David Gardner

Big healthcare AI news yesterday as Tempus AI received the first-ever CPT code for an algorithm-only analysis of previously-sequenced, laboratory developed test transcriptomic data. TLDR: AI molecular phenotyping has a new business model. The PurISTSM test uses RNA profiling to identify molecular subtypes in patients with advanced pancreatic ductal adenocarcinoma, which may inform first-line therapy selection and management. While I'm skeptical that payer balance sheets are going to solve the "who pays for healthcare AI" problem, the reimbursement pipes for clinical AI are maturing. I am surprised to see more progress for usage-based vs. performance-based models given the many challenges with FFS economics. It will be interesting to see how payers assess the "medical necessity" and therefore reimbursability of clinical AI as these models come to market. https://t.co/eLe18SmihV

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I used to spend 2-3 hours daily on clinic notes, skeptical of AI scribe technology. However, I've been impressed with RevMaxx, a generative AI company transforming clinical note creation by listening to physician-patient conversations and automatically generating comprehensive notes. This platform accurately captures crucial ICD-10 codes, saving valuable time ⏰. 👉 Why This Matters: - **Reducing Physician Burnout:** Administrative tasks are a significant contributor to physician burnout. Innovations like RevMaxx alleviate this burden effectively. #HealthcareInnovation #AI #PhysicianBurnout #MedicalDocumentation #HealthTech #RevMaxx

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✴ New Podcast Episode: Startup Location and Pricing💲 Check out this great startup episode where we touch on some of the most important points every NP looking to start their own clinic needs to address! https://lnkd.in/gfmNSYF3

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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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A whirlwind of activity last week at the America's Physician Groups conference. Lots of solid insights shared by health system leaders. Some notable thoughts: +++ Artificial intelligence is intelligent in different ways: By now, we all know ai has a diverse set of use cases, incorporated in different applications and tools. But there are fundamental differences in how the intelligence itself is brought to life. Examples include: - Predictive AI, used to forecast future outcomes by leveraging historical data. Shout out to UCLA’s CKD/ESRD early intervention protocol (Joycee Berin) and Diagnostic Robotics’ intelligence care post-dicharge journeys (Kira Radinsky) - Protocolized AI, used to automating a user’s administrative load by using a set of detailed, pre-defined rule sets. Thanks to ARC for sharing their experience using Elaborate 's automated outpatient lab summaries (Manish Naik) - Generative AI, used to create new content. Great overview of ambient documentation at MGB as well as Cedars’ Sinai talking through its medical ontology model powering acute triage (Caroline Goldzweig) Across system leaders and experts, there was clear agreement that the first step to implementing intelligence intelligently is defining the ‘jobs to be done’. That way, internal and external stakeholders are clear on what they're solving for when they architect the solution.  +++ Scaling AI takes time and rigorous observation: Market leaders describe a phased pilot approach that allows clinicians to build confidence and system leaders to measure ROI before deploying systemwide. Loved hearing Rebecca Mishuris outline MGB’s novel approach of piloting two solutions against one another, to pressure test implementation, workflow, and value creation. +++ Proving ROI continues to be challenging: Lots of vendors using lots of different metrics to prove value, but the majority of leaders agreed that estimating the ROI of these new tools today is part science, part art. Demonstrating the ROI of the “soft” metrics around provider burnout and retention seemed to be a big opportunity, especially for investment in more efficient primary care and PCP wellbeing. After all, PCPs drive referrals to specialty-level care (and higher reimbursements) for health systems. Appreciated Anurang Revri's overview of how working team setup can also impact ROI estimates. +++ Value-based care = tools + humanity: VBC will require not only implementing tools to support clinical documentation, risk capture, upcoding, etc, but also humanizing interactions to engage patients. Countless examples, but one that made me smile was a depression focused chat bot responding in the following interaction: - Context: post-discharge check in Bot: Hi Freida, how are you feeling today after your surgery?  Patient: I’m having a tough time, am in a lot of pain.  Bot: Well, it can’t be that bad, I’m sure it will get better with a positive mindset!    🤣 🤣 🤣 Can't wait for next go-around!

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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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Distilled from discussions with numerous healthcare C-level executives, sharing here today the HEART Framework that Health systems and IDNs can use for evaluating and embracing AI-driven solutions in Healthcare. Your insights are invaluable—please share your thoughts on what resonates or what can be added! 🔹 Healthcare Value: Prioritizing and solving key pain points swiftly—can you see tangible benefits within months? 🔹 Economic Analysis: Is the ROI justified? How do you evaluate the impact of AI ? 🔹 Adoptability: How do you ensure sustained adoption and engagement across your organization? For example: Deep workflow integrations 🔹 Regulatory Compliance: Does the solution uphold the highest standards of security and compliance? 🔹 Transformation and Risk: Ready to balance risks and manage change by starting in low-risk, high-value areas? Full article here: https://lnkd.in/dthy5_yw Your feedback is crucial as we navigate the integration of AI in healthcare. Let's discuss how we can drive transformation effectively. #AI #HealthcareInnovation #DigitalHealth #Leadership #HEARTFramework

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Grab a megapack of the hottest HLTH takeaways — By top healthcare innovators: (see more in the presentation ↓ ) Personally,  I was impressed by the HLTH scale. The agenda, networking, and expo were a blast. And connecting with healthcare forward-thinkers? The greatest pleasure of all. 👇 Here’re some worthy ideas to dig into: Christian Hein →  Healthtech marking positive trends in care. Carolina Correa →  We need to rethink the balance of tech/human roles. Jeremy Dähn →  Data & transparency are key drivers of healthcare change. Shez Partovi →  GenAI should be used for patient empowerment. Arnaud WILMET → The risks of not adopting AI outweigh adoption risks. Blas Diaz → AI needs a patient-centric focus for impact. Christopher Nial → UK healthcare is ready to embrace AI benefits. Ben Richardson →  Change management in AI adoption is the key. Eve Cunningham MD MBA →  Virtual care requires digital infrastructure transformation. Natalia Karbasova → Tech-driven prevention is key to wellness. Dr. Sven Jansen → The new healthtech era lies in holistic health. Dr. Felicitas Muth → Value-based care is impossible without patient focus. Tanja Tervonen →  To succeed, nail the 4 R’s for US commercialization. Christele Berthelot-Logsdon → A neglected strategy: incentivize payors to help startups. Roxanne King →  Focus on AI, chronic disease, health equity. Marty Gordon →  Tackling sustainable healthcare is crucial. Stef Nimmegeers →  Prevention is underfunded and underprioritized. Charlotte Pierron-Perlès → Connected health solves clinical trial inefficiencies. Sophie Burton-Jones →  Incentivization is way harder than it seems. Olaf Schneider → Health data drives next-gen diagnostics accuracy. Anna Codognotto → Data protection enhances AI reliability. Clara Landahl →  Administration complexity hinders efficiency. Moz Siddiqui → Women's health needs prioritization and support. Shana Hudes →  The transition from curative to predictive care is near. Hagar Anna Spits → The UK is ready to drive healthcare innovation. Kim Leung → Underfunded women's health needs change. Adam Brown, MD MBA →  The risks of healthtech divide are real. Samuel Scheer → Healthcare innovations will drive cardiometabolic care. P.S. Which one’s your favorite? Share in the comments and let’s kick off the discussion! HLTH Europe #hlth #hltheurope #hlth2024 #healthtech #innovation

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One key reason why healthcare technologies like AI, telemedicine, and software haven't structurally lowered costs or broadened access for the entire system after decades of experimentation (excluding pure financial engineering of payer contracts) is the limited reimagining of care delivery itself, with asynchronous telemedicine as a notable exception. In the same way that digitizing physical paper failed to exploit the capabilities of a new computing medium for word processing, hosting physician-patient conversations over video does not transform the actual delivery of care. In telemedicine, many of the inputs (e.g., clinician time) and therefore cost structures of in-person care persist, which is why we often see fee-for-service telemedicine companies struggle to achieve economies of scale (i.e., growing revenues non-linearly while growing costs linearly). Until we deconstruct the components of a medical appointment – from intake and triage, to chart review, history gathering, physical examination, diagnosis, treatment, and follow-up – we will continue to be underwhelmed by the disconnect between the transformative potential of these technologies and real-world patient/system impact. I’m optimistic that the emergence of reliable and performant medical AI agents will urge us to perform this deconstruction and redesign the fundamental building blocks of a “medical appointment.”

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Galen Growth | Insights You Can Trust just published its executive summary of its analysis of the #digitalhealth ecosystem performance in the first 6 months of 2024 - Read the key trends and insights here

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Telemedicine is dead. Or is it? 📉🩺 We've seen the meteoric rise and fall of giants like Teladoc and other telemedicine companies. The pandemic era sparked unprecedented growth in virtual care, but what happened next? Declining stock prices, wavering investor confidence, and questions about the sustainability of this healthcare model. Don't equate a failed business model (Teladoc was cozy under the sheets with insurance companies and forget to take care of doctors) with a failure of telemedicine. So let's shift gears. 🚀 Telemedicine isn't just a trend—it's a powerful tool that should be synonymous with modern healthcare. 🌟 **The Benefits**: - **Accessibility**: Reach patients in remote areas with ease. - **Convenience**: Eliminate the need for travel and reduce wait times. - **Efficiency**: Streamline processes, from booking to billing. Imagine this: providing guidance to patients, offering second opinions, and educating the masses—all without the friction of traditional office visits. 🏥💡 Telemedicine is here to stay, evolving to meet the needs of our digital age. As we navigate its integration, we must focus on: - **Technology access**: Ensuring everyone can connect. - **Regulatory clarity**: Harmonizing laws across regions. - **Data security**: Keeping patient information safe. Let’s lead the charge in embracing telemedicine as a vital part of healthcare’s future. The fact remains we have an asymmetry between where doctors live and where patients have access to care. Until we train more doctors, make living and working in rural America more attractive, we are going to have to embrace alternative ways of providing care. Telemedicine is one of the solutions. Regardless of Teladoc's stock price. Together, we can create a more connected, efficient, and equitable system for all. 🌍💼 #Telemedicine #DigitalHealth #HealthcareInnovation #PatientCare #FutureOfHealthcare #telehealth #healthcare

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Reboot Communications Ltd. What needs to be done? Here are four specific transformative roles the federal government should incorporate into the budget: @Healthcaresumm #hcs #healthcare #healthcareinnovation #healthcaretransformation #healthcaretrends #pointofcare #homecare #digital #digitalhealth #wholepersonhealth #elderlycare #disruption #genetics #longevity #healthyliving #healthdata 

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https://lnkd.in/gvH6WuTx Digital health is a tough place for startups. While it appears as a doomsday, there's no denial that digital health is a priority for players in the industry esp for tracking progression on chronic diseases and care continuum beyond hospital. The shift from wellness to clinical in digital health is fueling growth of market. Digital health is future. However, successful launch requires robust real world evidence, commercial strategies including reimbursements. Important to work with a partner who has experience in navigating regulatory pathways and human centered design to build seamless digital workflow experience to HCPs and patients, two critical stakeholders who make or break the digital health.

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This analysis, at least anecdotally makes sense to me. In many situations, infringe and holdout is the least painful option for large infringers. The system enables it. - The plaintiff must allocate the time and $$ to assert, taking time and $$ away from selling and developing products. Even if they engage litigation financiers they are limiting their upside potential. - The infringer continues to infringe while employing stall tactics or simply relying on the painfully slow, overburdened legal system. - The cost benefit analysis for infringers - "infringe and pay lawyers" typically outweighs the cost of design around or license. - Enhanced damages and injunctions are rare. - Litigation insurance products reduce risk all around. "The Marcum report shows that there is indeed something wrong with the patent system in the United States but it’s not excessive litigation or patent trolls. The real problem is the inability of patent owners to enforce their rights against infringers. Given the difficulty of obtaining injunctive relief and the limited enhancement of damages, it is unsurprising that predatory infringement has become a standard business practice when, at worst, all an infringer can be expected to pay is a reasonable royalty and, at best, nothing at all."

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I am very excited to share the pre-print study on Atropos Health ChatRWD beta results(link to paper below). ChatRWD beta outperformed ChatGPT 3.5, Google Gemini 1.5 Pro. and Anthropic Claude 3 on answers to clinical questions when reviewed by independent physicians. OpenEvidence also outperformed the Big Tech LLMs by a wide margin. Most important to us, ChatRWD performed highest on Physician trust and Best Answer and was able to answer questions asked 94% of the time. As the Gen AI cycle continues to move at a rapid pace we firmly believe that "Trust" and "Accuracy" are going to be critical, and that publishing your performance on both is table stakes. It is also clear to me that in the quest to be able to answer 100% of questions with Clinical grade accuracy training LLMs solely on the literature will not be enough. We need to produce new evidence in the form of high-quality transparent studies using appropriate methodology. We are adding beta users post this announcement, so please sign up to try it, and we will have more to come on full launch this summer. Exciting times and hope everyone has a great July 4th. https://lnkd.in/es5gWK84 #generativeAI #LLM #Realworldevidence

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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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The medical industry has room for almost unlimited innovation. There are so many problems to be solved with software and hardware across programs, materials, nanotech, biotech, you name it. The best part is all of this innovation helps people overcome health challenges! #health #medical #innovation

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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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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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