Kirsten Morbeck

The (Healthcare) Ground Beneath Our Feet… This year it is likely that over $10 billion will be invested in the digital health sector – a robust amount, no doubt, but inconsequential when compared to the amount of capital tied up in healthcare real estate assets, which is estimated to be $1.2 trillion by Jones Lang Lasalle. Of that amount, approximately $790 billion is in the hospital sector while the remaining $490 billion is in medical office assets. It is estimated that there are 48.6k facilities with 3.4 billion square feet of healthcare real estate, 42% of which are owned by REITs and another 33% held by other private investment vehicles. Much of the digital health investment is meant to make the physical healthcare infrastructure more productive: greater operating efficiencies, greater patient throughput, more relevant personalized care models with better outcomes. As the healthcare system is being pushed to be more distributed to lower cost sites of care, accelerated now by the rapid proliferation of automation and AI capabilities, the potential impact on healthcare infrastructure assets will be profound. Thoughts on what that might look like... https://lnkd.in/eTfAdUbS #digitalhealth Flare Capital Partners

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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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Latest #PitchBook data for #HealthIT investment shows a preference for later stage investment across healthIT that pre-dates the VC downturn and current interest rate environment. Even though healthIT has been more resilient to current headwinds compared to health care services and PPM plays, perhaps it speaks to a need to scale solutions and points of saturation for new entrants. "...In the lower middle market, we are beginning to see more examples of a phenomenon we have anticipated for a while: PE firms and PE-backed companies acquiring VC-backed startups. Lower-middle-market PE firms perennially complain that VC- backed companies expect too-high multiples, and these firms would generally prefer to invest on a multiple of EBITDA rather than a multiple of revenue..." Speaks to a convergence that would allow PE-VC M&A on both ends of the startup spectrum. #HealthcareVC #healthcarePE

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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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Healthcare is highly suited for AI automation, with many opportunities to improve accessibility, affordability, and outcomes. AI can drive efficiencies across various functions, though it will inevitably reduce the need for some human roles. #higherorder #ai #automation #healthcare #healthtech

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This analysis explores how Point of Care Testing (POCT) digital health technologies impact emergency care. It highlights how AI-powered remote monitoring can significantly improve operational efficiency in healthcare and enhance patient outcomes. Read more: [Nature](https://lnkd.in/gYb4hjXX)

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Some VC investors believe that brick and mortar - referring to a physical presence of some kind - should be avoided at all costs. Yet, the track record of clinic and hybrid care businesses in health care indicates otherwise. ==> One Medical (sold for $3.9 billion to Amazon), Oak Street (bought by CVS for $10.6 billion), Lifestance (IPO at $7.5 billion market cap), and PE-backed Premise Health (acquired by OMERS Private Equity for $1.1 billion) If a clinic is indicated as the optimal way to deliver care for that patient population, there are creative ways to build and operate them. Full article below with advice and strategies on how to build and operate hybrid clinics from my teammate Anarghya Vardhana from Maveron, Amir Dan Rubin from OneMedical Group, Steven Eidelman from Modern Animal and more!

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How do we use technology and new business models to connect care teams across specialties in service of better patient outcomes at lower cost? Care convergence brings together different clinical disciplines, tech and new payment models to take on the costliest conditions in the system from #diabetes to #dimenia. For me, it offers a new way of … Thinking… Investing in … Paying for… Delivering … Care. What does #CareConvergence mean to you? https://lnkd.in/dhtSs-Qa

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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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"Innovation in healthcare is not just about the tools we build, but the lives we change." Truly excited to be giving a #TechTalk at the Clinical Data Management and Innovation Conference! It's incredible to witness how recent advancements have transformed the landscape of #ClinicalTrials and #HealthCareResearch. Here are some of the recent trends transforming the industry: 🔹 AI & Machine Learning: These technologies are reshaping clinical data management by automating tasks like data cleaning, identifying patterns in vast datasets, and assisting with participant recruitment through Natural Language Processing (NLP). 🔹 Integrated Data Management Platforms: The move towards centralized systems is streamlining everything from data capture to reporting, enhancing efficiency and data quality across the board. 🔹 Real-World Data (RWD) & Evidence (RWE): Incorporating data from wearables and other digital health tools bridges the gap between controlled trial environments and real-life patient experiences. 🔹 Decentralized Trials & Telemedicine: By enabling remote participation, these models increase patient access and improve retention, especially for underrepresented groups. 🔹 Risk-Based Monitoring (RBM): Strategic monitoring of high-risk data points optimizes trial management, enhancing speed and data accuracy. 🔹 Wearable Tech & Data Security: Wearables are revolutionizing data collection, while an increased emphasis on data privacy protects sensitive clinical information. It's exciting to be at the forefront of such transformative changes, speeding up research and improving patient outcomes. The future of #ClinicalResearch is brighter than ever! 🌟 #Innovation #DataManagement #ArtificialIntelligence #AIinHealthcare #RWE #RWD #Realworddata #realworkevidence #PrecisionMedicine #HealthTech #DataScience #ClinicalTrials #Innovation #PatientCentricity #AI #DataStewardship #Leadership #Biopharma Agility Pharmaceuticals Arena International Events Group American Association for Precision Medicine (AAPM) #aapmhealth #aapm_health WISE World Investors & Entrepreneurs Society #drugdiscovery #drugdevelopment #clinicaldata #ai #news

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"The future of healthcare is not just treating disease but preventing it before it begins." We are witnessing a commendable shift in healthcare as AI transforms medical research and clinical practice by uncovering intricate data patterns that predict disease progression and treatment outcomes at an individual level. This move from conventional, generalized treatment approaches to personalized medicine marks a significant milestone in pursuing tailored, effective patient care. Ways AI is Enhancing Precision Medicine: AI and machine learning algorithms can process vast amounts of multidimensional data, including Genomic information, Clinical records, Imaging results, and Lifestyle factors. Environmental exposures: This ability to analyze and cross-reference complex datasets leads to groundbreaking advancements in diagnosing conditions and creating tailored treatment plans that humans might not readily identify. Key Applications of AI in Precision Medicine 1. Early Disease Detection: AI-powered tools are making waves in early disease detection, especially in cancer screening. For instance, advanced algorithms analyzing mammograms have shown impressive accuracy in detecting breast cancer, significantly reducing the rate of missed diagnoses. 2. Pharmacogenomics: AI plays a pivotal role in genome-informed prescribing, which predicts the most effective medications and dosages based on a patient's genetic profile. This ensures treatments are not only more effective but also safer. 3. Treatment Planning: By integrating multi-omic data with clinical and digital health metrics, AI enhances personalized diagnosis and treatment planning, allowing for highly specific, patient-centric care. 4. Clinical Trial Design: AI also optimizes clinical trial processes by streamlining participant selection and predicting outcomes tailored to individual characteristics, making trials faster and more efficient. Challenges and Future Directions: While the potential of AI in precision medicine is undeniable, challenges remain, including - Ensuring data privacy and security - Mitigating biases within AI algorithms - Seamlessly integrating AI into clinical workflows - Educating healthcare professionals on AI applications Addressing these issues will be key to unlocking AI's full potential in transforming healthcare. As these challenges are overcome, we can anticipate an era where treatments are as unique as the patients. 🚀 #PrecisionMedicine #HealthcareInnovation #AI #FutureOfHealth #PersonalizedMedicine #HLTH2024 #DigitalHealth #HealthInnovation #HealthEquity #LongevityScience #HealthTech #WellnessRevolution #HealthcareTransformation #MedTech #PatientCenteredCare #FutureOfWellness #HealthData #LifeSciencesInnovation Agility Pharmaceuticals American Association for Precision Medicine (AAPM) #AAPMhealth #AAPM_Health

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Here’s your recap of last week’s health IT news 🗞️ 👇 🤖 AI Clinician Assistant • Suki is partnering with Zoom to generate clinical notes as well as other integrated AI features.    • Net Health announced it would integrate AI ambient scribe Tali AI. • Aidoc is partnering with NVIDIA to create a guideline to accelerate AI adoption, the Blueprint for Resilient Integration and Deployment of Guided Excellence (BRIDGE). 📞 AI Contact Center • Authenticx released a new AI assistant that helps users uncover business insights from their data. • Infinitus Systems, Inc. closed a $51.5M Series C with participation from Memorial Hermann Health System and others.   🏥 AI Facility Management • Cognosos, Inc. acquired Cox Prosight. 🌡️ AI Remote Patient Monitoring and Triage • Biofourmis has merged with CopilotIQ. 📈 Data & Analytics • Avandra Imaging launched out of stealth; it plans to sell to biopharma, medical research, and AI companies. • Gradient Health acquired DataAppraisal. • HealthEx launched and announced $14M in Seed and Series A funding. 📋 Patient Administration • Notable released Flow Builder, which allows users to develop their own AI agents for operational workflows within EHRs and other systems. • MIla Health Inc released its flagship AI solution of the same name, and announced implementations at provider organizations including Aayu Clinic, MIMIT Health, and Best Practices Inpatient Care. 🔁 RCM • Oracle’s patient accounting solution has been integrated with FinThrive, which enables improved functionality, performance, and a unified login experience. • Blue Shield of California and Salesforce are partnering on a solution that promises to give patients prior auth responses within the course of their appointment. ⚙️ Clinical Operations • Dyania Health closed a $10M Series A, including participation from Cleveland Clinic Ventures. 📱 Patient Support & Communications • Psych Hub released a new solution designed to support patients seeking mental health support, directing them to both non-clinical and clinical resources, thereby assisting behavioral health providers to reach new patients. • Mayo Clinic has partnered with Lin Health to support patients after treatment for fibromyalgia.   🍎 VBC • WellSky acquired Bonafide Health, allowing it to provide a more integrated platform for providers to run their businesses. 🧠 Food For Thought • 𝗦𝘁𝗿𝘂𝗴𝗴𝗹𝗶𝗻𝗴 𝘁𝗼 𝗸𝗲𝗲𝗽 𝘂𝗽 𝘄𝗶𝘁𝗵 𝗮𝗹𝗹 𝘁𝗵𝗲 𝗔𝗜 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀? Andrew Hines, CTO at Canvas Medical, shared a breakdown (plus some hot takes) on all of the many entities currently vying for market share in the AI governance space https://lnkd.in/eMNpXw4t --- Want the latest healthcare tech news delivered to your inbox each week? Sign up here 📬 👉 https://lnkd.in/e2UJ3ckP

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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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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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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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Come join Right Triangle’s Director of Healthcare Analytics & Integration, Cindy Lou Vogel at the 𝐑𝐞𝐠𝐢𝐨𝐧𝐚𝐥 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐅𝐨𝐫𝐮𝐦: 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐚𝐧𝐝 𝐇𝐞𝐚𝐥𝐭𝐡 𝐚𝐧𝐝 𝐇𝐞𝐚𝐥𝐭𝐡 𝐂𝐚𝐫𝐞 - a panel discussion on the intersection of AI and health care with an eye toward public health. Event Overview: The use of artificial intelligence (AI) has increased dramatically over the past few years, through standalone tools like ChatGPT and built-in AI assistants in all of our familiar platforms like Zoom and Microsoft 365. There are significant opportunities and challenges with using AI in our work in public health and health care. Panelists will share knowledge, ideas, examples and ethical considerations when thinking about AI in the context of public health and health care with areas of expertise including ethical use of AI, training community health workers, managing a federally qualified health center (FQHC) and health care analytics and integration. This is not a roadmap to the implementation of AI in your health department or healthcare facility but instead an exploration of the use of AI for non-technical members of the health and health care world with a public sector consideration. Panelists include: - Lindsey Jarrett, PhD, Vice President, Ethical AI Services, Center for Practical Bioethics - Hannayd Ruiz, Community Health Project Manager, Mid-America Regional Council - Patrick Sallee, President and CEO, Vibrant Health - Cindy Lou Vogel, Director, Healthcare Analytics and Integration, Right Triangle Consulting Free Registration: https://lnkd.in/g3gvigWd #DataGovernance #AIGovernance #Healthcare

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Digital Health: Countervailing Forces… Consider this: over the past five years nearly $78 billion has been invested in digital health companies and yet just this past year over 20 million Americans were taken off the Medicaid rolls. Certain policy changes can be very damaging, to say nothing of other human-induced factors like pollution, climate change, wars, inadequate housing and education, and hunger which have staggering implications on health. At times it can feel like bailing water out of a sinking ship.    The overall venture capital activity in 1Q24 was a relatively muted $36.6 billion across 2,882 companies for an average round size of $12.7 million, as compared to $51.6 billion and 4,026 companies in 1Q23. Notwithstanding that the level of investment activity in the healthcare technology sector has receded from the $30 billion highwater mark in 2021 to a more manageable $10 – $12 billion annual pace, the opportunities to “transform the business of healthcare” remain obvious and acute. Arguably, the 2021 hangover still lingers in the healthcare technology sector as companies that raised too much capital at too high a price work to sort out challenging cap tables. Out of the 2021 mosh pit of too many companies, it appears that the sector is in an “Emerging Winners” phase that will drive companies with narrow and/or incomplete offerings to combine or shut down.   Thoughts on what to expect for the remainder of the year… https://lnkd.in/egy7Afhg Flare Capital Partners #digitalhealth

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Blueprint really is THE platform for mental health therapists. Not only does it give time back to practitioners but also helps them deliver even better care through data-driven insights. And Danny Freed’s personal story on why he started Blueprint is becoming a reality with Blueprint 2.0

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The defining factor isn't the size of the company or startup, but the vision behind it. Take OpenAI, for instance. Until last year, unless you were deeply embedded in the ML world as a computer scientist/researcher, or enthusiast, you might not have heard of OpenAI. Meanwhile, a giant like Google was dominating the scene. However, a few years back, OpenAI was just another small startup. Now, it's rapidly evolving into a major player in big tech. Why and how? It comes down to having a long-term vision, a clear roadmap, patience, and solid execution (i.e., talents). Even in the context of healthcare AI, where (small) startups face many challenges (including the ones mentioned), the principles of vision and strategy apply. While merging with big tech might seem like an option for some, if a startup truly believes in its vision and has a well-defined path to achieve it, it should forge ahead independently. The landscape is evolving, and like OpenAI, today’s small startups with clear, visionary goals could be tomorrow's industry leaders. #starup #founders #openai #google #healthcare

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