University of California, Google Ventures, Accel, and more. By investing heavily in using technology to make an in-home care delivery model not just possible but actually viable, we’ve been able to make huge strides in helping patients across the country - almost 100,000 now - and increasing access to care. From the ground up, we’ve created a logistics, data, and engagement platform that allows us to be extremely efficient with where we deliver care, making Sprinter visits the highest ROI in terms of care gaps closed for plans in the industry, all while maintaining over a 90+ NPS.  We call our mission “Healthcare Untethered” - the idea that most resonates with us is making sure people get the preventive care they need at no personal cost. We are extremely ambitious, and have come a long way from starting with basic blood draws, to now having over 20 services that run the gamut from hypertension checks, diabetic retinal exams, to full annual wellness exams from NPs delivered in a hybrid fashion. We first launched in just California around 2022, and now will be in over 20 states before the end of this year. Our “Sprinters” – cross-trained as medical assistants, community health workers, and phlebotomists – have served patients from ages three to 103, on behalf of national health plans. I’m extremely proud of what the team has achieved and thankful to all our supporters, but we have a long - a LONG - way to go to reach the impact that we know we are capable of. Hand-in-hand with the quality and risk departments of health plans, Sprinter Health will be seeing millions of patients over the upcoming years, so please reach out if you want to go on this journey together!

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Three incredible days at #JPM2026. Same conversation with 10+ health system execs: "We're building our AI strategy. Evaluating vendors. Need to pick the right partners." This sounds familiar. 2009-2012: The EHR decision. After the HITECH Act, health systems spent 18-24 months evaluating Epic vs. Cerner. Consultants. Committees. RFPs. Multi-year implementations. The logic made sense: EHRs were monolithic platforms with huge switching costs. You had to get it right. 2025: The AI decision. I'm watching health systems do the same thing. "AI steering committees." "Strategic AI partner" RFPs. Trying to pick winners. But there's a critical difference: EHRs were a single, massive platform decision. AI in healthcare is dozens of different problems that need dozens of different solutions. Here's what health systems are missing: They're looking for "the AI vendor" when they should be building "an AI portfolio." There's no single AI platform that solves:   → Documentation burden (ambient notes) → Radiology throughput (workflow optimization) → Clinical trials matching → Revenue cycle optimization (across specialties) → Clinical decision support These are different problems. Different technologies. Different vendors. Different timelines. Some need FDA clearance and 24-month validations. Some can pilot in 90 days. Some integrate with Epic. Some replace parts of Epic. You can't solve all of these with one "strategic AI partnership”....no matter that Anthropic is saying right now. <ducks> The AI landscape is evolving too fast for monogamous vendor relationships. 6 months ago: GPT-4 for clinical documentation. Today: Ambient listening, agentic workflows, multimodal imaging analysis. 6 months from now: Something else entirely. That's why you need exposure across the whole landscape—not a bet on one vendor. The mistake I see health systems making: Approach 1: "Strategic Partner" Strategy Pick one AI vendor → Enterprise deal → 3-year commitment → Hope they solve everything Result: You're locked in. Technology moves on. You're stuck in vendor negotiations while competitors move faster. Approach 2: "Portfolio Strategy" Deploy capital across multiple companies → Take equity → Co-develop solutions → Maintain optionality Result: You capture upside. You shape products. You're first to new capabilities. You have relationships across the ecosystem. After 20 years building innovation platforms at JPMorgan, Mousse Partners, Blueprint Health, Junto Health, Atlantic Health: In fast-moving markets, portfolio strategies beat single-vendor bets. Healthcare AI is moving fast. The question isn't "Which AI vendor should we pick?" The question is: "How do we build an AI portfolio that gives us the most optionality" If you're thinking about this, let's talk. 📩 douglas.m.hayes@gmail.com ☎️ 215-620-2032 #healthcareAI #digitalhealth #venturecapital #innovation

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As we enter the post-EHR era, it’s worth understanding who won the first battle: Epic, the leading U.S. EHR founded by Judith Faulkner. These insights are based on the recent "Acquired podcast", covering Epic’s story. Here are the key takeaways: 1️⃣𝐉𝐮𝐝𝐢𝐭𝐡 𝐅𝐚𝐮𝐥𝐤𝐧𝐞𝐫: 𝐭𝐡𝐞 #𝟏 𝐟𝐞𝐦𝐚𝐥𝐞 𝐞𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫 Judith Faulkner may not be widely known, but she deserves a seat alongside Steve Jobs and Bill Gates. A generational talent (she learned Fortran in a week), Faulkner built the world’s leading #EHR system from scratch.  2️⃣ 𝐊𝐚𝐢𝐬𝐞𝐫 𝐏𝐞𝐫𝐦𝐚𝐧𝐞𝐧𝐭𝐞 𝐢𝐧 𝟐𝟎𝟎𝟑: 𝐭𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐦𝐨𝐦𝐞𝐧𝐭 𝐟𝐨𝐫 𝐄𝐩𝐢𝐜 KP, the largest hospital system in the U.S., first tried to build its own EHR, and failed. IBM won the initial KP tender, then failed too. In the final round, #Epic and Cerner were the last two standing. The night before the pitch, Epic president Carl Dvorak flew to California, saw the plan, and said, “No, we need an Excel model showing KP’s daily transaction flow and how our system can handle it with zero downtime.” That’s how Epic won. 3️⃣ 𝐖𝐡𝐲 𝐢𝐬 𝐄𝐩𝐢𝐜 𝐭𝐡𝐞 𝐧𝐮𝐦𝐛𝐞𝐫 𝟏? 𝐓𝐰𝐨 𝐦𝐚𝐢𝐧 𝐫𝐞𝐚𝐬𝐨𝐧𝐬: 𝐫𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 Epic’s reliability comes from its single, unified database (Chronicles), unlike competitors who patched systems together through mergers. When Epic gives a timeline and budget, it usually delivers. Its clinical and billing systems run on the same codebase, ensuring nothing gets lost between departments. For #hospitals seeking seamless, end-to-end operations and financial stability, Epic’s architecture is hard to beat. ⚠️ Now, as we enter 2025, the post-EHR era is beginning, and we’re at a crossroads, with several open questions: ➡️ 𝐒𝐢𝐧𝐠𝐥𝐞 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞𝐝 𝐬𝐲𝐬𝐭𝐞𝐦 𝐯𝐬. 𝐛𝐞𝐬𝐭-𝐨𝐟-𝐛𝐫𝐞𝐞𝐝? Other industries have seen value chains unbundled and then re-bundled through platformization. Waystar (RCM) is gaining traction in the U.S. by excelling in its niche. Can it expand and re-bundle beyond RCM? ➡️ 𝐖𝐢𝐥𝐥 𝐡𝐨𝐬𝐩𝐢𝐭𝐚𝐥𝐬 𝐝𝐢𝐬𝐚𝐩𝐩𝐞𝐚𝐫? The hospital business model is broken and likely to be unbundled. What does that mean for the healthcare tech stack? ➡️ 𝐖𝐢𝐥𝐥 𝐩𝐫𝐨𝐯𝐢𝐝𝐞𝐫𝐬 𝐫𝐞𝐠𝐚𝐢𝐧 𝐜𝐨𝐧𝐭𝐫𝐨𝐥? Large hospitals tried to build / control their own EMR/EHR during the early EHR era (e.g., KP) and failed. Will they succeed in the post-EHR era? ➡️ 𝐖𝐢𝐥𝐥 𝐄𝐩𝐢𝐜’𝐬 𝐜𝐮𝐥𝐭𝐮𝐫𝐞 𝐫𝐞𝐦𝐚𝐢𝐧 𝐚𝐧 𝐚𝐬𝐬𝐞𝐭? Epic enforces strict protocols, no remote work, and near-robotic employee behavior. This worked over the last 20 years. But will it hold up in a future that demands agility and creativity? ➡️ 𝐄𝐩𝐢𝐜 𝐝𝐢𝐠𝐢𝐭𝐢��𝐞𝐝 𝐜𝐚𝐫𝐞. 𝐖𝐢𝐥𝐥 𝐀𝐈 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦 𝐜𝐚𝐫𝐞? Tempus AI describes Epic as a “system of records,” arguing that future winners will be “systems of insights". Can Epic still win in this new, AI-driven world? #healthtech #healthcare

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🔥🔥 PANEL ALERT 🔥🔥 What gaps may AI fill with the recent policy impacts on Medicaid?  Coyote Ventures 2025 Health Equity Innovators Fall Gathering will feature an expert panel discussing the impact of AI in Healthcare with a particular focus on its implications for Medicaid and Medi-Cal. As we are past the mid-point mark of 2025, AI and OBBBA are reshaping U.S. health policy in profound ways, from expansive new federal and state guidelines to sharp debates around oversight and authority. Our discussion will dive into the themes of bias, equity, and accountability in AI, and what these evolving mandates mean for those developing, deploying, or relying on AI-driven solutions in healthcare. With Medicaid and Medi-Cal covering some of our most vulnerable populations, the stakes couldn’t be higher. I’m looking forward to an engaging conversation with Priyanka Vaidya, Pooja Mittal, and Stella Tran - exploring how we can ensure AI not only advances innovation but also builds trust, fairness, and better outcomes. Curious to hear your thoughts: can AI truly help reduce disparities in Medicaid care, or will it deepen them?

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The Future of Healthcare Operations: A Collection Over the past few months, I’ve been exploring a single, urgent question: If we can’t hire our way out of healthcare’s challenges, how do we redesign the system to scale, without breaking the people inside it? My answer: scalable, invisible, intelligently governed AI. Here's the arc: 1️⃣ The Burning Platform – Adjusting to the Trump Administration Funding Cuts: A Once-in-a-Generation Opportunity - https://lnkd.in/gnhp5Ftp 2️⃣ The Labor Trap – Why Healthcare Can’t Hire Its Way Out Anymore - https://lnkd.in/gXnXbwgA 3️⃣ The Human Side – Health System Layoffs: Holding Two Realities - https://lnkd.in/g2_WMMYa 4️⃣ Finding the Right Opportunities – Three steps for identifying the right opportunities for healthcare automation - https://lnkd.in/g_ZK3xt2 5️⃣ Governance as Launchpad – Debunking the 9 Most Common Myths About AI Governance in Healthcare - https://lnkd.in/gNZsaR3G 6️⃣ Good Pilot, Bad Pilot – Hidden Signals Behind Scaled Impact - https://lnkd.in/gjpKxh-z 7️⃣ Invisible UX – The Best UX in Healthcare? None at All - https://lnkd.in/gaq-pJzd 8️⃣ From Point Solutions to Platforms – Why We Built a Healthcare-Focused Agentic AI Platform (coming soon — how a platform approach tames AI sprawl and accelerates impact) 9️⃣ Scaling Beyond Human Limits – Elastic AI Enabling Scalable Healthcare Operations Capacity (coming soon — six real-world use cases where elastic AI outperforms fixed staffing models) Just as health systems once moved from dozens of disconnected IT systems to unified EHR platforms, the next leap will be from dozens of disconnected AI tools to elastic, platform-based AI. Those who make this shift first will set the standard for healthcare productivity, patient experience, quality outcomes, and financial sustainability in the decade ahead.

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In our latest newsletter, I go deep into why we believe the next three years of healthcare innovation will be defined by two specific trends: Voice Agents and Hybrid AI Care Models. Here is the quick breakdown: 🎤 Amplifier Health (Voice AI Diagnostics): Amit Mehta, Jeremy Barber, and Peh Keong are doing the impossible. They have built a Large Acoustic Model that can screen for multiple medical conditions from a phone call. By focusing on the physical properties of sound rather than just words, they are creating a screening and diagnostic tool that is accessible to anyone with a phone. 🧠 Meru Health (Hybrid AI-Enhanced Care): Kristian Ranta, Riku Lindholm, and Henri Koponen are solving the "efficacy crisis" in mental health. Their 12-week program treats the mind and body together by combining licensed clinicians with biofeedback technology. With millions of lives covered, they are proving that value-based care is the only way forward. The Bigger Picture: We believe the "Golden Age" of healthtech is moving toward a model where AI handled the routine data and diagnostics while humans focus on high-level clinical decisions. Whether it is a voice agent triaging a patient or an AI-enhanced clinician monitoring recovery, this hybrid approach is how we solve for both access and quality. Read the full breakdown of our investment thesis #HealthTech #VentureCapital #AI https://lnkd.in/dqDGBnJF

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At HLTH Europe, industry leaders Terri Couts, RN-BC MHA, David Rhew, M.D., Saad C., Ali Parsa and Isabelle Zablit-Schmitz gathered to discuss the groundbreaking potential of Ambient Listening technology. This innovation promises to transform healthcare by slashing documentation burdens while enriching patient care quality. Currency in healthcare is time! 🎤 Ambient Listening alleviates 50% of documentation hassle, providing clinicians more time for crucial patient interactions. As AI integrates seamlessly within EHR systems, clinicians and patients alike benefit from a streamlined flow of information. 🔒 Privacy, consent, and security are pivotal challenges we face, yet they must be addressed for Ambient Listening to truly flourish. The technology not only assists with documentation but opens avenues for AI to monitor health indicators and enrich clinical decision-making. 👍 This tech is highly appreciated by clinicians, as it can be fitted into existing workflows. Ambient Listening is poised as the most scalable AI, with particular success in primary care and expansion into acute settings on the horizon. 🔍 True Value of Ambient Listening: the improvement in the quality of patient outcomes, not merely increased patient throughput. 🚀 As AI pushes boundaries, we stand at the threshold of reimagining healthcare delivery, moving from resource constraints to virtual abundance. This evolution parallels the smartphone transformation—it begins as a novelty and becomes indispensable. 🔑 The session affirmed our journey towards harmonizing cross-disciplinary care, breaking silos, and embracing a future where technology profoundly supports healthcare excellence.

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The hardest conversation in digital health fundraising isn't about your technology. It's about proving your revenue model works in healthcare's unique buying environment. When investors ask for "traction," they're really asking: Can you navigate the 18-month sales cycles, the committee-based purchasing decisions, and the risk-averse culture that defines healthcare procurement? Most health tech founders think traction means pilot programs with impressive user metrics. But healthcare buyers evaluate technology differently from other industries. They care less about your AI capabilities and more about whether you can reduce their cost per patient encounter or improve their HCAHPS scores. The gap between pilot interest and contracted revenue in healthcare is significant. Clinical champions support your solution, but procurement teams seek proof of ROI. IT departments are concerned about the challenges of integration. Finance requires budget justification that withstands annual planning cycles. Real traction in healthcare means demonstrating three things investors understand: Your pilots convert to paid contracts at predictable rates. You've proven your solution integrates without disrupting clinical workflows. Your customers can measure and defend the value you deliver internally. The challenge isn't developing better healthcare technology. It's creating a revenue model that fits healthcare's operational realities. Health systems don't invest in innovation just for the sake of it. They acquire solutions to address specific operational issues that affect their finances or clinical results. Your traction story should reflect this purchasing behavior. The companies that successfully scale in digital health aren't necessarily the ones with the most advanced technology. They're the ones who understand healthcare's unique market dynamics and build their go-to-market strategy accordingly.

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The Fragmentation Problem in Healthcare Program Integrity (some thoughts after attending the HPRI Chicago 2025) One thing that struck me at HPRI Chicago was how payment integrity and FWA teams often don't talk to each other. They're frequently reporting to different leaders, working on what are really sub-puzzles of one problem, but approaching them from completely different angles. Part of what keeps these teams apart is all the jargon we've built up around what should be straightforward work. Pre-payment, post-payment, claim edits, prior authorization, utilization management, data-mining - these terms have become more like barriers that facilitate the divide between teams and technologies and point solutions. I think in the end, the task is as simple as: find things that don't look right, and if they're not right, make them right. The level of expertise in this field ranges widely - from people who mostly repeat buzzwords to those who actually understand the underlying problems. It's always enlightening to find people I'd like to learn from and showing lots of their passion, but I think the average level isn't quite there. Correction. Let's say it is not that they are not good at what they do. They know their domain well enough, but it's hard for them to cross over into other areas. The real difficulty of having a comprehensive view of program integrity is that it requires a combination of medical expertise, policy expertise, analytics, informatics, and cybersecurity. It's often difficult to excel in just one vertical, but program integrity demands all of these at a high level. Sometimes this work is run by medical officers who understand data and policy, sometimes by data experts who grasp the other pieces. But finding that combination isn't easy. The industry's immaturity shows in the lack of senior leadership dedicated solely to program integrity at most payers. This absence of executive accountability reflects how the field still treats program integrity as separate functions rather than an integrated discipline requiring unified leadership. While CMS and other regulators are pushing for more integrated approaches to program integrity, the fragmented structure makes it harder for organizations to respond cohesively to regulatory expectations and reporting requirements. This makes me think there may need to be a leadership position called Chief Program Integrity Officer - someone who oversees the correctness and compliance of all transactions and records. It's a bit like an extended concept of Chief Privacy Officer, but broader. They'd need to understand the business of health insurance regarding policy and medical practices and data, and most importantly, they'd need to understand how it all should work together. What are your thoughts? Is it about time to have Chief Program Integrity Officer in payers? Image credit: Gemini

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If you’re still thinking of pricing as a line item, you’re already behind. In healthcare, climate, and infrastructure, your revenue model is your system design. It’s how you -->Align incentives across fragmented stakeholders, Capture value across time and interface, and Preserve mission without sacrificing scale. I just helped a women’s fertility platform re-architect their monetization model into three distinct revenue streams: DTC, reimbursable care, and B2B SaaS for providers... all without diluting their core product or confusing the user. This results in inncreased LTV, more aligned stakeholders, and a system that can actually scale. I believe every early-stage founder in complex categories should be designing hybrid revenue models from day one. 👉 Read the full piece on Substack: https://lnkd.in/gt9PcfKN

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