Peter Horan

Platforms are in, point solutions are out as the healthcare AI category leaders come into focus this year. In conversation with Shelby Livingston at Endpoints News, I shared: 1. Why AI-first companies have the greatest platform potential and heuristics for identifying these opportunities at the earliest stages, 2. How companies are differentiating through co-development and distribution partnerships with leading healthcare institutions, and 3. Strategies for navigating anemic budgets and constrained market sizes through business model innovation such as AI-enabled services and pay for performance models Read more here: https://lnkd.in/dJWqv_zC Bessemer Venture Partners Abridge #healthcare #lifesciences #AI #generativeAI

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There appears to be a "Superstar Effect" in healthcare and biomedical AI research right now. A small percentage of publications are truly novel methods contributions that introduce new capabilities or behaviors; whereas a majority of contemporary research publications are focused on implementation science to assess the real-world utility and performance of new methods. This dynamic seems different from prior eras, when the translational infrastructure for implementing novel AI methods was largely unavailable. While methods research often captures more attention and accolades, both types of research are critical – novel methods without implementation science lacks translatability; implementation science without novel methods lacks novelty. If our goal is to invent and deploy transformative AI methods in real-world healthcare and life sciences contexts, we ought to continue encouraging and rewarding stellar implementation science work alongside breakthrough methods development.

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Latest #PitchBook data for #HealthIT investment shows a preference for later stage investment across healthIT that pre-dates the VC downturn and current interest rate environment. Even though healthIT has been more resilient to current headwinds compared to health care services and PPM plays, perhaps it speaks to a need to scale solutions and points of saturation for new entrants. "...In the lower middle market, we are beginning to see more examples of a phenomenon we have anticipated for a while: PE firms and PE-backed companies acquiring VC-backed startups. Lower-middle-market PE firms perennially complain that VC- backed companies expect too-high multiples, and these firms would generally prefer to invest on a multiple of EBITDA rather than a multiple of revenue..." Speaks to a convergence that would allow PE-VC M&A on both ends of the startup spectrum. #HealthcareVC #healthcarePE

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In case you missed it, last week the Coalition for Health AI (CHAI) released a draft consensus framework for responsible health AI. Developed with input from over 100 contributors representing a diverse network of healthcare stakeholders, this guide proposes actionable evaluation criteria throughout the AI lifecycle—from identifying use cases to deployment and monitoring. Key examples outlined in the guide include: • Predictive EHR Risk Use Case (Pediatric Asthma Exacerbation) • Imaging Diagnostic Use Case (Mammography) • Generative AI Use Case (EHR Query and Extraction) • Claims-Based Outpatient Use Case (Care Management) • Clinical Ops & Administration Use Case (Prior Authorization with Medical Coding) • Genomics Use Case (Precision Oncology with Genomic Markers) The draft framework is open for public review and comment for the next sixty days. Please use this form to submit feedback: https://lnkd.in/eYughFYC Kudos to the CHAI team led by CEO & President, Dr. Brian Anderson, MD, on this milestone. Eric Horvitz Jennifer Goldsack John Halamka, M.D., M.S. Michael Pencina Micky Tripathi Nigam Shah Suchi Saria Troy Tazbaz #healthcare #ai #artificialintelligence #generativeai https://lnkd.in/e7VRv6fD

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M13 is thrilled to lead the Series A in RadiantGraph which is focused on personalization in healthcare. As we continue to invest in early stage companies it is abundantly clear that the biggest indicator of success is the founder and his or her ability to execute on their vision of the future. In this case, I don't think I have seen much better founder-market fit than we have with founder and CEO Anmol Madan. We believe in his vision: in order to have the best patient outcomes in healthcare we need increased personalization and AI is the breakthrough to get us there. Anmol started one of the pioneering digital health companies Ginger and then was Chief Data Scientist at Livongo and Teledoc. He has done it all: early stage, late stage, public company. And he deeply understands the nuances of the healthcare market from all angles which is critical for success. While there are many players building healthcare-specific AI capabilities, RadiantGraph is focused on outcomes: The platform is already processing personalization models for more than 3.5 million people, despite launching just last year. Excited to partner with my friend Adam D'Augelli and the great True Ventures again and Morgan Blumberg who has been deep in the healthcare market with me for many years. More on our thesis in the blog below. https://lnkd.in/evDDmC3W

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The (Healthcare) Ground Beneath Our Feet… This year it is likely that over $10 billion will be invested in the digital health sector – a robust amount, no doubt, but inconsequential when compared to the amount of capital tied up in healthcare real estate assets, which is estimated to be $1.2 trillion by Jones Lang Lasalle. Of that amount, approximately $790 billion is in the hospital sector while the remaining $490 billion is in medical office assets. It is estimated that there are 48.6k facilities with 3.4 billion square feet of healthcare real estate, 42% of which are owned by REITs and another 33% held by other private investment vehicles. Much of the digital health investment is meant to make the physical healthcare infrastructure more productive: greater operating efficiencies, greater patient throughput, more relevant personalized care models with better outcomes. As the healthcare system is being pushed to be more distributed to lower cost sites of care, accelerated now by the rapid proliferation of automation and AI capabilities, the potential impact on healthcare infrastructure assets will be profound. Thoughts on what that might look like... https://lnkd.in/eTfAdUbS #digitalhealth Flare Capital Partners

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I saw this pattern of rapid growth and then consolidation happening in banking and FinTech in the mid 2000s. We jumped into Digital Healthcare in 2016 with the thesis that there were similar drivers. One big surprise, COVID, acted as rocket fuel to the industry but the same fundamentals apply. Consolidation of the biggest players , innovation by faster moving startups raising capital and then being acquired and patients expecting current ( i.e... wait, we are still using faxes? ) but rather now , de facto to them, omni channel consumer experiences. What can we continue to learn from past "explosions" of growth?

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In our latest publication in Health, Management, Policy, and Innovation – "Why AI Is Good for Our Health but May Hurt Our Wallets," we examine how current regulatory frameworks, reimbursement structures, and business models for AI in healthcare are decoupled, creating an environment in which AI may significantly increase costs without necessarily improving outcomes. We recommend three interconnected reforms to unlock the full potential of healthcare AI: (1) Rigorous pre- and post-deployment evaluation to verify proposed clinical value, (2) Development of assessment standards through shared guidelines, and (3) Strategic alignment of AI deployment modalities with sustainable business models – "modality-business model-market" fit 👉 https://lnkd.in/d8NiczyM Sneha Shah Jain, MD, MBA, Clinical Professor and Kevin Schulman Professor of Medicine at Stanford University, Nigam Shah, Chief Data Scientist, Michael Pfeffer, Chief Information and Digital Officer, and Linda Hoff Chief Financial Officer at Stanford Health Care

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🎙️ Thrilled to share that V. Tyrone Lam, COO of GATC Health, was recently featured on the Innovation Wave Podcast! In this insightful 20’ episode with Bob McGriff and me, Ty delves into how AI-driven predictive analytics can transform our approach to disease treatment, making it more proactive and less risky. He shared compelling insights on the future of healthcare and how predictive tools can lead to earlier interventions and better patient outcomes. A must-listen for anyone interested in the cutting-edge of medical technology and AI! 👉 Check out the episode to learn more about Tyrone's vision and GATC Health's pioneering work in this exciting field. Let's discuss how these innovations are reshaping the landscape of healthcare! #HealthTech #AI #PredictiveAnalytics #Innovation

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Some VC investors believe that brick and mortar - referring to a physical presence of some kind - should be avoided at all costs. Yet, the track record of clinic and hybrid care businesses in health care indicates otherwise. ==> One Medical (sold for $3.9 billion to Amazon), Oak Street (bought by CVS for $10.6 billion), Lifestance (IPO at $7.5 billion market cap), and PE-backed Premise Health (acquired by OMERS Private Equity for $1.1 billion) If a clinic is indicated as the optimal way to deliver care for that patient population, there are creative ways to build and operate them. Full article below with advice and strategies on how to build and operate hybrid clinics from my teammate Anarghya Vardhana from Maveron, Amir Dan Rubin from OneMedical Group, Steven Eidelman from Modern Animal and more!

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💡Benchmarks in the investment industry serve as a standard for measuring the performance of securities, mutual funds, or investment managers. They provide a reference point for analyzing allocation, risk, and return of a portfolio, enabling investors to make informed decisions. Thanks Peter Walker for keeping us all informed!! Can’t wait for this!! Follow and get on the waitlist for this one! #benchmarks #fundraising #Capitalraise #founders #womenshealth #femhealth #medtech #wellness

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I’m thrilled to be announcing that Notion Capital is leading the $15m Series A investment in Cogna today. In the industry, we like to think that software has been eating the world. But when you look at the data a better description would be more of a nibble. Depending on what source you look at the software industry represents between 5-8% of global GDP. Contrast that with the services industry that represents between 60-70% of GDP and worth around $25 trillion on a global basis. Most services have been out of reach for the software industry. They have either been too complex or too specialized for off the shelf software to access in any economically viable way. But that’s beginnning to change with GenAI leading to the emergence of ‘service as a software.’ Cogna is at the forefront of this opportunity - building precision software at scale and delivering huge productivity gains for traditional industries. We know Ben Peters & Lars Mennen well having backed their previous company Five AI that was acquired by Bosch in 2022. And we’re very excited to be backing them again together with Hoxton Ventures & Chalfen Ventures Read my full blog post on why we invested here. Radu Bozga Ben Peters Lars Mennen Bryan G. Mike Chalfen Hussein Kanji Kirsten Connell https://lnkd.in/eh8mhcJb

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I’m a lucky man - I get to talk about stuff I care about with people that feel the same way, but know how to approach it in fresh ways. This chat with Josh Au Yeung goes into another area I think needs much more attention - leadership. NHS providers recently published data showing only around a third of NHS CEOs have a clinical background: https://lnkd.in/givrbU_p . When evidence suggests that expert leadership is strongly associated with better outcomes, happier staff, and greater productivity, we need to work harder to identify, train, and support current and future clinical leaders. The burning question is this: when it comes to #HealthTech , who is the expert leader? A technologist? A clinician? A hybrid? Would love to hear your thoughts on this (and the podcast, naturally)

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Exciting news from Monica Chopra, Jeffrey De Flavio, MD, Samantha Adelberg, and the rest of the Auxa Health team as they officially announce their $5.2M Seed round. The team's deep industry expertise and drive for change have led them to solve critical infrastructural friction to providing quality healthcare and adoption of value-based care. Auxa's AI benefit navigation platform is simplifying the complexities of healthcare by streamlining all of the fragmented and siloed data and information to make it actionable in real-time for healthcare organizations. For the 70% of Americans who aren't getting access to the health and social care benefits they deserve, Auxa's solution will be pivotal in enabling equitable care. We're thrilled to partner with co-investors Zeal Capital Partners, AlleyCorp, Laconia, and Chaac Ventures on this journey and look to share many more milestones ahead. Cc K50 Ventures, Ryan Bloomer, Daniel Vásquez, Nick Talwar, Stefanie Ng https://lnkd.in/dPDY7-Db

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Medical practice staff handle a large volume of calls and texts to patients for things like appointment scheduling, referral follow-ups and prescription refills. It's a time-consuming process and results in a lot of administrative overhead. I chatted w/ Alex Cohen about how his new startup Hello Patient built AI agents to automate this patient-facing communication work

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The most talked about AI x Medical startup Abridge is working to rescue doctors from the never-ending admin grind (which causes burnout and less patient face-time). Abridge's AI listens to patient visits and generates precise medical notes, slashing the clerical workload. Now, doctors can focus on what truly matters: patient care. Major health systems like Yale and Emory are already on board and raving, calling it "life-changing" and "magical." 🔷 A big reason --> Payback of the scribe tool is easy to measure. It supports 14 languages including Haitian Creole, Brazilian Portuguese, and Punjabi. An ongoing criticism of generative AI is that it still has few substantive business applications. This seems to quash that. Question: is a dedicated medical LLM needed to be successful in the space? Or will the huge foundational models (GPT-4o, Google, and Meta) ingest a plethora of medical notes and kill the competition with performance? We're dealing with a fast and furious pace, and today's edge may not be relevant tomorrow. Competitors include Microsoft-owned Nuance Healthcare , Ambience Healthcare, Nabla and Suki. I'm excited to continue to see this field revolutionized. 🌟 #AI #MedTech #Abridge #HealthTech

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Great time on the Embracing Erosion podcast w/Devon O'Rourke! We talked about: 🚀 How to scale a company from concept to 9-figure exit 🔄 How to break away from the traditional consulting model and apply product approaches ⏩ Why it’s important to iterate quickly and often with messaging 💸📈What signals are important to pay attention to when investing in startups and much more!

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One conversation we should be having more, especially in healthcare: is this an AI problem or a policy problem? A big challenge in American healthcare stems from the reality that our healthcare strategy changes with every administration. Throwing AI at problems that are well-addressed by policy innovation (e.g., AI for payer-provider RCM war) feels like a gross misallocation of resources. Solution sets are rarely zero sum – in truth, most problems will require policy, tech, and human interventions, but it's worth asking ourselves whether AI is the best solve when we have a multitude of options.

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What's been buzzing the loudest for me so far at HLTH Europe? AI, AI, and more AI, of course. Tongues have been tripping over those two letters in every conversation I've had today or listened to including these nuggets: Michael Chen of Nuclera: "Generative AI is wonderful because it brings more hypothesis-making power for the drug discovery researcher. But ultimately, we all know that AI isn't enough. You need to have the power at the wet lab benchtop in order to validate experiments and bring hits and needs into the local trials, and the quality of these hits and leads that ultimately will help the success rates in phase one through three clinical trials, which often don't rear their ugly heads until it's too late." Geraldine O'Keeffe of EQT Group: "There's a huge amount of investment opportunity in terms of AI-, SaaS-based models, in big data and machine learning in diagnostics, precision medicine...delivering the care you need better, faster, cheaper." Karen DeSalvo of Google: "The availability of AI, the ubiquity of it, and just how quickly that is moving [has been significant in the evolution of AI in healthcare]. What I'm hoping now is the next generation of this technology allows us to democratise access to health for people all over the world, and that we can start to do that much more quickly and much more equitably." Chiara Bucciarelli-Ducci, MD, PhD and Marlies Schijven on clinicians' take on AI: "To scale up adoption of AI in healthcare, industry needs to demonstrate to clinicians and healthcare providers the cost effectiveness and cost efficiencies that the technology can bring at every level." "More often than not, we find that AI does work and helps to bring efficiencies, but it also carries risk. So it needs to be properly explained." Agree, disagree, or follow-up comments on these soundbites? #genAI #AIeverywhere #medicalAI #healthtech #digitalhealth #AIfordrugdiscovery #techbio #healthAI #clinicalAI

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