Andrew Kucheriavy

On episode #178 of #TheShot of #DigitalHealth Therapy, Jim Joyce and I had a blast chatting with Jonathan Pearce, the thoughtful and forward-looking CEO of Masterlete - and previously the co-founder and CEO of Zipnosis, the company that pioneered asynchronous telemedicine long before it was mainstream. From balancing athlete-grade performance with mental resilience to building a company that refuses to compromise between data and empathy, Jon brings his trademark blend of humility and precision. He also opened up about his own mental health journey, reminding us that resilience isn’t just a leadership skill - it’s a human one. It’s an episode that reminds us - even in a world of algorithms and wearables, the human spirit still defines the win. 📺 - YouTube - https://lnkd.in/dvDHg9RE 🍏 - Spotify - https://lnkd.in/dbKpEcTE 🍎 - Apple - https://lnkd.in/dsRW-svh 🔹 Top 5 Key Takeaways 💻 Lessons from Zipnosis: how DTC missteps became powerful playbooks 🤖 AI enables personalization - not replacement 🔥 Burnout prevention is the next performance edge 📊 From wearables to wisdom: data needs translation 🎯 Leadership = clarity, curiosity, and constant iteration Fun mentions as always: Pat Sukhum John Brownlee

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My 7 biggest takeaways from The Permanente Medical Group, Inc. experience using AI Scribes after 1 year. This is particularly interesting given the switch from Nabla to Abridge after the decision to go enterprise-wide with AI Scribes by Kaiser Permanente. 1️⃣  72% of physicians used the AI Scribe at least once among a sample of 10,000+ physicians who were given access Also, at the end of 2024 the adoption curve was still trending up, so it may not have plateaued just yet. 2️⃣ 34% of physicians used AI Scribes in at least 100 patient encounters… but that means the other 38% of physicians who tried it only used it for an average of less than 0.38 patient encounters per work day (< 100 encounters / 260 work days) In other words, usage is driven by the top cohort of users. This is what will drive the argument from health systems from why the pricing model should not be “per user” and why the enterprise license should be at a fraction of the original “per user” costs. Ambient vendors will argue that the “per user” pricing already baked in this distribution of usage among possible users, and this is still a fraction of what hiring human scribes for every clinician would cost. 3️⃣ Highest physician adoption was among mental health (42%), primary care (32%) and emergency medicine (32%), based on % adoption by clinicians in each specialty. No real surprises here. 4️⃣ The top 33% of physicians who tried the AI Scribe (“High Users”) were responsible for an overwhelming 89% of the total usage of the AI scribe. In fact, High Users also were the ones who needed it the most - as pre-AI Scribe they tended to be physicians with more time spent in the EHR per appointment and fewer patient visits per day. Not provided: did High Users end up now doing more patient visits per day than before? 5️⃣By the end of 2024, High Users spent even less time in notes than Low Users and Non-Users (i.e. didn’t try AI scribes even once) → High Users went from 4.5 minutes/note to 2.5 minutes/note → Low Users went from 3.75 minutes/note to 2.9 minutes/note → Non-Users went from 3.75 minutes/note to 3.4 minutes/note Will data showing that maybe they could save 30 seconds per note motivate the Non-Users to become Users? I’d guess No. 6️⃣ 57% of patients experienced no difference in time physicians spent looking at a computer screen (caveat: small n=118 sample) This was surprising. Begs the question: were some physicians weren’t looking at a screen much normally during a visit, or whether they just couldn’t shake the habit? 7️⃣ Adoption of AI Scribes were mostly agnostic to the vendor Although the total physician adoption essentially doubled after switching vendors, the team felt that this was related more to: → The positive experience of Vendor 1’s pilot → Increased awareness and support provided over 2024 → Implementation of EHR integration with Vendor 2 Hard to tell how KP truly felt about this or if they were just being nice. Full article in the comments 👇

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💙 𝗔 𝗹𝗼𝘃𝗶𝗻𝗴 𝗰𝗿𝗶𝘁𝗶𝗾𝘂𝗲 𝗼𝗳 𝘁𝗵𝗶𝘀 𝗮𝗿𝘁𝗶𝗰𝗹𝗲. Here's a key quote to get us started: "Across health systems, CMIOs describe three ways they are guiding clinicians as patient-generated AI becomes a routine part of care encounters." 1️⃣ 𝗥𝗲𝗳𝗿𝗮𝗺𝗶𝗻𝗴 𝗔𝗜 𝗮𝘀 𝗮 𝘀𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗽𝗼𝗶𝗻𝘁 — 𝗻𝗼𝘁 𝗮 𝗱𝗶𝗮𝗴𝗻𝗼𝘀𝗶𝘀 "At University of California Irvine Health, CMIO Deepti Pandita, MD, said clinicians are trained to gently correct misinformation and reposition AI outputs as tools for education and shared decision-making." 👉 What does "gently correct" mean? How are clinicians trained? Please publish this training! 🙏 "At Los Angeles-based Mission Community Hospital, Jason La Marca, MD, CMIO, said clinicians are encouraged to treat AI-generated content as a conversation starter — similar to the WebMD or Medscape printouts patients have long brought into appointments." 👉 Is this saying that clinicians have to deal with yet another Dr. Google, this time Dr. ChatGPT, second-guessing their expertise? 2️⃣ 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝗶𝘇𝗶𝗻𝗴 𝗵𝗼𝘄 𝗰𝗹𝗶𝗻𝗶𝗰𝗶𝗮𝗻𝘀 𝘀𝗲𝘁 𝗯𝗼𝘂𝗻𝗱𝗮𝗿𝗶𝗲𝘀 𝗮𝗻𝗱 𝗰𝗼𝗿𝗿𝗲𝗰𝘁 𝗺𝗶𝘀𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 "At Roseville, Calif.-based Adventist Health, CMIO Amer Saati, MD, said clinicians are instructed to acknowledge patient-generated AI content, correct misinformation directly and anchor every encounter in evidence-based care. Organization-approved AI tools can support patient education and shared decision-making, he said, but clinical assessment remains central." This is GREAT advise! 👉 My only question is: Will this AI editing and approval add yet another burden to clinicians? Where's the clinical ROI in that? "Some systems acknowledge they are still early in developing formal guidance. At Wenatchee, Wash.-based Confluence Health, CMIO Becket Mahnke, MD, said the organization does not yet have system-level policies for managing patient-generated AI content. However, after a recent Wall Street Journal article prompted patient questions about ambient documentation, the system proactively provided clinicians with scripted responses so they would be prepared." 👉 Every clinic, hospital, health system, and health-related organization in general needs an AI policy now! Even if you're not using AI, your patients are! 3️⃣ 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗶𝗻𝘁𝗼 𝗔𝗜 𝘁𝗼𝗼𝗹𝘀 𝘁𝗵𝗲𝗺𝘀𝗲𝗹𝘃𝗲𝘀 “'If a clinician uses the content provided by AI, they understand that they are responsible for the generated output,' [Parkview Health, CMIO Mark Mabus, MD] said." YES, YES, YES! 𝗜𝗻 𝗮 𝗡𝘂𝘁𝘀𝗵𝗲𝗹𝗹 "The shift, leaders say, is less about controlling what patients bring into appointments and more about equipping clinicians with the language, guardrails and accountability needed to keep AI-informed conversations grounded in safe, evidence-based care." 𝗧𝗵𝗲 𝗕𝗼𝘁𝘁𝗼𝗺 𝗟𝗶𝗻𝗲 Whether you like it or not, GenAI is here. Lead it or it will lead you!

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California’s new law regulating #AI #companion #chatbots marks a significant, first-in-the-nation step toward safer digital #mentalhealth interactions, particularly for minors. The law, signed by Governor Newsom, introduces mandatory safety protocols for AI companion chatbot operators. This legislation targets companion chatbots, explicitly excluding customer-service and internal-use bots. It responds to tragic incidents and concerns regarding the safety of vulnerable users interacting with unregulated AI. The law is set to take effect on January 1, 2026. As an investor focused on the intersection of healthcare and technology, Nina Capital views this regulatory progress as a validation of safety-by-design as a foundational requirement. Clear labeling, age-appropriate experiences, and evidence-based crisis routing are hallmarks of responsible innovation. We are proud to see our portfolio company, Sonar Mental Health, actively positioned to meet and exceed these evolving standards. Sonar's model, which incorporates a human-in-the-loop approach, offers an inherent layer of compliance and safety that pure AI-only companion bots do not have. We believe this human-in-the-loop model is currently the best approach to genuinely reduce risk while preserving access to supportive, ethical AI tools. We welcome collaboration with lawmakers, clinicians, and peers to operationalize safeguards in a manner that protects users without stifling clinically valuable innovation. Read the full TechCrunch article by Rebecca Bellan here: https://lnkd.in/dj9Z7eaH Kudos to Drew Barvir and the Sonar team for their dedication to safe, effective mental health technology. #wearenina #healthcare #MentalHealth #AI #Policy Rebecca Schechter Monica Rivera Yahel Halamish Marc Subirats

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✨ Big news for us at Hyro ✨ We’re teaming up with Sutter Health to transform how their 3.5 million patients connect with their care. By bringing Hyro’s responsible AI agents into voice, chat and SMS, Sutter Health will redefine their modern patient experience. ➡️ “We focus on empowering patients and changing the experience around what is possible in healthcare. And to that end, we are always looking for opportunities to build stronger connections with consumers across all channels and engage in ways that fit into their lives,” said Jennifer Bollinger, Chief Consumer and Brand Officer for Sutter Health. “With the addition of an AI-powered voice and chat communications platform, Sutter will continue to transform touchpoints for our patients and our people, helping drive better patient engagement, streamline operations for our teams and deliver data-driven insights that can help us better serve their needs now and in the future.” Proud to see our tech helping unburden staff, unblock patient access, and unlock insights for one of California’s most innovative health systems. 🎉 Read the full story: https://lnkd.in/d8QZcw4R

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Whether the healthcare system's ready for it or not, consumers are using AI for their care. We've talked about the pros and cons of "Doctor Google" for decades. Now we're going to be talking about "Doctor ChatGPT". Rumor has it that OpenAI is even taking out ads to promote GPT-5 for healthcare. Consumers are already using these tools (I certainly have!). They'll be coming to appointments with information from AI - not from Google. Ultimately, we can't control how consumers access healthcare information. Instead of scolding patients who use this, we should embrace this as the future of how consumers will interact with health information and figure out strategies to make it the most effective. #healthcare #digitalhealth #healthtech #healthai https://lnkd.in/gUtKRUqB

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Exciting news! MoldCo is now live and available in California. Our clinician-led digital health platform standardizes mold detox as routine preventive care rising to meet the growing, often hidden health risks mold poses. A recent LA Times article perfectly captures the challenge: modern, energy-efficient homes can unintentionally trap moisture, creating an ideal environment for mold growth that affects both home durability and occupant health. At MoldCo, we combine advanced lab testing and personalized therapies to detect and prevent mold-related illness before it starts. Prevention is better than remediation. Californians now have a trusted partner in MoldCo to help protect their homes and health. Read the article here: https://lnkd.in/gxdkjyf5

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𝗢𝗽𝗲𝗻𝗔𝗜’𝘀 𝗛𝗲𝗮𝗹𝘁𝗵𝗕𝗲𝗻𝗰𝗵 𝗺𝗮𝘆 𝗵𝗮𝘃𝗲 𝗹𝗮𝘂𝗻𝗰𝗵𝗲𝗱 𝗳𝗼𝗿 𝗺𝗲𝗱𝗶𝗰𝗶𝗻𝗲—𝗯𝘂𝘁 𝗶𝘁𝘀 𝗿𝗶𝗽𝗽𝗹𝗲 𝗲𝗳𝗳𝗲𝗰𝘁 𝗰𝗼𝘂𝗹𝗱 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺 𝘁𝗵𝗲 𝗳𝗶𝘁𝗻𝗲𝘀𝘀 𝗮𝗻𝗱 𝘄𝗲𝗹𝗹𝗻𝗲𝘀𝘀 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝘆. 🧠💪 At first glance, HealthBench looks like another step forward in clinical AI: LLMs benchmarked against tasks like emergency triage, medication planning, and writing medical notes that are nearly indistinguishable from those of physicians. But here’s the 𝘳𝘦𝘢𝘭 signal beneath the noise: 🔍 HealthBench gives us a new framework to measure how well AI performs in high-stakes human decision-making. And that opens the door for a fitness parallel—a potential “PerformanceBench” that evaluates how AI models support: • Personalized training program generation based on sleep, HRV, menstrual phase, or glucose trends • Real-time decision-making in overtraining, RED-S, or injury risk • Nutrition and hydration guidance layered against individual physiology • Recovery strategy recommendations that actually improve outcomes In my world—where wearables like ŌURA, Garmin, POLAR, WHOOP, and Ultrahuman are becoming default for anyone serious about their performance—we’re already seeing clients bring AI-generated insights to the gym. 📲 “My app said today’s a zone 2 cardio day because I only got 5.5 hrs of sleep and my HRV dropped 12 ms.” 📈 “My recovery score was low, so I swapped strength day for mobility.” 🧠 “ChatGPT gave me a split routine based on my soreness and whoop strain.” This isn’t just personalization—it’s AI-driven agency. But as these AI tools become more widespread, we need to know: are they right? Are they effective? Are they safe? That’s where HealthBench’s model matters—because what it did for healthcare, we need in fitness: ✔️ A standardized way to benchmark LLM performance on decision quality ✔️ Human expert comparison (like physicians, coaches, RDs) ✔️ Transparent evaluations of what’s working, and what’s just noise The fitness and wellness industry has long lagged in evidence-backed programming outside of elite sport. But with HealthBench as a roadmap, we now have a chance to hold AI coaching to a higher bar—and build trust in tools that can scale expert-level insights. The future of fitness isn’t about AI replacing coaches. It’s about AI that earns its place alongside them—by being measured, validated, and improved. Learn more about OpenAI’s HealthBench - https://lnkd.in/ewEVMRWH 💬 I’m curious: how would you define a benchmark for AI in fitness and performance? What metrics matter most? #OpenAI #HealthBench #AIinFitness #WearableTech #RecoveryScience #DigitalHealth #PerformanceOptimization #LIFTS #FutureOfFitness #LLMs #PersonalizedWellnes

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#AI + #Robotics: Redefining Fertility Care and #IVF Success I’m humbled to be featured in Fox News discussing how AI-powered robotics are transforming reproductive medicine. “As both a physician and an AI futurist, I believe our goal is not just more births, but healthier beginnings — achieved responsibly, ethically and equitably.” 💡 The problem: Infertility affects 1 in 6 couples globally. Traditional IVF involves over 200 manual lab steps each one introducing human variability, cost, and emotional strain. Success rates can vary dramatically between clinics, and a single cycle can cost up to $25,000. 🤖 The innovation: New AI-driven robotic systems are now automating these delicate steps improving precision 10×, enhancing consistency, and lowering costs. This shift could democratize fertility care, offering hope to millions of families worldwide. 🌍 The impact on healthcare: • Standardizes quality and reduces human error • Boosts IVF success rates while lowering emotional and financial tolls • Expands access to fertility treatment across socioeconomic barriers • Introduces new ethical frameworks for responsible AI use in medicine I’m deeply grateful to the Fox News Media Health team for spotlighting this pivotal intersection of AI, ethics, and life creation. The convergence of robotics and compassion reminds us that technology’s highest purpose is to serve humanity. Harvey Castro, MD, MBA. ER Physician • AI & Healthcare Futurist #AIinHealthcare #IVFInnovation #HealthTech #DigitalMedicine #AIFuturist #FertilityRevolution #PrecisionMedicine #Robotics #EthicalAI #DrGPT https://lnkd.in/gM-4_ZyQ

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In our latest newsletter, I go deep into why we believe the next three years of healthcare innovation will be defined by two specific trends: Voice Agents and Hybrid AI Care Models. Here is the quick breakdown: 🎤 Amplifier Health (Voice AI Diagnostics): Amit Mehta, Jeremy Barber, and Peh Keong are doing the impossible. They have built a Large Acoustic Model that can screen for multiple medical conditions from a phone call. By focusing on the physical properties of sound rather than just words, they are creating a screening and diagnostic tool that is accessible to anyone with a phone. 🧠 Meru Health (Hybrid AI-Enhanced Care): Kristian Ranta, Riku Lindholm, and Henri Koponen are solving the "efficacy crisis" in mental health. Their 12-week program treats the mind and body together by combining licensed clinicians with biofeedback technology. With millions of lives covered, they are proving that value-based care is the only way forward. The Bigger Picture: We believe the "Golden Age" of healthtech is moving toward a model where AI handled the routine data and diagnostics while humans focus on high-level clinical decisions. Whether it is a voice agent triaging a patient or an AI-enhanced clinician monitoring recovery, this hybrid approach is how we solve for both access and quality. Read the full breakdown of our investment thesis #HealthTech #VentureCapital #AI https://lnkd.in/dqDGBnJF

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Do physicians or AI offer better treatment recommendations? In a recent Cedars‑Sinai study published in the Annals of Internal Medicine, AI-powered virtual urgent care visits demonstrated that “AI Recommendations Were Graded Higher Than Physician Decisions” Well, at least that was the subheadline intended to grab the reader’s attention (and rank higher in SEO results)… But here’s the key. If you read the study and accompanying article, AI didn’t replace the physician and clinical staff — it empowered them. AI was good at certain things, such as identifying red flags (i.e., specific, finite signals or changes in side effects). Physicians were substantially better at understanding the complete patient history and adapting their treatment recommendations as needed. Physicians were the lead, and AI was best playing a supporting role. When AI handles structured intake, ongoing engagement, and data organization, the physicians and the clinical team can focus more energy on the nuanced, human side of care. That means more time available for listening, adapting, and building trust… and, most importantly, making the diagnosis and treatment decisions that really matter—decisions only a human can and should make. The opportunities for AI + clinician collaboration in patient engagement are clear. Use cases are growing every day. For example:  -- Streamlining intake: AI gathers detailed symptom histories in minutes, ensuring providers have a comprehensive picture before the visit begins -- Identify red flags early:Algorithms surface warning signs (e.g., side effects, possible antibiotic resistance) so providers can act faster. -- Support follow‑up care: Automated messaging keeps patients informed about lab results, referrals, and recovery steps—without tying up staff phone lines. -- Reduce cognitive load: By organizing patient data and history, AI helps clinicians spot patterns and make confident, informed decisions. When designed thoughtfully, AI is not a competitor—it’s the ultimate teammate, enabling medical professionals to spend more time practicing medicine and less time chasing data. How could your patient outcomes improve if AI handled administrative tasks and your team focused 100% on care? Cedars‑Sinai article: https://lnkd.in/gfayMimN Annals of Internal Medicine Study (Full Abstract) https://lnkd.in/gKdvcTZR #AIAgents #DigitalCare #HealthcareAutomation #PatientPrep #ThinkneticAI

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