Ellis Hiroki Butterfield

Hot take on a lot of early-stage digital health companies out there: You're not a tech company. Most tech-enabled care companies I've seen over the past two years are only tech-enabled in the sense that they use telehealth as their delivery mechanism for care. There are exceptions to this, of course - companies who build computer vision and applied AI tools to better the doctor-patient experience, companies who build tooling around risk scoring and stratification to enable more personalized medicine, companies who build truly novel intakes to better route patients to the appropriate care, etc. These companies have real technology chops and, if they sell it right to the market, can get credit for this from investors. But if you're truly a telehealth provider, you need to realize now that the goal post has shifted dramatically from 2021 and you're going to be valued at maturity at something like 3x EBITDA. That's profit. Not revenue. Throw a revenue multiple out the window. That's not the world we live in if you're a virtual doctor's office. Think of how that impacts venture math. If you're raising a seed round at $15M post-money (or $12M pre-money), it means you'll have to generate something like $150-200M in annual EBITDA to be a fund returner for your seed investors. Maybe even more with dilution, since telehealth businesses are not traditionally capital efficient and will likely need to raise material additional capital to reach that scale. You need to be ridiculously profitable (probably on $800M-$1B in annual revenue since you're likely going to be a 40% gross margin business). Here's the good news: you can set yourself up well (and probably be a contrarian founder relative to your peers), by talking about EBITDA growth and how you can grow into a fund-returning outcome based on realistic mature market comps. This will stand out for the investors you're pitching, even at the early stage. This is how you can beat the malaise of the tech-enabled care market. Focus on the right metrics and the right type of growth. You don't have to have all the answers (no founder does), but you need to make sure the ship is headed in the right direction. A focus on profitability for "tech-enabled care" (*ahem* telehealth) businesses is a good first step.

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We're trying a new thing: Company spotlights to help people better understand what various health IT vendors actually do 🔦 We’ll be cutting through the marketing speak to give short, to-the-point descriptions of a company’s product and/or service + some context on how they see their differentiators. Tag any companies in the comments you'd like to see us cover (and follow Elion if you want to stay in the loop!)

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Over last few years, I have often interacted with college students who do not take academic’s seriously thinking that academics is not “so important” for the success later in life, as a lot of successful founders are college dropouts. However, we often ignore the success rates in college dropouts. A handful of successful entrepreneurs who are college drop outs shouldn’t be a motivation to take the study and job at hand lineantly. In this article, the author assertively tells that how higher education shapes a person to be enterprising and take calculated risks. One more understated quality that a higher education gives is that of perseverance. A M.D./PhD or a similar education takes years together and requires the candidate to sail through self doubt, uncertainities and develops mental strength. A good read for everyone!

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Someone broke down the estimated costs of a $15 Sweetgreen salad. We need these cost graphics for digital health to help future founders. Especially for tech enabled cos, the greatest cost is labor. Much of the "value created" is in curation and matching, which means the gross margins are reliant on labor arbitrage. Pay someone $X, but get paid $X+Y% per visit. The challenge with healthcare is that you often have to pick one of two business models: 1. specialized, low volume, high cost, low gross margin % 2. generalized, high volume, low cost, high gross margin % I'd argue founders should focus on gross dollars over the lifetime of the customer (like Jeff Bezos said) instead of gross margin %'s, but we'll leave that for another time. The challenge is that many tech enabled digital health cos have high cost of goods sold (labor) and moderately high product, design, and engineering budgets. We must build differentiated solutions for patients, clinicians, and clients to be out incumbents, however, we're realizing that companies are ultimately valued on the discounted value of future cash flows. And the high SG&A costs at most organizations might be inbalanced to the unit economics of the business. I'm not sure the math pencils out for everyone unfortunately. But I'm just a guy on the internet, would love to hear the thoughts from those smarter than I (you!). Comment below. --- p.s. I have no idea the accuracy of the graphic and not an investor in Sweetgreen. Cheers. Credit: David Crowther

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“Over one million new articles are added to PubMed annually—about two per minute. No physician can keep up.” This highlights a challenge that PCPs face daily, managing countless chronic and acute conditions while adapting to ever-evolving clinical guidelines. We can’t expect our clinicians to act like machines. At RhythmX AI (https://rhythmx.ai), we address this by revolutionizing primary care with our generative AI-native precision care platform, developed collaboratively by our physicians, specialists, and AI teams. Our platform integrates advanced AI and longitudinal data to deliver patient-specific, evidence-based recommendations directly within clinical workflows. These hyper-personalized insights help physicians make informed decisions at the point of care, bridging the gap between research and practice. Trust is at our core. Our physicians rigorously validate every recommendation to ensure clinical-grade reliability, empowering clinicians to confidently rely on the insights we provide. #PioneerPrimaryCare #Hyper-PersonalizedCare #PCPBurnOut #HealthAI #ResponsibleAI

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Hot off the pre-print server – an important publication authored by the Atropos Health team exploring the performance of LLMs in answering real-world clinical questions. LLMs excel at summarizing and contextualizing existing literature, but cannot generate de novo medical evidence today. The results of the study highlight performance gains attributable to injecting novel, relevant, and up-to-date medical evidence into LLM-powered clinical decision support systems. Brigham Hyde Nigam Shah Saurabh Gombar Read the study here: https://lnkd.in/ecuU25Pq

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Every startup is trying to solve a problem. But let’s be honest: some problems are more important than others. One of the most critical problems facing the U.S. healthcare system is our obscenely high maternal mortality rate. We have the highest rate of any high-income country - and the group most impacted is women of color.  We’re fortunate at Lantern to be working with incredible founders trying to address this heartbreaking problem. With Mother’s Day coming up, I wanted to take a minute to shout out Anu Sharma, her co-founders Talia Borgo CNM, WHNP, RN and Sarah Reynolds, and the incredible work they are doing at Millie to make carrying, delivering, and caring for babies safer and better.  The problem was clear: Overworked and understaffed OB departments and practices that just aren’t equipped to provide the individualized, comprehensive care that many pregnant people are seeking. Pregnant patients often experience:  • A 10-12 week wait for an initial appointment • Very short appointment times • An absence of holistic health information • Gaps in care between visits, which add anxiety and risk • A few-sizes-fits-all approach to labor and delivery • And craziest of all: a near-complete lack of postpartum care Millie’s solution? A modern maternal health system that provides holistic pregnancy care - pre, during and post delivery. Made possible with the expertise of Certified Nurse Midwives – medical professionals known for their deep knowledge of pregnancy and the labor process, and their minimal-intervention approach. Midwives can spend more time with patients during and after the pregnancy, and are the ideal provider for the 80% of pregnancies that are considered “low risk”, allowing OBGYNs to focus on high risk cases. When I first met Anu and she told me about Millie, my first thought was, "How does this not already exist?” I was inspired by the vision and the need for this service is obvious - what more could a marketer ask for? Better yet, our SEO strategy seemed to be working as Anu found Lantern by Googling “embedded growth teams in the early-stage health space.” The fit was obvious. She needed help with web analytics, paid search, Meta creative, and conversion rate optimization. And she didn’t have the budget to hire the 2-4 specialists needed. Moreover, she didn’t need 2-4 full-time hires. It was the perfect use case for our new kind of agency. Lantern got involved shortly after launch and was able to help Millie build on their early momentum. They were getting great local press but needed a long term plan for growth. Our team (led by Kristin Proctor, one of our Growth Directors) built a systematic growth machine, using best practice tactics throughout the funnel to significantly scale new customer acquisition, while keeping spend flat. Thank you for trusting us to get the word out about Millie, Anu. Truly honored to help build this revolutionary business. Happy early Mother’s Day, to you and the Millie team! 

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I'm currently going through some very old SnagIT screenshots from 2015. I'm trying to recall which hype cycle this is from. Which hype cycle was relevant in 2015? #SelfServeAnalytics? Had we reached #BigData yet? The progress in "#reusability" has been remarkable for the cartoon industry. 😂 #SameHypeDifferentDay

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🚀 Accelerating the Future of Healthcare with AI 🚀 I recently had the pleasure of tuning into an insightful episode of The Chris Voss Show featuring Lana Feng, Ph.D., CEO and co-founder of Huma.AI. 🗝 Here are some key takeaways that highlight the transformative power of AI in drug development and precision medicine: 🧠 Introduction to Huma.AI: Dr. Feng’s company, Huma.AI, leverages generative AI to automate data analysis, speeding up the development of life-saving drugs. Their mission? To reduce the time and cost involved in bringing these drugs to market. 🌟 💡 Challenges in Drug Development: Traditional drug development is a 10-year, $2.6 billion process plagued by data bottlenecks and regulatory complexities. AI can revolutionize this by handling vast amounts of unstructured data from various sources efficiently. 📊 🤖 The Role of AI: Utilizing advanced AI models like GPT-4, Huma.AI ensures data privacy, accuracy, and transparency. This leads to more reliable insights, faster clinical trial enrollments, and ultimately, better patient outcomes. 🏥 🌍 Real-world Applications: From identifying the right treatments in precision medicine to accelerating clinical trials, AI’s impact on healthcare is profound. It’s especially crucial in areas like cancer treatment and chronic disease management. 🎯 📈 Industry Recognition: Huma.AI has garnered significant recognition, being named a leader in generative AI for life sciences by Gartner. 🏆 🔮 Future Directions: The integration of AI in healthcare requires responsible usage, industry-wide collaboration, and continuous efforts to mitigate risks like data privacy issues and AI hallucination. 🤝 🌟 AI for Good: Dr. Feng emphasizes the importance of using AI responsibly to lower drug prices and improve healthcare outcomes. This approach ensures AI serves as a powerful ally in our quest for better health. ❤️ I’m excited about the potential of AI in transforming healthcare and making life-saving treatments more accessible and affordable. Let's embrace this technology for a healthier future! 🚀 #HealthcareInnovation #AI #PrecisionMedicine #DrugDevelopment #TechForGood #FutureOfHealthcare #ChrisVossShow #HumaAI #Leadership

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🎬 Matt Damon and 🏈 Colin Kaepernick have invested in it, and so has 💰Andreessen Horowitz... Function Health's executive team has "engineered a first-of-its-kind approach that focuses on prevention and empowerment"—very much in line with what we aimed to achieve with Carebook when we started it over six years ago. Could they be the ones to fulfill their lead investors' prophecy (link at the bottom) and Dr. Eric Topol, MD's premonitions in his books "The Patient Will See You Now" and "Deep Medicine"? They have just secured a $50 million grant. Let's hope this is not another Theranos and that we are truly witnessing the rise of the next generation of direct-to-consumer health companies. These companies will be key players in the "transition from reactive to proactive" health care that the system—and we—desperately need. What do you think? Links: 📝 Investment round press release: https://lnkd.in/eUG87qkf 🔗 Andreessen Horowitz's prophecy: https://lnkd.in/eZATCf4f

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A tale of two product development cycle timelines Software: a few months to a few years. ⏰ Biologic drugs: 10-15 years. ⏰⏰⏰⏰⏰ What happens when you put teams from both schools — whose fundamental understanding of development cycles looks so different — together to build something? Gears gonna grind. The mismatch between information science and biopharma is a big part of the conversation in this week's #BusinessOfBiotech with Foresite Capital's Vik Bajaj. Listen wherever you get podcasts or watch online at: https://lnkd.in/e8VGkU49 Here's a preview 🎬

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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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🤔 A Fascinating Question: How could LLMs transform medical coding? Here's a data-driven hypothesis worth exploring... The Challenge: Medical coders today spend hours translating clinical notes into ICD-10 codes, juggling multiple reference guides and databases. It's like trying to translate a book while simultaneously checking three different dictionaries. Here's what an LLM-powered solution could look like: Think of it as a smart highlighter that could: - Extract key medical terminology from clinical notes - Map common diagnoses to preliminary codes - Create documentation checklists Based on current LLM capabilities and publicly available healthcare data, we could potentially see: - 25-30% faster processing for routine cases - Improved documentation completeness - Reduced lookup time for common codes The Technical Framework: - Fine-tuned LLM on medical terminology - Integration with existing systems - Human oversight for complex cases Why This Matters: For a hospital processing 200 records daily, even a 20% efficiency improvement means 40 more patients getting faster care. It's not about replacing human expertise - it's about augmenting it. 💡 Key Insight: The real value isn't in automation, but in reducing cognitive load. Like having a knowledgeable assistant who handles the initial research while experts focus on critical decisions. Question for healthcare professionals: Which parts of the coding workflow would benefit most from this kind of AI assistance? #HealthTech #AI #Healthcare #Innovation --- What specific challenges would you want this system to address first? Share below 👇

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📈 Demand for fertility services is rising -> 💼 PE recognizes this and wants in -> 🏜 but opportunities are scarce (https://lnkd.in/g6zXEVZh). Highly recommend anyone who wants a deeper understanding of what's going with fertility and fertility tech read Aya Spencer's *2024 State of fertility tech report* (https://lnkd.in/gVjK_UpX) - it's a great summary

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Presenting at the Senate as part of the Coalition for Health AI (CHAI) "Day on the Hill" wasn't on my 2024 bingo card, but I'm feeling energized by the bipartisan discussions on healthcare AI. The numbers tell a compelling story: while nearly 2,000 healthcare AI startups have received funding over the last two decades, only 1 in 20 provider-facing companies reach late-stage maturity. Beyond natural market dynamics, two critical barriers are holding back AI's full potential in healthcare: unsustainable payment models and inadequate evaluation infrastructure – only 5% of research studies on LLMs in medicine utilize real patient care data, and studies advancing our understanding of performance beyond medical licensing exam benchmarks remain anemic at best. At CHAI, we're advocating for essential foundations: • Rigorous technical model performance evaluations • Comprehensive bias assessments across diverse patient populations • Thorough pre-deployment simulations and prospective studies • Robust ongoing local monitoring The path forward demands strong reporting infrastructure, advanced healthcare AI benchmarks, and meaningful public-private partnerships to drive real-world AI deployment in healthcare. Stay tuned for CHAI's upcoming initiatives in 2025 as we expand our engagements with the startup and investment ecosystem. https://lnkd.in/enw-GQcA

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𝐓𝐡𝐞 𝐍𝐞𝐱𝐭 𝐁𝐢𝐥𝐥𝐢𝐨𝐧-𝐃𝐨𝐥𝐥𝐚𝐫 𝐀𝐈 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐖𝐢𝐥𝐥 𝐁𝐞 𝐢𝐧 𝐀𝐩𝐩𝐬 🚀 Like cloud and mobile revolutions gave rise to giants like Meta and Uber, AI's next $1B+ companies will emerge at the application layer. With foundational players like OpenAI and AWS stabilising, the focus shifts to apps with advanced agentic capabilities—reasoning, problem-solving, and delivering outcomes. 💡 What industries stand to benefit most from agentic AI apps? 💡 Are we ready for the cognitive leap in applications? 💡 What role will trust and ethics play in their adoption? #AI #Innovation #AgenticApps #FutureOfTech

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Excited to announce Frist Cressey Ventures' investment in Qualified Health and privileged to partner w/ SignalFire, Healthier Capital, Town Hall Ventures and others!   Healthcare costs are increasing at a faster rate than ever before, with the US spending nearly twice as other wealthy countries and still ranking bottom in outcomes. It's a story you've all heard - - US healthcare is known for astronomical inefficiencies, waste, workforce supply constraints, fragmented access, appalling patient experiences, and driving patients and businesses into debt.   Yes these problems present opportunities. But opportunities are limited to the system's appetite for change, desire and incentive to try something new and the innovation available. At FCV we believe we've hit the trifecta with Generative AI. Generative AI has given us truly transformational tools in the toolkit and the healthcare ecosystem is demanding to absorb its benefits. This perfect collision of supply and demand means healthcare is poised for big change.   Generative AI is everywhere, it's buzzy, it dangles hope and opportunity. But many things need to be true for the Gen AI transformation in healthcare to take hold, such as but not limited to:   💡 Patient lives and data need to remain safe: We believe in a highly regulated and human life-touching sector such as healthcare we must ensure Gen AI can drive to unrivalled savings and improvements in the quality of care WHILE not putting patient lives or data at risk.   💡 Systems need to own their utilization of Gen AI: We believe systems will use some hybrid of external partners and homegrown solutions but importantly will want full control of data provisioning and utilization as well as the ability to solve an unlimited number of nuanced issues and not cookie cutter algorithms.   💡 Costs need to be looked at on an enterprise level: We believe the speed of innovation in Gen AI means costs will continue decreasing dramatically but at an enterprise level this will still not be a small detail. Systems will want the ability to understand costs and delegate as needed for the outcomes desired at the organizational level.   Enter Qualified.   We knew when we met Justin Norden, MD, MBA, MPhil and team we were standing in front of changemakers. These individuals have lived and breathed the true application and implementation of Generative AI far before we were asking ChatGPT to write our emails. In fact, if you’ve ever driven in a Waymo you’ve benefited from past products this team has built.   Qualified Health is on a mission to enforce governance in Gen AI, allow systems to rapidly build for their needs, monitor and make decisions for all GenAI (homegrown and external) and accelerate the value the sector can glean from these new technologies.   Huge shout out to William T., Tommaso Auerbach and Jamie Kuntz for their hard work!

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I am torn by this as well. When I see a new platform shift, I see the opportunity for a shift that benefits the end user. The ultimate end user in healthcare is the patient. In the current model, the structure is to chase revenue by driving it up or maximizing profit. The AI platform shift, targeting low-hanging fruit like administrative efficiencies, follows this path. It's reminiscent of the famous quote: "We wanted flying cars, but we got 140 characters." The same thing is happening all over again, without truly challenging the status quo. Maybe AI can help people get less sick, prevent disease, and navigate spending less money in the first place. But in the current model, it's difficult to get penetration. Ultimately, everyone needs short-term metrics and traction to raise another round of funds. I am not criticizing those who play this game. I respect them for playing it well. However, they shouldn't position themselves as lowering costs for patients by decreasing administrative costs. The trickle-down effect simply doesn’t work.

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