Digital Health Investment Insights

The next group of digital health companies to go public will face a critical test: Do they have true tech products that can produce consistent profits. Many companies in the last cohort of digital health IPOs were merely offering traditional health care services zhuzhed with some tech VSports app下载. (See: Teladoc, Amwell). "If you're a true tech company in health care, you have more upside, you can scale faster, and you can bring costs down," one digital health executive told me recently. The new group is expected to include digital physical therapy firm Hinge Health, virtual diabetes care provider Omada Health, and women's digital health unicorn Maven Clinic. (Hinge, for example, uses computer vision to track and provide live feedback to people during physical therapy. ) "There's a big difference between . taking traditional health care and just adding in a convenient face-time option — that's not an additive form of treatment or care — and going beyond that," Omada president Wei-Li Shao told me recently. "Our bet is if you can create an engaging and delightful experience between those [traditional doctor's visits], that you can bend the curve," he added. The biggest near-term question is whether AI can help these businesses materially change the stakes for employers and health plans so they become nonnegotiables rather than nice-to-haves. .

Is Hinge Health About to Break the Digital Health IPO Curse. Hinge Health is preparing to IPO and it may revive the digital health listing scene. Timing remains uncertain amid market volatility, but there are several reasons for optimism: ✅ Hinge are built on a B2B2C model, selling to employers and payers rather than directly to consumers. Their value is clear to buyers focused on reducing absenteeism and managing MSK costs ✅ They offer a hybrid solution combining digital tools (apps, sensors, virtual coaching) with human-led care, helping scale while still delivering clinical outcomes ✅ They expanded into device-based care with the FDA-cleared Enso wearable and introduced TrueMotion, a sensor-free motion tracking technology ✅ Also broadened into new clinical areas such as pelvic health and menopause-related MSK care ✅ Hinge have strong engagement and outcome data, including reduced pain and surgery intent, which resonates with cost-conscious employers ✅ They benefited from macro trends like rising MSK costs, growing employer demand, and greater acceptance of remote care post-COVID ✅ Focused on institutional clients, with over 2,250 employers and health plans and 20 million lives covered VSports手机版. Now contracted with the five largest US health insurers. Recent partnerships include Cigna, Amazon Health, Teladoc, Midi Health, and Sun Life ✅ Financial performance is improving: $390M revenue in 2024 (up 33 percent), $124M in Q1 2025 (up 50 percent), and $17. 1M in Q1 profit after prior losses. But there are still some challenges ahead ⚠️ Last valuation was $6. 2B, but the IPO may price lower given broader skepticism about 2021–2022 valuations, and timing remains uncertain ⚠️ In 2024 Hinge still closed with an $11. 9M loss, though a major improvement from a $108M loss in 2023 ⚠️ Revenue concentration among a few large clients may pose a risk. ⚠️ Hinge faces rising competition from Sword Health, Vori, RecoveryOne and others in the MSK space Whatever happens it will be interesting #DigitalHealth #IPO.

Most healthtech founders don’t get a “no” from investors. But that’s a BAD thing. Because they don’t get the money either. They get silence. Endless follow-ups. Polite interest… followed by nothing. Not because the idea is bad. But because the pitch lacks proof. And that’s the only currency that counts in healthtech. You’re often raising: BEFORE clinical trials BEFORE commercial scale BEFORE regulatory approvals Here’s how you can bridge the credibility gap and raise funding early: 1. Prove the problem is real (and costly) Use real-world stats from peer-reviewed studies or government data. The more specific and costly the problem, the more investable your solution feels. Example: “20% of diagnostic errors stem from image misinterpretation. ” 2. Use early pilots to prove outcomes, not just usage A working prototype isn’t enough. Even pre-commercial, you can run: -Clinical pilots (10–50 patients) for health outcomes -Operational pilots to track time saved, error reduction, throughout gains 3. Validate from the front lines, not just the lab A quote from a nurse who uses your product 10x a day beats a generic testimonial from a CIO V体育ios版. Clinicians, procurement heads, and payers understand ROI and adoption - their support carries real weight. 4. Build a clear path to scale before the money arrives Investors want to see how you’ll grow from 1 to 100. Define your regulatory strategy, GTM plan, and business model early. Show the infrastructure and systems you’ll need to scale - don’t wait for the money to figure it out. 5. Know what “proof” looks like at your stage At pre-seed: expert interviews + MVP + LOI At seed: pilot results + early revenue + FDA submission At Series A: revenue growth + multi-site usage + clinical publications Reverse-engineer your path and build with intention. You don’t need millions to show traction - just the right proof. In healthtech, evidence is everything, where lives, compliance, and capital are on the line. Having been on both sides of the table, I can tell you: the pitch that wins isn’t the flashiest - it’s the one with undeniable proof. Not sure if your pitch deck makes the cut. For a limited time, I’m providing free pitch-deck reviews to Early stage healthtech entrepreneurs. To get access, DM me ‘REVIEW’. #investment #founders #startups #healthtech.

Digital health companies may be preparing to test the IPO market (per a report from Axios). Are they ready. Outsized valuations during the prior funding frenzy may have painted unicorns into a corner. Too large to be acquired (and unlikely to find favorable terms), companies are faced with going public as the only means to an exit. Going public means showing your hand, revealing both financials and business models (for better or worse). The companies most likely to go public last raised at valuations that far exceed the current market cap of many previous digital health IPOs. Retail investors may be willing to buy the promise of eventual sustained profitability for companies like Uber, Twitter/X, and Peloton -- will they do the same for digital health companies they've never heard of. What are the long-term ramifications for digital health if unicorn IPOs fall flat. I'm most curious to see how companies with patient-facing solutions fare (especially in MSK). What happens to your mission when the early days of growth, free flowing venture capital, and endless possibilities give way to the pressures of an IPO V体育平台登录. The paradox of healthcare is that, even though it's a $4. 3 trillion industry, making money isn't as easy as it seems (at least for non-incumbents). Great ideas and great products that solve real problems still must find a way to reach profitability. If the mission buckles, so too will the promise of "fixing a broken system. " We'll hear a lot about revenue, EBITDA, member growth, path to profitability, etc. Will we hear as much about clinical outcomes. Early-stage companies have the benefit of learning from the mistakes of the past -- too much focus on hype, growth, and first-mover advantage, not enough focus on evidence, impact, and business model. A re-setting of the landscape may be best if digital health is to fulfill its promise. But IPO failures could be a further drag on a sector that is in danger of losing "it" status to AI. Pretenders who go public will die a slow death (as we've already seen). Still, IMO, it would be a mistake for late-stage companies to go public under pressure. Panicking won't fix a flawed approach. Engage traditional healthcare. Find experts who have real world experience. Don't buy in to your own hype. Stay humble. If you believe in your mission, are earnest about driving change, and can execute on your vision, there is still a path ahead. #digitalhealth #healthtech #healthcaretechnology #medicine #healthcare #ipo .

People love to say, “Telehealth improves access. ” (It's me, I'm 'People). 🙋🏽♀️ That's true. But access to what. And for whom. And how. 🌎 If you’re building or scaling global telehealth programs, especially across borders or populations, you can’t just focus on the technology. You need to start with clinical reality. Nothing will ever work without it. Nor will you ever get clinical buy-in. Here’s how I've helped health systems and organizations build models that actually work. Keep it in mind if applies to you: 🔹 1. Patient access ≠ patient readiness. Don’t assume people have email, Wi-Fi, or even private space. You have to understand the real-life barriers. In one program, we realized our patients didn’t have email addresses so login-based systems completely failed. What an easy 🔹 2. Clinician training isn’t optional. I’ve trained doctors, nurses, and advanced practice providers on telehealth. The tools are easy the workflow isn’t. You have to teach digital empathy, virtual assessment, and how to actually listen through the screen. This is the only way to use telemedicine to its highest capacity. Otherwise it will remain simply clinical screening or follow-ups for low acuity complaints. Which is an utter waste. 🔹 3. Age isn’t the issue. Design is. I’ve had 85-year-olds test their telehealth logins “just in case. ” I’ve also had 28-year-olds drop off because the interface was clunky. The real barrier. Usability. It has to be frictionless for everyone. 🔹 4. Global ≠ generic. Every region has its own culture, workflow, language access issues, and regulatory context. If you’re applying a one-size-fits-all model across countries or populations, expect gaps in engagement, trust, and compliance. This one seems particularly obvious yet I see it all the time. The frameworks may be the same but not the solutions. 🧠 If we want to build telehealth that’s durable, we have to stop treating it like a tech rollout. It never has been. It never will be V体育官网入口. This is simply clinical care delivered differently. It deserves the same thought, structure, and feedback loop as any other service line. In short, when you're building, ask yourself: 💡 If this were in-person care, would you launch it this way. #telemedicine #telehealth #healthequity #remotecare.

🚀 Digital health is holding steady with $6. 4B invested in H1 2025 alone. 📈 Rock Health’s H1 2025 Market Overview makes one thing clear, that investors remain committed to digital health, backing 245 deals with a strong inclination toward purposeful & scalable solutions. One of the biggest takeaways. AI-enabled companies raised 62% of total digital health funding, and their average round size was 83% larger than peers. But with those dollars comes a higher bar. --- 💡 For product leaders, the signal is clear: 1. AI isn’t a strategy, but a tool. Teams must be focused on what real world problems AI is solving. Without clarity on the “why,” it’s just another buzzword. There must be crystal clarity and understanding of the real world problems. 2. Cross-functional depth and deep domain expertise is a must. Scalable and sustainable solutions demand teams that understand: •The clinical context which builds trust and relevance •The operational reality and barriers that impede scale •The business and reimbursement model in order to align with what payers and investors need to see 3. Execution matters more than ever. Companies like Hinge Health and Omada didn’t just raise capital. they turned clinical outcomes and operational discipline into value. That’s the bar. --- ✅ My final thoughts: Digital health is no longer in the “prove it” phase. With all the insights and learnings from past experiences, we're in the build it right and scale it smart phase V体育2025版. 🤓 This market won't just reward bold ideas. The market is looking for execution grounded in clarity, rigor, and product leaders who possess a cross-functional depth of knowledge. 💪🏼 Long-term value lies at the intersection of technology + clinical nuance + operational scalability. ♻️ #DigitalHealth #AI #ValueBasedCare #VentureCapital #HealthcareLeadership #HealthcareSaaS #NextGenRx #SmartRx.

🚀 Global Digital Health Assessment & Medical Diagnostics Startups Landscape: 4Q 2024 🌍 The healthcare industry is experiencing a revolution, driven by cutting-edge AI-powered innovations transforming how we diagnose and treat diseases. From early detection 🕵️♀️ to personalized care 🩺, startups worldwide are making healthcare more accessible, accurate, and efficient. ✨ Key Trends Shaping the Future ✨ 👉 AI-Driven Diagnostics: Faster, non-invasive, and precise—startups like Aiberry (mental health) and Aidoc (cardiovascular care) are setting the standard. 👉 Medical Imaging & Radiology: Leaders like Aidence and Paige are enhancing cancer diagnostics through precision AI tools. 🧠📊 👉 Portable & Wearable Devices: Innovations by Butterfly Network (ultrasound) and Hyperfine (MRI) are bringing medical imaging to underserved areas. 📱 👉 Predictive & Personalized Medicine: Companies like Cardiosense and Freenome are leveraging AI for early detection and tailored treatments. 🔬 👉 Voice Biomarkers: Startups like Sonde Health and Kintsugi are using AI to analyze speech for mental health insights. 🗣️💡 👉 Women’s Health: Platforms like LEVY Health and Sonio are revolutionizing reproductive and prenatal care. 🤰🧬 👉 Cross-Specialty Platforms: Solutions from Viz. ai (neurology) and PathAI (cancer pathology) are synchronizing care across medical disciplines VSports app下载. 🌐 🌟 Game-Changing Innovators Startups worldwide are leading the charge: 🔹 Butterfly Network (USA): Portable ultrasound devices 📱 🔹 Freenome (USA): Blood-based cancer detection tests 🩸 🔹 Sonio (France): AI-driven prenatal ultrasound tools 👶 🔹 Optellum (UK): Lung cancer diagnostics with AI 🫁 🔹 Coreline Soft (S. Korea): AI for lung and cardiac health 💓 🔹 Paige (USA): Generative AI-powered pathology solutions 🧬 #DigitalHealth #Healthcare #Assessment #Medical #Diagnostics #AIinHealthcare .

One Pitch Deck Does Not Fit All — I Learned the Hard Way When I was a first-time digital health founder raising capital, I made a rookie mistake: I built one beautiful pitch deck, polished every slide… …and sent it to every investor I could find—strategics, VCs, angels. Here’s the truth: It wasn't all that effective, because different investors are playing different games, and I initially didn't understand that. It took me a while to course correct and realize the differences between strategic, institutional and Angel investors. Here's what I wish someone had told me when I first started pitching Strategic Investors Think: pharma, health systems, medtech, insurers, large corporates. What they care about: - Science and clinical validity - Strategic fit with their portfolio, pipeline, geography - How your solution helps them win—market share, cost savings, product differentiation - Integration risk and operational lift How to pitch them: Lead with the strategic opportunity—make it obvious why they should care; Show them partnership models, pilot pathways, IP/licensing options; Address adoption and implementation risks up front Venture Capitalists Think: institutional investors chasing growth and returns. What they care about: - Market size, defensibility, and exit potential - Scalable unit economics (LTV:CAC) - Speed and quality of execution - Whether this can be a big win in their fund How to pitch them: Lead with the market problem and the size of the opportunity. Show traction, strong unit economics, and growth levers. Make the exit potential crystal clear—and framed in terms of their returns, not just your vision Angel Investors Think: high-net-worth individuals, often with personal or industry ties. What they care about: - Founder vision and grit - A story they can connect with - Early proof you can execute How to pitch them: Keep it human—angels invest in you as much as the business and emphasize early traction and why their money will move the needle. Less jargon, more narrative Pro tip: Before you send your deck, ask: - Do I know this investor’s real motivation for investing. - Does my first 5 slides answer that motivation. - You don’t need three totally different decks. But you do need to change the opening, emphasis, and close so each investor sees what they came looking for. That’s how you turn crickets into callbacks. If you’re in the middle of a raise and want to run a tight, investor-ready process that actually gets results—let’s talk. #digitalhealth #healthcare #startup #founder #VC #venturecapital #fundraising VSports手机版.

There's been great analyses on Hinge Health's S-1 already, but one thought that I've been noodling on:   Even with impressive metrics— $390+ million in revenue, 33% year-over-year growth, 77% gross margins, and strong trends towards profitability—Hinge will need top-tier revenue multiples (12-15x) to simply match its private valuation of $6. 2 billion from 2021.   A quick look at digital health comps today shows that median LTM revenue multiples are currently around 2-3x, a far cry from what Hinge needs.   Traditional telehealth companies are struggling.  Teladoc trades at about ~0. 7x TTM revenue despite generating $2. 6 billion in revenue, due to stagnant growth and nearly zero EBITDA margins. Companies like LifeMD and Talkspace have similar financial profiles and comparable valuation multiples V体育ios版. In contrast, Doximity leads the pack with ~20x TTM revenue multiples, driven by $475 million in revenue, 15% year-over-year growth, 90% gross margins, and 40%+ EBITDA margins. Perhaps this is an unfair comparison since Doximity is not a tech-enabled services company; alternatively, maybe this is the key takeaway itself.   It'll be interesting to see where the market places Hinge in this landscape and how growth stage investors react to the real disparities between public and private market benchmarks.

On my annual trek to the JPM Healthcare Conference, a critical question emerges about AI and healthcare investments: Are we investing in value or just digitizing inefficiency? 1. Digital Biology vs. Analog Medicine    • Traditional medicine operates like analog TV: fuzzy, low resolution and with limited channels.      • Digital Biology—through proteins, genetics, and multi-omics—offers HD-quality insights into human health    • Key stat: The vast majority of molecular disease drivers remain unmeasured in current practice [Nature Medicine, 2023] 2. Data: Quality Over Quantity    • Public datasets are table stakes. What's your unfair advantage?    • Real-world validation beats simulation every time    • Fact: Only 8% of AI healthcare solutions demonstrate real-world clinical impact [JAMA, 2023] 3. From Lab to Life    • Care delivery requires very different tools, data, quality control, and systems integration than discovery    • Clinical integration demands industrial-grade infrastructure and validation    • Reality check: Over 70% of AI healthcare solutions fail in real-world implementation [Gartner, 2023] 4. Value Creation vs. Status Quo    • Optimize outcomes, not processes    • Warning sign: Most healthcare AI today reinforces existing biases    • Evidence: 67% of current AI healthcare applications focus on administrative tasks rather than clinical outcomes [McKinsey, 2023] 5. Future-Proofing Healthcare    • Healthcare represents 20% of U.S. GDP, 60% of which is waste [JAMA, 2022]    • Digital transformation is inevitable—just ask Kodak or Blockbuster    • Critical question: Are you investing in healthcare's Netflix or Blockbuster? "The future is here, it's just not evenly distributed" - William Gibson (1993) Supporting Evidence: 1. "The Economics of Healthcare Transformation" - McKinsey Global Institute, 2023  - Details $500B potential annual value from digital biology 2. UK Biobank's Proteomics Revolution - Nature, 2023 - World's largest proteomics study (50,000 participants) showing the molecular basis of disease 3. "AI in Healthcare: Reality vs. Hype" - MIT Technology Review, 2023  - Analysis of real-world AI implementation success rates 4. "Digital Biology: The Next Frontier" - Cell, 2023 - Comprehensive review of digital biology's impact Bottom Line: AI isn't the revolution—biology is. Without deep biological data and real-world validation, you are building a faster horse in a world that will rapidly transition to cars.