Marc Bandt

Clinicians want to use AI but don’t have the bandwidth to evaluate all the different models. Meet Health Olymp, an AI tool purpose-built for clinicians. Here’s why this matters 👇 1. Health and life science experts gain instant access to frontier models for free. No procurement hoops or IT bottlenecks. Every clinician gets their own sandbox to explore. 2. Clinicians can compare models side by side and pick the one that works best for their use case. That transparency builds trust and sparks ideas for novel AI applications in care delivery, diagnostics, and research. 3. Most AI benchmarks are too generic or disconnected from clinical reality. Health Olymp brings frontline feedback into the loop, helping the industry identify models that perform reliably in real world clinical environments. Congrats to Ruslan Nazarenko and the Lumos team as they put AI model benchmarking directly into the hands of healthcare professionals. ⬇️ (link in comments)

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🌍 Proof of Concept: Standardizing Oncology Care with FHIR. I'm excited to present Oncology Implementation Guide;a proof of concept developed to demonstrate how HL7® FHIR® standards can streamline oncology care. This guide provides a structured framework for capturing, managing, and exchanging oncology data—spanning prevention, diagnosis, treatment, and follow-up—enabling interoperability across healthcare systems. Explore the guide here: https://lnkd.in/ggMugMUj #Kenya #OncologyCare #FHIR #DigitalHealth #HealthTech #Interoperability #CancerCare #ProofOfConcept

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𝗛𝗟𝗧𝗛𝟮𝟱: 𝗔𝗜 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 𝗠𝗲𝗻𝘁𝗮𝗹 𝗮𝗻𝗱 𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗛𝗲𝗮𝗹𝘁𝗵 At HLTH 2025, Spring Health, Oura, and Hinge Health debuted major AI advancements:  • 𝗦𝗽𝗿𝗶𝗻𝗴 𝗛𝗲𝗮𝗹𝘁𝗵 launched VERA-MH, an open-source benchmark to assess the ethics and safety of mental health chatbots.   • 𝗢𝘂𝗿𝗮 announced a large-scale study to detect early signs of hypertension through its wearable ring, expanding its cardiovascular health focus.   • 𝗛𝗶𝗻𝗴𝗲 𝗛𝗲𝗮𝗹𝘁𝗵 introduced AI-powered movement analysis and a 24/7 assistant, Robin, to support musculoskeletal care. Together, these innovations reflect the industry’s shift toward safer, more personalized, and preventive AI-driven healthcare.

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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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Distribution is becoming the moat in healthcare AI Anthropic’s recent Claude for Healthcare update was a good example: the main features were not focused on model performance, it was connectivity, making Claude usable inside the healthcare enterprise stack. The main drops were: -> Coverage rules (CMS Coverage Database connector): check whether a treatment is reimbursable and under what conditions -> Coding (ICD-10 connector): translate clinical language into billing/diagnosis codes -> Provider verification (NPI Registry connector): validate provider identity for credentialing and claims -> Prior Authorization Agent: assemble documentation and rationale for approvals/appeals -> Interoperability tooling: make it easier to plug into health IT systems This shift creates real opportunity for founders. Healthcare is fragmented by country, system, and workflow, so teams that can embed applications deeply in specific workflows can build meaningful markets, even from narrow starting points. Source: https://lnkd.in/dFEi8UDP

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Hot take: betting or investing in any niche EHR right now (e.g. AI-native EHR for X clinical specialist or X vertical like Longevity) when AI code development exists and only continues to get better with each new model release has to be dumbest pre-AI SaaS era thing an investor can do. Here's why ⤵️ The EHR market is essentially split into 5 categories: #1. Outpatient EHR-enabled private practice (doctor or clinical owned) #2. Outpatient tech-enabled practice (PE, VC, family office owned) #3. Outpatient tech-enabled practice (MBA or bootstrapped owned) #4. Startup enterprise (PE or VC backed) #5. Inpatient hospital VC backed EHRs primarily make their money selling to #2-4, with the Epic's of the world taking most if not all of 5. For #1 there really isn't any true TAM since it's difficult to acquire this customer even when giving the EHR product away for free. But here's what these EHRs are not telling you and why they're all racing to update their API docs. They hope that #2-4 will continue to use their solutions to build with AI vs exiting and vibe coding their own in-house solutions. So when you hear them say their EHR product is safe from AI, that's not true. Right now the Epics of the world are safe but it's customers in categories 1-4 who will 100% vibe code their own solutions. #VibeWithCline #LetDoctorsVibe

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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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Health tech startups are scrambling to adapt as labor shortages and pricing pressures loom large. With EHR giants like Epic calling the shots, how are founders supposed to keep their heads above water while navigating this chaotic landscape? #HealthInnovation #DigitalHealth https://lnkd.in/gYbCjspE

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TheFounderVC has a truly compelling team - entrepreneurs and operators that have scaled from 0-1 and to exits across a variety of markets - some of whom are fellow classmates. They have built strong founder and VC networks over the last 25 years in tech and are now leveraging that access and experience on behalf of their portfolio. It clearly resonates with founders, as their early portfolio is truly compelling.

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Amazon will be the FIRST to show us what a vertically-integrated, Healthcare Provider + Patient AI Agent can deliver for society. My 4 thoughts on what this all means… First, what Amazon announced: → Amazon One Medical (a hybrid in-person + virtual primary care service) launched a patient-facing, AI assistant within its patient app - which has access to the patient’s medical history and lab results → Patients can ask questions about test results, health/wellness and symptoms - and the AI will connect the patient to a human clinician as needed → The AI can even schedule appointments with a clinician and make requests for prescription refills - which of course can be filled by Amazon Pharmacy → One Medical membership (and thus access to the Health AI assistant) can be purchased by Amazon Prime members for $9/month or $99/year. This news didn’t get the fanfare of ChatGPT for Health, but I actually think this is a LOT more interesting. My 4 thoughts on why: 1/ The biggest knock against ChatGPT for Health is that it’s disconnected from the care delivery system. But Amazon One Medical is a care delivery system launching its own ChatGPT for patients - it’s actually using agentic AI to help manage the longitudinal patient - provider relationship. Your medical record is already accessible. AI will schedule appointments or get you escalated to a clinician. Isn’t that the holy grail? 2/ Talk about verticalization: Amazon has been quietly buying up the components to create a vertically-integrated healthcare system. It bought PillPack to become Amazon Pharmacy. It bought One Medical to have primary care. It’s now using Agentic AI to connect all the pieces. Given how small margins are in care delivery (OneMedical is probably still losing money), if Amazon can turn a profit through ancillary services like Pharmacy, it can find a way to make this all work (unlike ChatGPT for Health… which is probably going to lose a bunch of money indefinitely) 3/ Amazon might actually make healthcare membership fees work by selling consumers on a life-time relationship across both health/wellness and acute medical care: groceries (Whole Foods), medications (Pharmacy) and medical care (OneMedical) all from a single health subscription. Plus flywheel effects as consumers of one product are more likely to be consumers of the next. How long until we see Amazon’s Health AI embed Whole Food purchase suggestions in the AI experience? 4/ For a long-time I’ve half-joked that Amazon Prime is a “human tax” - as in Prime will eventually be so universally used that Amazon will be the first company to tax every human alive. Well if you want healthcare from Amazon too, the tax cost just doubled. 8 billion humans * $200 / human / year = $1.6T annual “human tax” for Prime + Healthcare. Create a bundle of services that every human will want and you’ll be the biggest company on Earth - a more conceivable path than most Consumer Health AI startups.

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