Jane Ren

The interviewer of this episode was more impressive than the one who was interviewed but I enjoyed it! Every health system should challenge providers with real-time cost data inside a clinical, evidence-based context. “We’ve built alerts” or “made it hard to order that” is not changing a culture! Cultures change when approaches iterate and alignment models promote and support the change.

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If you’re building a health tech startup, here’s a useful perspective from the accelerator side. At ViVE, I spoke with Keith Camhi, Managing Director of the Techstars Healthcare Accelerator powered by Permanente Medicine Mid-Atlantic States. The program invests in early-stage startups and helps founders run pilots with physicians in the Kaiser Permanente ecosystem. Some interesting takeaways: • Techstars still prioritizes “Team, team, team” above everything else; • Founders in the program are interviewed by physicians before acceptance; • The goal isn’t just mentorship — it’s getting real pilots with providers; • AI startups dominate applications, but the focus remains on real clinical problems. Applications for the next cohort open soon, so founders may want to keep an eye on it. Short interview from #ViVE 👇 🎥 Watch here: https://lnkd.in/gNN_5628 #Vive2026 #digitalhealthinsideout #health2tech #digitalhealth

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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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Build for the 3 Waves of Innovation in Healthcare Healthcare is poised for a dramatic shift. It's not just incremental change; we're talking about a fundamental rewrite driven by three converging waves of innovation. Imagine the landscape of healthcare being completely reshaped, leaving no aspect untouched. This isn’t a gradual evolution; it's a rapid transformation. The 3 Waves of Innovation AI is accelerating everything from diagnostics to personalized treatment plans at an unprecedented pace. It's like having a supercharged research and development team at your fingertips. Simultaneously, Web3 is laying the groundwork for secure, decentralized data, effectively putting patient records back into the hands of the individual, much like how you built your businesses by empowering your teams. Finally, Biotech is pushing the boundaries of what's possible in human health, from gene editing to regenerative medicine. This convergence isn’t just adding up; it’s multiplying, creating a new paradigm for healthcare delivery. It's akin to identifying and capitalizing on a market disruption before anyone else. Healthcare access will be redefined, with remote diagnostics and personalized medicine reaching underserved populations. Professionals will evolve, with AI handling routine tasks, allowing them to focus on complex cases. Data-driven decisions will become the norm, with predictive analytics anticipating health crises before they occur. Picture a world where healthcare is proactive, not reactive. It's like moving from reactive problem-solving to proactive strategic planning, a skill you’ve honed over your career. A Builder’s Market We're moving beyond the Information Age, where data was king. Now, intelligence is the driving force. This shift will democratize knowledge and empower individuals and small teams to innovate, much like your own journey in building successful businesses. Millennials, with their unique perspectives, will lead this transformation, shaping healthcare for generations to come. This transition will be dynamic, and we need to be prepared. Elevate Health 2050 is designed to help navigate this change, providing the insights and connections needed to capitalize on these emerging trends. It's about staying ahead of the curve, something you understand well. How will these three waves of innovation impact your role in healthcare? What opportunities do you see emerging? Join the conversation and explore the possibilities of the Intelligence Age at the Elevate Health 2050 substack: https://bit.ly/4efm4BE Let's discuss and learn together. Join our community and discover how to leverage these innovations.

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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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Aditya Narayan and I are proud to share a Health Affairs Scholar piece on CMMI's new ACCESS payment model. ACCESS will pay for care delivered by AI (with or without a clinician) for Medicare patients. This is the first time ever Medicare will pay for care without a person in the loop. It is for chronic-disease management: recurring, condition-specific payments tied to clinical improvement, rather than billing for discrete encounters or tightly defined remote-monitoring activities. The promise is straightforward, more reimbursement for technology-enabled longitudinal care and more choice and competition for patient care. It could lead to lots of startup and innovation. It could also lead to lots of hard to cancel subscriptions and FWA. There are still many unanswered questions about payment levels, how quality is measured, how risk is adjusted, and how these patients’ facing technology enabled services will coordinate care with the traditional delivery systems. https://lnkd.in/grDfXDH5

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Premiering now on the Digital Health Heavyweights Podcast I have a conversation with the co founder and CEO of Bonfire Analytics Vinay Nagaraj! One great moment was when Vinay says that while business moves at the speed of trust, so does sales. I could not agree more. It requires a huge level of authenticity, being able to connect with a person, as a person. Building deeper relationships. There is a lot to learn on this weeks episode. Vinay shares his journey from biomedical engineering to healthcare sales, discussing the challenges and successes he faced while scaling revenue at Roundtrip. He emphasizes the importance of authentic relationships in sales, the role of data in healthcare, and the key traits he looks for in salespeople. Vinay also discusses the inspiration behind Bonfire Analytics, its mission to accelerate healthcare technology adoption, and the common mistakes healthcare companies make in sales. He provides insights into market opportunities, the importance of making data actionable, and offers advice for founders seeking funding. I always love asking my guests the 3 things they look for when hiring for sales roles, Vinay shares three traits he likes to seek out: 1. Hunger to LEARN, someone always focusing on learning, growing, improving themselves personally, and professionally. 2. Taking Initiative- startups are all the hats, building the plane while you're flying it. So if you see a process that needs fixing, fix it. 3. Strong Communicators- communications that is clear, direct, and easy to understand. I would add radical transparency to this list, but I did only give him 3 traits to distill. Check in to learn if you're a vitamin, or a pain killer, emerging markets, and of course all about Bonfire's impact, and goals, and more! Check out our key takeaways: 🎯 Salespeople should focus on understanding customer pain points to be effective. 📊 Bonfire Analytics aims to provide actionable insights to healthcare companies to improve sales efficiency. 🌍 Vinay's global upbringing fostered adaptability and resilience, essential traits for a startup founder. 🏥 Healthcare companies often make the mistake of relying too heavily on large health systems for sales. 🔑 Data must be actionable; Bonfire helps clients leverage data effectively for their sales strategies. Check it all out here: https://lnkd.in/dnvucCrF

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"Make Health Tech Great Again" ! Today a new Health Tech Ecosystem was launched backed by Tech, Govt and prominent healthcare stakeholders in this space. The focus -- better value in healthcare with innovative solutions, wearables and future focused solutions to reduce cost and drive better outcomes. This all tracks right, what is not clear though on who will control access to the integrated data -- are we creating more gatekeepers, and how will this all work in the reimbursement-strapped ecosystem that is currently not conducive to innovation. To truly make health tech great, that should be the first problem to tackle.

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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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Improving health outcomes will require new ways of thinking about how data, technology, and care delivery come together. In Intelligent Health, my friend Nasim Afsar, MD MBA MHM explores how these forces can align to create a more proactive and person-centered system. I’d recommend this read to anyone shaping the future of healthcare: https://lnkd.in/gSTRrZGR

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Super excited to share my recent podcast with Becker’s Hospital Review, where I reflect on the parallel revolutions I’ve witnessed: the rise of digital health (2010–2022, during my time as Chief Innovation Officer on the East Coast) and the current wave of Generative AI (coinciding with my CIO role on the West Coast). Both moments are milestones, but what matters is how we translate promise into real-world impact. Here’s a problem I can’t unsee: Clinical trials show that 9 out of 10 patients can achieve blood pressure control but in the real world, fewer than 4 in 10 do. Why? Because our healthcare system is still built on one-to-one care—one patient, one clinician, one time, one place. Key takeaways from our conversation: 1. One-to-One Care Is the Bottleneck: Patients spend less than 0.007% of their time with a clinician and 99.993% without anyone guiding them. Telehealth unlocked space, but not time. We must think bigger. 2. Empowering One-to-Many Care:  During COVID, our STOP COVID NYC program reached 1 million+ patients via the EHR and enrolled 55,000 in remote monitoring—what would have taken 100 staff over 1.5 years. This is the power of digital tools scaling care. 3. Generative AI as the Next Leap:  GenAI offers human-like conversations (video, voice, multilingual) going far beyond apps or rule-based bots. It brings us closer than ever to bridging the gap between clinical intent and real-world care. 4. Tech Enables Innovation, But Humans Drive Transformation: Barriers like regulation, talent gaps, affordability, and safety remain. But transformation happens only when humans integrate technology into workflows that matter. 5. Will Gen AI widen the gaps between haves and have nots or will it bring empowerment to all? The answer lies in how we implement it. Are we ready to bring superpowers to all of our healthcare workforce and bring on care abundance or do we leave it to technology to replace us humans? I believe in human-led transformation and that’s why we created GVX to enable one-to- many care. At GlobalVentures X (in partnership with 100+ engineers from Thinkhat), we’re accelerating the convergence in healthcare where startups, health systems, health plans, and GenAI innovations come together to drive human-led transformation at scale.  Can’t wait to share exciting updates next week! Listen to the full episode: https://lnkd.in/gZ4epyUg VALID AI Becker's Healthcare NODE.Health Mount Sinai Health System  Cleveland Clinic   #GenAI #DigitalHealth  #OneToManyCare #HealthcareInnovation #Intrapreneurship #AIinHealthcare #BeckersHealthcare

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Equitable healthcare access for elderly populations in rural ethnic minority regions remains a global challenge. In service availability & geographic barriers often prevent high risk populations from receiving timely care. A newly published study in BHTY applies Graph Neural Networks (GNNs) to model the dynamic healthcare utilization pathways of elderly patients with chronic diseases offers actionable insights for precision allocation of health resources and optimization of service pathways. What this study examines - Construction of a heterogeneous health service utilization graph linking patients, medical institutions, and geographic units - Use of Heterogeneous Graph Attention Networks (HAN) and Graph Attention Network (GAT) classifiers to identify at risk patient groups - Generation of resource optimization recommendations, including mobile medical points and cross-regional collaborative nodes - Provides a framework for actionable healthcare delivery improvements in complex rural and minority contexts Why this work is citable ♦️ Applies advanced AI (GNNs) to a real world healthcare equity problem ♦️ Demonstrates a scalable methodology for identifying high risk patients and service bottlenecks ♦️ Bridges data science, health services research, and platform based healthcare optimization ♦️ Provides a reproducible framework to guide resource allocation and service planning for underserved populations The full study explores the methodology, modeling, and potential applications. Read the article at 👉 DOI: https://lnkd.in/gcKAZEAH **MEET THE AUTHORS** Jing Zhang, MD; Haitao Fan, MD Yunnan University Technology and Business, Kunming City, China The article is part of the theme issue exploring the transformation of healthcare and the broader life sciences sector.

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