Nick Myers

I’m worried about the state of venture capital and direct-to-consumer (DTC) healthcare startups. Hims & Hers is the poster child for DTC healthcare at $1.2B proj 2024 revenue and a $3.6B valuation. By most accounts, they have been an outlier success for DTC since bottoming out in May 2022. So why is this bad news for DTC healthcare? Because the market leader (Hims) trades at a 3x forward revenue multiple. And the category leader typically gets a higher valuation multiple than smaller startups. We see this phenomenon in private equity. They “roll up” smaller companies within the same category at a lower multiples just to create one larger platform that trades at higher multiples. Now back to DTC healthcare startups. If Hims commands a 3x revenue multiple, it’s not unrealistic that smaller, unprofitable startups may be valued 1-2x revenue at exit. At 2x revenue, a startup must generate $500M to produce a $1B exit in today’s market (depending on growth and profitability). Series A/B venture capitalists must see a pathway to $1B outcomes. And if the growth-stage investors with billions under management are less interested in DTC healthcare, the future funding rounds necessary for fueling growth are not guaranteed. Juxtapose this against 2017-2022 where DTC could raise Series B-E funding. Let’s take a DTC startup doing $25M after 3-4 years of operations and has already raised a Series A. By most accounts, it would be a phenomenal accomplishment. But today, investors will question the chances of that same company scaling from $25M to $500M revenue in the next 3-4 years with unknown future funding sources from Series B and beyond. You're stuck in VC-funding purgatory. Some of these companies will shut down. Some may sell for 1-3x revenue. And some may try to transition to profitable, cash-flowing businesses. All of which are certainly not the venture-backed goal the founders, investors, and employees often had in mind when first taking capital. I say this all with friends working at or starting DTC healthcare companies, I feel bad for them. I also feel bad for the patients who enjoy those products or services. To caveat (b/c I know people will object), there will be other DTC brands that exit for $1B+ (i.e., Ro). However, they were forged and scaled during a different time period where seemingly endless venture capital was available for DTC healthcare. Now we're in a different time with no end in sight. Thoughts?

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Leading US VC General Catalyst just acquired the health system Summa Health for $485 million. Summa Health is a nonprofit #healthcare system with over 30 locations in Ohio (US). This analysis has been made possible thanks to the data platform HealthTech Alpha from Galen Growth | Insights You Can Trust. I wrote down a few thoughts: 1️⃣ 𝐆𝐞𝐧𝐞𝐫𝐚𝐥 𝐂𝐚𝐭𝐚𝐥𝐲𝐬𝐭 𝐢𝐬 𝐩𝐥𝐚𝐧𝐧𝐢𝐧𝐠 𝐭𝐨 𝐛𝐮𝐢𝐥𝐝 𝐚 𝐝𝐢𝐠𝐢𝐭𝐚𝐥-𝐟𝐢𝐫𝐬𝐭 𝐜𝐚𝐫𝐞 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐲 𝐦𝐨𝐝𝐞𝐥 𝐥𝐨𝐜𝐚𝐥𝐥𝐲 The health system Summa Health will be used as a testing field for the wide HealthTech portfolio of General Catalyst. General Catalyst, through its subsidiary HATCo, has committed an additional $550 million over the next five years for strategic investments and innovation. I had a similar case in my network of a PE fund that owned both a health system and a portfolio of HealthTech companies. On paper, this was the perfect match. In reality, it failed. 2️⃣ 𝐓𝐡𝐞 "𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐬𝐲𝐬𝐭𝐞𝐦" 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐚𝐭 𝐭𝐡𝐞 𝐜𝐨𝐫𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 General Catalyst includes Commure in its portfolio. Over the past several years, Commure has integrated data from various systems, including all major EHRs, to become the interoperable operating system used by many leading hospitals across the U.S. One immediate application will be implementing Scribe (based on Commure), an AI-powered tool for automatic clinical documentation co-developed with HCA Healthcare. 3️⃣ 𝐆𝐞𝐧𝐞𝐫𝐚𝐥 𝐂𝐚𝐭𝐚𝐥𝐲𝐬𝐭'𝐬 𝐩𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐡𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭: 𝟏 𝐛𝐢𝐠 𝐬𝐮𝐜𝐜𝐞𝐬𝐬 𝐚𝐧𝐝 𝟏 𝐛𝐢𝐠 𝐟𝐚𝐢𝐥𝐮𝐫𝐞 GC invested in Livongo, a telehealth solution for diabetes management, that was acquired by Teladoc for $18 billion (though Teladoc is now valued at only $1.7 billion!). Livongo was the perfect exit before the HealthTech downturn. On the other hand, GC has been a major investor in Olive AI, a BPO and care automation company for hospitals. Despite being valued at over $4 billion in 2021, Olive AI went bankrupt in 2023. Commure is now GC's new bet in care operations, informed by lessons from Olive AI's failure. 4️⃣ 𝐀 𝐕𝐂 𝐨𝐰𝐧𝐢𝐧𝐠 𝐚 𝐡𝐞𝐚𝐥𝐭𝐡 𝐬𝐲𝐬𝐭𝐞𝐦: 𝐰𝐢𝐧𝐧𝐢𝐧𝐠 𝐫𝐞𝐜𝐢𝐩𝐞 𝐨𝐫 𝐝𝐲𝐬𝐭𝐨𝐩𝐢𝐚𝐧 𝐬𝐜𝐞𝐧𝐚𝐫𝐢𝐨? The debate over private investors owning parts of the healthcare system (and potentially prioritizing profits over patient care) is intense (both in the US and Europe). Personally, I am quite excited about this move. And VCs are not PEs: While private equity firms aim to optimize the profitability of an established healthcare asset within five years for a high-multiple resale, venture capitalists focus on increasing the value of their HealthTech portfolio by demonstrating how these solutions bring real-world value. I am not naive though: I know that VCs do not act in the general interest. But we need them to drive innovation in healthcare. #healthcare #healthtech #vc #hospital #transformation

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"Design for discovery: Successful businesses don't assume they know what customers want. They are set up to learn what customers want and how to deliver it."   David Asch gave a wonderful presentation last week at the Digital Health Co/Lab at the University of Kansas's Innovators Day.   A few things from David's presentation that stick with me:   ✔️ We tend to give what we are already doing a pass and intensely scrutinize anything new. ✔️ The science of motivation has evolved from information to standard economics to behavioral economics. ✔️ When it comes to behavioral change, it's not about education. It's about using behavioral "reflexes' to bypass cognition. ✔️ We are irrational in highly predictable ways. One we realize how we are irrational, we are in a better position to help ourselves. ✔️ Frameworks to help include the nudge, framing in the right way, and making it social. ✔️ A nudge is a small effort with great influence. How are you using the power of the nudge? Thank you Christopher Wilson, Alex Chiu, Emily Law, Dana Reinert, Jennie Andra, and Frank T. Materia, PhD, MHS for a great day!   #business  

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How Do Physicians Experience Interoperability? Since working at Redox, I've come to understand why interoperability is important for digital health organizations but never focused on where it matters most: in the hands of the people providing patient care. I wanted to have a broader perspective of the space and came across a survey study (linked below) that asked the question, "What were primacy care physician perspectives on access to health information from outside organizations after years of policy support for interoperability?" What astonished me was that out of 2088 physicians, 70% said they were somewhat satisfied, and only "23% indicated that it was very easy to use." It's essential to understand the physicians' experience using interoperability systems to measure the impact of public policy on health information technology. Reading about the survey revealed to me that physician satisfaction varied across multiple factors - EHR, type of information, and physician. To my surprise, physicians frequently encountered missing information and even too much information. Physicians are at the forefront of our healthcare world. When it comes to HIT systems, there is a need for targeted approaches to help them progress toward "universal, high-level interoperability." Amazing authors of the survey: Jordan Everson, Nathaniel Hendrix, Bob Phillips, Julia Adler-Milstein, Andrew Bazemore, Vaishali Patel https://lnkd.in/gxtgGWm3

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As the landscape of healthcare changed with the progress of AI, so did our strategy at Aidoc. Here, I walk through how we came to our realization that enterprise-wide deployment was the future of clinical AI and not point solutions as we've seen thus far, and why health systems are changing their approach to AI adoption: #healthcareai

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One of the LinkedIn greats! Spencer Dorn has been putting out great content here on AI in healthcare, we had a great chat on the Healthcare Trailblazers Podcast. ALSO: looks like we are 20 subscribers away from reaching 10K subs on YouTube, so hit that subscribe button! 🙌 We discuss: The realistic applications and limitations of AI in the healthcare industry. The adoption and impact of digital health tools on patient care and administrative efficiency. The importance of maintaining critical thinking skills in the face of advancing technologies. Exploring the gap between what patients expect and what is feasible in healthcare. The vision for hyper-personalized care and the challenges in achieving it. https://lnkd.in/eUiiyDX2

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The median patient adoption for our Digital Health tool is 75%. Our best health systems achieve 90% adoption. Here’s what those getting 90% patient adoption are doing differently👇 1. Go true multichannel: make it available beyond just their patient portal and digital front door. Some patients prefer a native mobile app, an SMS or email + web app experience. 2. Entire interprofessional care team (physicians, nurses, pharmacists, OT/PT, allied health, etc.) all involved in the customization and implementation process. That’s how you build a sense of team-wide ownership of the Digital Health tool. 3. Clinicians actively promote it to patients as standard of care. It’s not an afterthought that just the office staff barely mention. 4. The leadership team is bought in and cares. When everyone knows it’s a real organizational priority, magically the numbers go up. Who would’ve guessed? 5. If possible, actually monitor patient health data (e.g. symptoms) and act on it when patients fall off track (e.g. early signs of deterioration). When patients have log a symptom and a care team member calls them about it, it has a magical effect: patients stay engaged. 6. Automate patient enrollment via an EHR integration BUT still educating patients on the tool. You can’t just “set it and forget it”. Patients still have to know WHY they should use this tool they get an electronic notification about. 7. Reinforce use of the Digital Health tool at multiple points in the patient journey - at the clinic, in the hospital, at follow up, etc. 8. Support multiple languages based on the local demographics. No AI isn’t safe enough to real-time translate clinical information with no oversight. But, LLMs are now often good enough to do a “first draft” of the translation which lowers time and cost to review. 9. Review your patient adoption and engagement data regularly (at minimum quarterly, but ideally monthly). Share it with your executives and key champions. Dig into the data where it’s weak and ask WHY. Use the tips in this post to improve the dta. 10. Provide actual scripts and train staff on best practice talk tracks for how to introduce the Digital Health tool to patients and families. Don’t just leave it up to staff to make up what to say. Systematize the communication. 11. Design for health literacy: all clinical content at the Gr. 6 reading level, in plain language, using adult learning principles. 12. Meet digital accessibility guidelines, such as WCAG 2.0 level AA. E.g. make sure it’s colorblind and contrast-tested, screen reader friendly, etc. 13. Allow caregivers and family members to be enrolled in the Digital Health tool so they can monitor the patient’s progress and nudge them to stay on track. Motivation from family members is HUGE. P.S. SeamlessMD enables health systems to digitize patient care journeys with reminders, education and symptom monitoring. If you’re looking for help on how to make 90%+ adoption happen for you… give us a shout!

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What kind of ROI can you expect with PA Checkpoint, our foundational product in prior auth automation? Blue Cross Blue Shield of Minnesota shares the ROI they've seen in this clip: #PriorAuth #Automation #HealthAI

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I'm betting big on AI in healthcare  (and why you should too) It’s not all Shakespearean sonnets about your favorite sandwich or photorealistic images of your dog dressed as Lincoln, you know… AI is so much more than ChatGPT, DALL-E, or Midjourney. Sure, those applications are undeniably cool (and hilarious). But they pale in comparison to the real potential of AI. AI is already revolutionizing how we manage chronic conditions and deliver care to patients. It’s why I’m so bullish on AI in healthcare. 3 words… Personalization. Prediction. Patient empowerment. (yes, that counts as 3 words, not 4) Here, let me show you… 🤖 AI rapidly analyzes vast quantities of patient data collected from wearable devices.  🩻 And identifies patterns and insights most humans would miss. 🩺 So we can tailor interventions and recommendations specific to unique needs and circumstances. Which means highly personalized care (at scale). No one-size-fits-all approach. How about this… 🤖 AI continuously monitors patient data and compares it to historical patterns. 🩻 So our platform can flag early warning signs and alert the clinical team. 🩺 Who can intervene proactively to prevent health landslides before they happen. This kind of predictive capability has the potential to save countless lives and reduce the burden on our healthcare system. And finally… 🤖 AI provides patients with personalized insights, recommendations, and educational content. 🤔 So they can better understand their conditions. ❤️‍🩹And make informed decisions about their care. By automating routine tasks and communication, we can free up more time for meaningful patient-provider interactions and relationship-building. At Side Health, we're already seeing the impact of AI in action. Our platform helps patients with chronic conditions achieve significant improvements in key health metrics, while reducing hospitalizations and emergency department visits. And we're just getting started. Sure, AI in healthcare is not without its challenges and limitations. There are valid concerns around data privacy, algorithm bias, and the need for human oversight and judgment. But it’s obvious to me: the potential far outweighs the risks. By actively engaging with these challenges and addressing them head-on, AI can and will transform healthcare for the better.

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I've seen companies buy a "turnkey" RPM solution only to realize it can't sync data with their EHR system or runs on outdated tech the engineers hate. Then you're stuck doing expensive overhauls or ripping and replacing. But even there, I avoided turnkey offerings. Why? Because they're often bloated with features my team didn't need, and custom workflows were difficult to build. Instead, I chose to build our RPM devices and billing software from the ground up. It took way more time and money upfront, but it let us mold the tech to our audience’s exact clinical and operational needs with zero shoehorning. Was it a harder road? Yes. But now I'm not stuck paying heavy fees to customize a turnkey system. That's my philosophy - unless it's a dead simple commodity, forget turnkey. In healthcare, the upfront savings are rarely worth the debt. Build it custom or be prepared for a gut rehab down the line. As a founder, what’s your take on the turnkey model? ♻️Repost to gather more insights. #founder #turnkeymodel #tips #healthcare

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The US hospital information system market is a $60 billion industry...but most tech vendors I talk to have a fuzzy idea *at best* of the true potential of their content marketing. They often under, or OVERestimate what's possible for their sales and marketing department. This makes it incredibly difficult to set realistic goals for a content marketing program...it's also why I always suggest some level of market research for early-stage programs before we do any significant content work. https://buff.ly/49tLJ5q

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Question for my network: how do you evaluate your digital health and health tech initiatives? Do you use any frameworks or services, etc? I am not one of those "tech can solve everything" people, but I do think it is a primary enabler for the future of health, equity, and "doing more with less" since we can't seem to magically triple our workforce or funding for it. Digital Health initiatives have been a little willy nilly and certainly aren't a silver bullet. But—for that reason, more and more attention is now being given to both evaluating digital health/health tech initiatives (finally!), AND bringing the health equity lens into their development/implementation (heck yes!) For the latter, I was interested to read the development of this Digital Health Equity-Focused Implementation Research (DH-EquIR) model! This framework outlines how you might start to integrate considerations of health equity into the implementation of your digital health technologies. Key takeaways: 👏 Inclusive Design: Technologies must be accessible and culturally sensitive, designed with input from diverse communities. 👏 Equity-Focused Planning: Integrate health equity considerations at every stage to reduce disparities. 👏 Continuous Evaluation: Monitor and adapt interventions to meet the needs of underserved populations. 👏 Sustainability: Ensure financial sustainability and interoperability for long-term success. 👏 Collaboration: Engage stakeholders from all sectors to drive impactful health solutions. It is promising to see health equity being promoted through thoughtful and inclusive digital health solutions designed to meet people where their real challenge is at, and I recognize that tech, people, and workflows go ✋in ✋ Frameworks like this are helpful as directional guidance to start with. I am also seeing a lot of "Digital Determinants of Health" crop up, though still meaning different things by different groups. Source: Construction of the Digital Health Equity Focused Implementation Research Conceptual Model - Bridging the Divide Between Equity-focused Digital Health and Implementation Research (https://buff.ly/3RbWmDQ) ----------------------------- (AI was used to generate this strange and misshapen/spelled image, but I actually kind of liked it!!)

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AI is all the rage, not just in healthcare but pretty much every industry. Heck, even the guy who mows my lawn is asking me about AI... the problem is the vast majority of people still don't trust it because they don't understand it. Check out NRC Health's Market Insights for all the details. Dive into the stats and see how YOU can better connect with our communities: https://bit.ly/3Wg1PMR #HealthcareAI #ConsumerTrust #HumanUnderstanding

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I am giving back to Healthcare. If your hospital uses Epic and you are considering note taking apps like Nabla /Abridge where you would spend hundreds of $ per user per month: I will develop a custom application for you for under $100K connected with your OpenAi account (using LLM/Whisper) and integrated with Epic. Your monthly running cost per user per day would be pennies. If nothing else then show this offer to Nabla/Abridge rep and get the price under $50 per month. If you develop with me: - **NEW**: You can resell the app to other hospitals. The IP and codebase will be in your hospital's name. I will charge no money if you resell. - Customized app for <$100K one time. Integrated with Epic. - Only pay for your LLM and Whisper spend directly to OpenAI (pennies for an hour of Whisper). - Possibility to use RAG for help with coding. There may be an additional few grands for this. - Deployed on your AWS/Azure cloud.

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Want to win trust in healthcare? Here’s the secret: Build with clinicians, not just for them. When a healthtech startup is clinically led, it immediately stands out. Clinicians know the realities of patient care, the struggles providers face, and the right solutions to build. This isn’t just about tech. It’s about creating solutions that healthcare professionals can trust—because they’re built by people who’ve been in their shoes. Credibility = Trust How is your startup building trust? 👇 #HealthTech #Trust #HealthcareInnovation #ClinicalCredibility #StartupLeadership #Innovation

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Write this down: the biggest impact of AI will be in healthcare. The healthcare segment represents 17% of the US economy, but that number doesn’t count all tech companies focused on this segment. Despite the rhetoric, the issue in healthcare is not staffing shortage, it is technology shortage. Two key areas to focus on: - There is an excess of administrative work being done by professionals that should be focusing on clinical work. - Predictive analytics in healthcare is crucial for performance-based services. AI has the potential to disrupt both areas, and it is already happening. A noteworthy point: the healthcare sector is highly fragmented, with the largest hospital system only holding a 3.5% market share. Margins are thin, making consolidation inevitable. #AI #Healthcare #Technology #Analytics #FutureImpact

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Everyone in digital health is talking about Telehealth 2.0 right now, but what we really should be talking about is, direct to consumer (D2C) 2.0. Here's why: ⤵ - D2C 1.0 was all about 🍆 pills, hair growth, and birth control, built primarily by D2C startups like Hims or Ro. - D2C 2.0 is going to be all about GLP1's, built by physicians via fractional private practices leveraging social as their main source of distribution. Now, here's where I'm going to make a massive prediction (piggy backing off of Scott Galloway). GLP1's will be what revitalizes primary care, not any of the new CMS payment models, not value based care, not even any of the new tech. Instead it's an old drug with a new rebrand that will save the doctor patient relationship and shift the clinical workforce back to independent practice, and of course it will all powered by AI. TLDR: Every physician in the U.S. will operate a fractional private practice regardless of their FT employment. The default practice type will be D2C and the main objective will be centered on primary care. GLP1s + AI is what gets us there. What do you think of this prediction? ---- Hi, I'm Dr. Mario Amaro, Founder and CEO Ease, and I talk about all things starting, running, and growing a private practice with AI. Follow me, if you are planning to start one or are currently figuring out creative ways to grow one. #PrivatePractice #SelfEmployment #HealthcareOnLinkedin #HeyEase #IndependentTogether #Fintech #Infrastructure #AIinHealthcare #CareDelivery

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What people think Custom Healthcare GPTs are: • Basic medical chatbots • Simple symptom checkers • Generic health advisors • Standard AI assistants What I Actually Built: A Healthcare AI That Understands: • Why night shift computers need therapy • How to translate doctor handwriting to tech speak • When the EMR system needs a coffee break • Which printer issues are actually emergencies Built From Real Experience: • 5 years of night administration • Emergency care background • Digital health transformation • Hospital operations expertise Technical Arsenal Used: • Advanced GPT-4 implementation • Custom prompt engineering • Healthcare data integration • Clinical workflow understanding Real Healthcare Knowledge Added: • Emergency protocols (ACLS certified) • Hospital management (MBA Healthcare) • Digital Health solutions (MS in progress) • Telemedicine operations Current Applications: • Supporting clinical decisions • Streamlining documentation • Enhancing workflow efficiency • Bridging clinical-technical gap Time Left to Share This Innovation: 5 months Healthcare Systems Understood: Countless Night Shifts Translated: Infinite Coffee Breaks Respected: Always #HealthcareAI #CustomGPT #DigitalHealth P.S. Yes, it also knows why the hospital WiFi only works in the cafeteria

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As the AI-accelerated future unfolds, ownership and sovereignty of data is vital and is the focus of Native BioData Consortium. Here, they share a paper co-authored by their Executive Director Joseph Yracheta presenting a framework for reducing biases and reducing disparities in the integration of AI into health care.

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