Hubert Zajicek, MD, MBA

There appears to be a "Superstar Effect" in healthcare and biomedical AI research right now. A small percentage of publications are truly novel methods contributions that introduce new capabilities or behaviors; whereas a majority of contemporary research publications are focused on implementation science to assess the real-world utility and performance of new methods. This dynamic seems different from prior eras, when the translational infrastructure for implementing novel AI methods was largely unavailable. While methods research often captures more attention and accolades, both types of research are critical – novel methods without implementation science lacks translatability; implementation science without novel methods lacks novelty. If our goal is to invent and deploy transformative AI methods in real-world healthcare and life sciences contexts, we ought to continue encouraging and rewarding stellar implementation science work alongside breakthrough methods development.

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Exciting news from Monica Chopra, Jeffrey De Flavio, MD, Samantha Adelberg, and the rest of the Auxa Health team as they officially announce their $5.2M Seed round. The team's deep industry expertise and drive for change have led them to solve critical infrastructural friction to providing quality healthcare and adoption of value-based care. Auxa's AI benefit navigation platform is simplifying the complexities of healthcare by streamlining all of the fragmented and siloed data and information to make it actionable in real-time for healthcare organizations. For the 70% of Americans who aren't getting access to the health and social care benefits they deserve, Auxa's solution will be pivotal in enabling equitable care. We're thrilled to partner with co-investors Zeal Capital Partners, AlleyCorp, Laconia, and Chaac Ventures on this journey and look to share many more milestones ahead. Cc K50 Ventures, Ryan Bloomer, Daniel Vásquez, Nick Talwar, Stefanie Ng https://lnkd.in/dPDY7-Db

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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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Investing in companies that fill needs for health systems is a growth opportunity for both delivery organizations and start ups. Some systems are jumping in on their own, while others are partnering with like minded systems or with established VC firms. While this is a relatively new trend for systems, health plans have been making similar bets for many years. The benefits of becoming a health system portfolio company can be significant. Data, access to beta populations and real world coaching can be extremely beneficial. Start ups get mentoring and systems have to ability to leverage outside resources to solve relevant business problems. I predict a booming business!

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Imagine swallowing the competition whole. That's what many players in tech do via roll-up strategies, gobbling up smaller firms to deliver richer solutions and amass greater market share. Where else are roll-up strategies common? // HEALTHCARE Picture being a patient at a medical practice that’s been part of a roll-up in Healthcare Services. It's an industry ripe for roll-ups due to its fragmented nature and potential for greater efficiency. // CONSUMER SERVICES Or let's say you needed your HVAC serviced, and notice your local repairman is now part of a bigger Consumer Services entity? Centralized management and scale economy turn these localized businesses into roll-up targets. // FINANCIAL SERVICES Think about your insurance agent or wealth management advisor. They're working in complex, highly regulated environments. In the Financial Services sector, roll-ups offer an effective way to consolidate expertise, streamline operations, and enhance customer offerings. // MANUFACTURING Now, imagine driving past factories under a new name — the result of Manufacturing and Industrial Services roll-ups. Bulk purchasing reduces costs, enhances production capabilities, and expands geographical footprints. // REAL ESTATE Lastly, envision your real estate brokerage firm. The industry sees roll-ups as a strategic move to increase market penetration, enhance service offerings, and hike up portfolio value. Roll-ups play a huge role in most industries, rather like a snowball rolling downhill, gaining momentum, and size. Are you seeing roll-ups in your sector or considering M&A?

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M13 is thrilled to lead the Series A in RadiantGraph which is focused on personalization in healthcare. As we continue to invest in early stage companies it is abundantly clear that the biggest indicator of success is the founder and his or her ability to execute on their vision of the future. In this case, I don't think I have seen much better founder-market fit than we have with founder and CEO Anmol Madan. We believe in his vision: in order to have the best patient outcomes in healthcare we need increased personalization and AI is the breakthrough to get us there. Anmol started one of the pioneering digital health companies Ginger and then was Chief Data Scientist at Livongo and Teledoc. He has done it all: early stage, late stage, public company. And he deeply understands the nuances of the healthcare market from all angles which is critical for success. While there are many players building healthcare-specific AI capabilities, RadiantGraph is focused on outcomes: The platform is already processing personalization models for more than 3.5 million people, despite launching just last year. Excited to partner with my friend Adam D'Augelli and the great True Ventures again and Morgan Blumberg who has been deep in the healthcare market with me for many years. More on our thesis in the blog below. https://lnkd.in/evDDmC3W

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In our latest publication in Health, Management, Policy, and Innovation – "Why AI Is Good for Our Health but May Hurt Our Wallets," we examine how current regulatory frameworks, reimbursement structures, and business models for AI in healthcare are decoupled, creating an environment in which AI may significantly increase costs without necessarily improving outcomes. We recommend three interconnected reforms to unlock the full potential of healthcare AI: (1) Rigorous pre- and post-deployment evaluation to verify proposed clinical value, (2) Development of assessment standards through shared guidelines, and (3) Strategic alignment of AI deployment modalities with sustainable business models – "modality-business model-market" fit 👉 https://lnkd.in/d8NiczyM Sneha Shah Jain, MD, MBA, Clinical Professor and Kevin Schulman Professor of Medicine at Stanford University, Nigam Shah, Chief Data Scientist, Michael Pfeffer, Chief Information and Digital Officer, and Linda Hoff Chief Financial Officer at Stanford Health Care

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📊Why disadvantaged neighborhoods suffer more from asthma and COPD, and how can we change this? A recent article on Medscape explores this troubling reality. Factors such as environmental exposures and limited access to healthcare are driving these disparities. These statistics are particularly alarming because many of these health issues are preventable with proper care and early intervention. The article underscores the urgent need for more equitable healthcare systems. Moreover, a study published in JAMA Surgery showed that patients living in disadvantaged neighborhoods are more likely to experience worse post-surgical outcomes. In my view, technology and AI are key to addressing these disparities effectively. At Caresyntax, we see technology as a powerful equalizer in healthcare. By integrating AI-powered solutions into patient care, we're not only reducing the total cost of care but also enhancing access to quality healthcare for all. Our mission extends beyond optimizing surgical workflows; it's about transforming healthcare to be more accessible, affordable, and equitable. The statistics shared in this article should not determine the fate of disadvantaged communities. We have the tools at our fingertips - it's time to ensure they are available to everyone. 🌍 https://lnkd.in/gM8PyM8K #HealthcareInnovation #AIinHealthcare #Caresyntax #FutureofHealthcare

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Artificial intelligence (AI) revolutionizes healthcare by enhancing diagnostics, personalizing treatments, and streamlining operations. AI algorithms can analyze vast datasets, uncovering patterns that aid in early disease detection and more accurate diagnoses. This capability is particularly beneficial in medical imaging, where AI assists radiologists in identifying anomalies that might be overlooked. In drug discovery, AI expedites the identification of potential therapeutic compounds, significantly reducing the time and cost associated with bringing new drugs to market. For instance, companies like Insitro leverage machine learning to analyze extensive biological data, aiming to develop more effective treatments. Operationally, AI enhances healthcare efficiency by automating administrative tasks such as scheduling and patient record management, allowing healthcare professionals to focus more on patient care. However, the rapid integration of AI raises concerns about data privacy, algorithmic bias, and the need for transparency in AI models. Ensuring ethical AI deployment is crucial to prevent disparities in healthcare delivery. As AI continues to evolve, its potential to transform healthcare is immense. Balancing innovation with ethical considerations will be key to harnessing AI's full medical benefits.

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Telemedicine and telehealth rapidly transform patient care by offering accessible, remote healthcare solutions. This article emphasizes the growing adoption of virtual health services, addressing challenges like patient engagement and healthcare access. As demand for telemedicine rises, integrating digital tools and platforms becomes essential for healthcare providers to enhance patient outcomes and reduce costs. Telehealth is critical for shaping the future of healthcare, improving both efficiency and accessibility in a post-pandemic world. #PINCommunityAdvocate #RuralMedicine #PostCovid19 #Telemedicine #TeleHealth

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I saw this pattern of rapid growth and then consolidation happening in banking and FinTech in the mid 2000s. We jumped into Digital Healthcare in 2016 with the thesis that there were similar drivers. One big surprise, COVID, acted as rocket fuel to the industry but the same fundamentals apply. Consolidation of the biggest players , innovation by faster moving startups raising capital and then being acquired and patients expecting current ( i.e... wait, we are still using faxes? ) but rather now , de facto to them, omni channel consumer experiences. What can we continue to learn from past "explosions" of growth?

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Platforms are in, point solutions are out as the healthcare AI category leaders come into focus this year. In conversation with Shelby Livingston at Endpoints News, I shared: 1. Why AI-first companies have the greatest platform potential and heuristics for identifying these opportunities at the earliest stages, 2. How companies are differentiating through co-development and distribution partnerships with leading healthcare institutions, and 3. Strategies for navigating anemic budgets and constrained market sizes through business model innovation such as AI-enabled services and pay for performance models Read more here: https://lnkd.in/dJWqv_zC Bessemer Venture Partners Abridge #healthcare #lifesciences #AI #generativeAI

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Excited for our webinar tonight: Investing in Healthcare Startups: An Angel Perspective When: tonight at 6 pm eastern Where: https://lnkd.in/dPUFNbhe We had had a couple last minute changes and I am very excited to have an engaging conversation with Thanasi Tsiodras, Dr. Shaun Kuan and Regina Prasad, MS. We will be discussing: 1. How to start investing in startups 2. Lessons from your winners and losers 3. What are some red flags in a startup 4. What is your diligence process like? 5. How do you get deal flow?  6. What is the ideal angel investor archetype? Who should invest in startups and who shouldn't. #healthcare #venturecapital #angelinvesting

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We’re on the brink of a healthcare revolution; Generative AI is about to save hundreds of thousands of lives. However, the transformation won’t happen unless doctors, patients, and leaders unite. In the latest episode of The Business of AI in Healthcare Podcast, Robert Pearl, M.D. — a visionary healthcare leader and former CEO of one of the largest medical groups in the U.S. — reveals how Generative AI is transforming medicine, based on insights from his new book, ChatGPT, MD. In this episode, he reveals mind-blowing insights that every healthcare professional should know: 🩺  Generative AI isn’t just a tool—it’s poised to save hundreds of thousands of lives by preventing heart attacks, strokes, and cancer before they happen.  🌐  AI’s power is doubling every year—in 5 years, it will be 32x stronger, and in 10 years, 1,000x more powerful. The future of healthcare is moving faster than we can imagine!  🏥  The chronic disease epidemic—diabetes, hypertension, heart disease—could be managed by a triad of physicians, patients, and AI tools that provide real-time monitoring and personalized treatments, reducing deaths by up to 50%. Healthcare 4.0 isn’t coming—it’s here, and this episode shows how AI is reshaping the future of patient care. 👁‍🗨 🔗 Learn More about Robert Pearl, M.D. at: https://robertpearlmd.com/ 📚 Get your copy of ChatGPT, MD here: https://lnkd.in/ewVW3CJF Think you’ve seen it all in healthcare? Think again. Subscribe and discover AI’s game-changing impact: Listen to the full episode on: - Website: https://lnkd.in/eCbME_bf - Spotify: https://lnkd.in/eNY4rJkB - Apple Podcast: https://lnkd.in/e8iwkZrZ #HealthcareAI #EmotionalIntelligence #AIinHealthcare #HealthcareProviders #AIandHealthcare #BusinessofAIinHealthcarePodcast #HealthcarePodcast #HealthcarePodcast

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Artificial Intelligence is revolutionizing healthcare, bringing amazing advancements in diagnostics, treatment, and patient care. As these technologies evolve, it’s crucial to ensure they’re used safely and ethically. Here’s a look at where we are and what lies ahead: 🔍 Current Regulatory Landscape: In the U.S., the FDA and HHS are key players in overseeing AI-driven medical devices, ensuring they’re safe and reliable. Across the Atlantic, the EU’s AI Act, which kicks in August 2024, sets rigorous standards for high-risk AI systems, including mandates for transparency and ongoing risk evaluations. 🌍 Global Efforts and Recent Developments: The EU’s AI Act is a trailblazer, aiming to balance innovation with patient protection. The recent U.S. Executive Order on AI emphasizes the commitment to safe and trustworthy AI, with the White House AI Council spearheading cross-sector initiatives. ⚖️ Challenges and the Path Forward: With AI advancing rapidly, regulators face the challenge of keeping pace while ensuring safety. There’s a clear need for international cooperation to create unified standards. Moving forward, expect greater focus on transparency, accountability, and ethical practices. As AI becomes an integral part of healthcare, aligning regulations with technological progress will be crucial. Collaboration among government bodies, industry leaders, and global organizations will help ensure that AI innovations enhance patient care while upholding the highest standards of safety and ethics. Let’s stay engaged and informed as we navigate this dynamic landscape. Together, we can foster AI advancements that improve patient outcomes and uphold strong ethical standards. 🌐💡 #AI #Healthcare #Regulation #Innovation #PatientCare #Ethics #GlobalStandards #HealthTech #AIRegulation #FutureOfHealthcare #MedicalAI #AIInHealthcare #TechPolicy #DigitalHealth #AICompliance #HealthcareInnovation Read More: https://lnkd.in/g42FhhY3

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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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This is perhaps where the "U" turn for DTx starts? I'm not suggesting we will enter the highly bullish times of 2018-2021 but I think like a lot of technology cycles, this may serve as an inflection point as we look back on this 2-4 years from now. In addition to some of the additional coverage guidance around breakthrough treatments, we may see folks filing back into this space over the next 12-18 months. #dtx #digitaltherapeutics #FDA #reimbursement

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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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Revolutionizing Health Care Delivery With Artificial Intelligence

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