Jayson Sterba, 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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Do you ever wonder why health technology and therapy consumers make the decisions they do? I'm eager to hear how Roundpeg Consulting, LLC has leveraged MRI-Simmons' consumer insights to provide value to organizations and leaders across various sectors of healthcare. #Healthcare #B2C #Leaders #Consumer #HealthTechnology

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AI has made good design more important than ever in healthcare. Why? Model performance alone doesn't guarantee clinical or financial value. A model can deliver a robust insight/output (accurate, reliable, complete, etc.), but clinician-users may struggle to use or integrate it in a real-world setting. As healthcare AI systems become compound machines, these design challenges amplify. Here are two simple examples: • AI systems that do not integrate seamlessly into EHRs, PACS, or pathology viewers may drive differential rates of utilization/adoption across sites, privileging some patients to a given algorithm without an underlying clinical rationale. • Imagine a model recommending a "next best step in care" that is not provided at a given hospital (e.g., due to lacking resources or infrastructure). Contextual and human factors can have a greater influence on whether the value of an AI intervention is realized, even when in silico model performance is compelling. There are two near-term opportunities here: 1) Healthcare AI model benchmarking should encompass "end-to-end systems," capturing nuances around system design, user experience, workflow integration, and ease of adoption. 2) It's time for AI-first design in healthcare – made possible by revisiting the unique capabilities of AI systems and their emergent behaviors to interrogate what new user experiences are possible. What are your favorite examples of AI-first design? #healthcare #ai #artificialintelligence #generativeai

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We're witnessing the next wave of leading companies being within healthcare services & being more "involved" than just writing good code. 🌊 I fundamentally believe it's equally important, understanding on the highest granularity, how healthcare is delivered at the core (in the clinics, hospitals & with doctors). A couple years ago there was a massive focus on digital health, this has shifted to healthcare services, experiencing exponential growth atm, due to the following. 📈 1. Operating within the very heterogenous market of healthcare (in particular primary care) requires to understand and interpret operational nuances (those closest to the problem/market will win) and solve for those very operational topics 🩸 2. Pain to innovate is highest amongst those delivering care, as there is no "continuing as before" (patients jump between services/providers based on availability, that's why digital health only takes off v slowly), doctors can't transition away but are "stuck" with their daily operational problems 😵‍💫 3. Willingness to pay is present, (see point 2.) and doctors can afford to pay for these services (shift from paying for "non-available" staff to software) and lastly it's the largest market (DACH €+550B primary care spend) with everyone being a user at one point, opening up multiple cross revenue streams 💸 4. No payor/insurance fights but a "simple" B2B customer (non of the DTx/reimbursement complexities) and a market with unparalleled retention rates (check CompuGroup revenues over the past 10 years, €1.2B in 2023) ⚔️ 5. Less regulation and increasing emphasis/relaxation on data usage (check Patient Data Protection Act or European Health Data Space) as well as enforced digitalisation throughout the upcoming years (every restaurant needs a modern POS, whilst doctors can still operate pen & paper...) ⚖️ Personally I am very bullish, that within the next 5 years, we'll see the N26/Revolut transformation happening in European healthcare - no flying cars - just better operations, services & experiences on top of existing core medical services. 💯 Thanks for the Eterno Health mention Thomas Hagemeijer - V cool overview! 🙌🏽

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David Blumenthal at the World Medical Innovation Forum shared some great insights about how generative AI will need to be regulated in order to prove helpful — “The knowledge we need to manage this technology is insufficient. What are the standards to measure this against? Need a foundational science to rate the quality of generative AI models. This is a government issue, it will require funding, and consensus development. The performance metrics and standards will need to be transparent. We will also need a platform for privacy performance. This is a novel form of intelligence with applications to healthcare. — Can you regulate intelligence? — Can we train it, apprentice it, can we test it, can we certify it, can we monitor it?” Trustworthy Technology and Innovation in Healthcare Book Series Consortium (TTIC) Sherri Douville Ed Gaudet Charles Podesta Shaun E. Garcia Joshua Tamayo-Sarver, MD, PhD, FACEP, FAMIA Thanks to Mary Aggarwal, Vinay Aggarwal, MD, MPH, and Bank of America Private Bank for the learning opportunity!

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Interesting to see that digital health funding is relatively stable. Only a couple of exits. I think we'll see more deals like DarioHealth's acquisition of Twill, since from a sales perspective, the narrower the solution, the more difficult it is to acquire customers. This difficulty has nothing to do with the quality of offerings, but with the data management and administrative complexity on the customer side.

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Healthcare AI is having its moment, with an explosion of new entrants and exceptionally high market demand for solutions from established incumbents. We are seeing this play out in the startup ecosystem and across boardrooms at Fortune 500 companies, as CEOs from within the industry and outside are eyeing healthcare AI as an immense market opportunity — from Big Tech and Big Pharma, to the very institutions that are responsible for our own care.

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Newest episode of #HealthAndVeritas with guest, Mitesh Rao, MD, CEO of OMNY Health talking about democratizing access to healthcare data and improving health through more reliable information. Harlan Krumholz talks about "The business case for quality: estimating lives saved and harms avoided in a value-based purchasing model" an article in Health Affairs Scholar that returns us to the uncomfortable domain of asking why our "system" doesn't do more to save lives and improve health outcomes. I talk about Marijuana. I am concerned that we are watching a slow moving catastrophe due to the desire to decriminalize and reduce controls over Cannabis and THC-containing products (which is good) while paying too little attention to quality and regulations. Listen to the pod and tell me what YOU think. And please post your comments, tell a friend, and rate and review us on your favorite podcast app. Yale School of Management Yale School of Public Health Yale School of Medicine https://lnkd.in/ezj8qVqy

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Here’s your recap of last week’s health IT news 🗞️ 👇 🤖 AI Products • Emergency Services, Inc. + Augmedix Go ED: The emergency medicine group adopted the new ED-specific AI ambient scribe solution.    • Color + OpenAI: The cancer care tech company partnered with the GenAI giant to build a AI clinical decision support copilot.    • AKASA Medical Coding: The AI RCM vendor known for its AI prior auth tool AKASA Authorization Advisor released a new GenAI medical coding solution.    • Humata Health: The AI prior auth for providers vendor closed a $25M funding round led by healthcare org-backed funds The Blue Venture Fund and LRVHealth.    • Wellsheet + Concord Hospital Health System: The AI-enabled Smart EHR UI solution announced a client-reported 16.3% reduction in length of stay and 40% decrease in time spent in the EHR via its partnership with Concord Health, as well as the release of its new LLM-generated handoff summary feature. 🍎 VBC • BSIM Healthcare Services + Innovaccer: The healthcare provider—embarking on its first VBC contract—adopted the pop health data platform for analytics. 🩼 Durable Medical Equipment • Parachute Health: The DME e-prescribing and ordering solution released an update that integrates prior authorization. ⚕️Clinical Staffing • Matchwell + Indiana Hospital Association: The clinical staffing service partnered with the hospital member org to create the first state-wide resource pool for temp staffing. 🧑‍💻 Virtual and At-Home Care • Deaconess Health System + KeyCare: The Indiana-based health system adopted the Epic-based virtual care provider for around-the-clock virtual urgent care.    • UC Davis Health + Current Health: The health system launched a new RPM program for high blood pressure in partnership with Best Buy Health’s care-at-home platform. 🧠 Food for Thought: We came across a couple of good resources this past week on the current state of healthcare data information exchange: • This article in Health Affairs from Deven McGraw and Tina Grande provides a comprehensive overview of some of the patient health data abuses we've seen come to light in recent months, as well as a number of policy recommendations to improve the health information exchange landscape for all participants. https://lnkd.in/e_GEQ-JJ  (h/t Alya Sulaiman)    • This episode of Health Gorilla's InteropTalk gives a helpful update on the current state of affairs, with a particular focus on the state of trust across the health data exchange community and how the definition of "Treatment" may evolve. https://lnkd.in/e96AJG-5 (h/t Brendan Keeler) --- Reminder: you can sign up for the Elion Briefing to get the latest healthcare tech news delivered to your inbox each week 📬 👉 https://lnkd.in/e2UJ3ckP

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𝗖𝘆𝗯𝗲𝗿𝗰𝗵𝗼𝗻𝗱𝗿𝗶𝗮: ChatGPT has a far-reaching impact on 𝘩𝘺𝘱𝘰𝘤𝘩𝘰𝘯𝘥𝘳𝘪𝘢𝘤 𝘵𝘦𝘯𝘥𝘦𝘯𝘤𝘪𝘦𝘴. 1️⃣ 𝗔 𝗱𝗼𝘂𝗯𝗹𝗲-𝗲𝗱𝗴𝗲𝗱 𝘀𝘄𝗼𝗿𝗱: Instant access to massive information can 𝘦𝘹𝘢𝘤𝘦𝘳𝘣𝘢𝘵𝘦 𝘸𝘰𝘳𝘳𝘪𝘦𝘴. 2️⃣ 𝗗𝗮𝗻𝗴𝗲𝗿𝘀 𝗼𝗳 𝘀𝗲𝗹𝗳-𝗱𝗶𝗮𝗴𝗻𝗼𝘀𝗶𝘀: AI tools enable users to input symptoms and receive diagnosis leading to 𝘮𝘪𝘴𝘪𝘯𝘵𝘦𝘳𝘱𝘳𝘦𝘵𝘢𝘵𝘪𝘰𝘯 𝘢𝘯𝘥 𝘢𝘯𝘹𝘪𝘦𝘵𝘺. 3️⃣ 𝗠𝗶𝘀𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻, 𝗵𝗮𝗹𝗹𝘂𝗰𝗶𝗻𝗮𝘁𝗶𝗼𝗻𝘀: Information, presented in a convincing manner: spell-checked, grammatically perfect, logically organised, yet wildly inaccurate. 4️⃣ 𝗧𝗵𝗲 𝗽𝗹𝘂𝘀 𝘀𝗶𝗱𝗲: Easy access to health information can be reassuring when answering questions. 5️⃣ 𝗦𝘁𝗶𝗴𝗺𝗮 𝗿𝗲𝗱𝘂𝗰𝘁𝗶𝗼𝗻: AI interactions are impersonal and private, which may reduce the stigma associated with seeking help and encourage more people to seek support discreetly. ➡️ Please subscribe to {ℙ}𝕣𝕖𝕤𝕔𝕣𝕚𝕡𝕥𝕚𝕠𝕟 - 𝗠𝘆 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿 𝗼𝗻 𝗵𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲, 𝘄𝗲𝗹𝗹𝗻𝗲𝘀𝘀 𝗮𝗻𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 - 𝘏𝘢𝘯𝘥 𝘤𝘳𝘢𝘧𝘵𝘦𝘥 𝘰𝘱𝘪𝘯𝘪𝘰𝘯𝘴 𝘰𝘯 𝘩𝘢𝘯𝘥 𝘱𝘪𝘤𝘬𝘦𝘥 𝘪𝘯𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯 || https://lnkd.in/gvr5kfEM 

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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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Equitable access to healthcare AI is essential to ensure that technological advancements benefit ALL, not just the privileged. Healthcare disparities are already persistent, and AI has the potential to either eliminate or exacerbate those disparities depending on our actions. If access to AI remains uneven, these disparities could worsen, potentially leading to significant differences in patient outcomes and overall public health. Addressing this will require comprehensive, consistent collaboration! #HealthEquity #AI #Healthcare

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AI is changing the game in healthcare. A quarter of VC investments in healthcare tech are projected to be AI-related solutions; plus, the US AI healthcare market is projected to receive $11.1 billion in 2024, up from $7.2 billion in 2023. AI isn't just a trend; it's transforming efficiency, boosting patient outcomes, and aiding drug discovery. The stats back it up. 84% of global healthcare leaders believe AI-driven automation can save clinicians' time by reducing administrative burdens, while 88% think it can help alleviate workforce shortages. The convergence of AI and healthcare is not just a promising development; it is essential for the future of value-based care. The potential impact on patient journeys, cost reduction, and overall healthcare delivery could be profound. #HealthcareInnovation #AI #DigitalHealth

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🚀 Innovate for Impact, Not Hype Too many healthtech startups are dazzled by the latest technology trends. But real success comes from driving value-based outcomes. Here’s your roadmap: 🔍 Enhance Patient Outcomes 💰 Cut Down Healthcare Costs ⚙️ Boost Operational Efficiency Funding and contracts don’t come from flashy features—they come from proven results. Focus on what truly matters to your end users and stakeholders. 💡 Make value the core of your innovation strategy. #Healthtech #ValueBasedOutcomes #HealthcareInnovation #Efficiency #Innovation #Health

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Exciting to see CodaMetrix named as one of Boston's top startups to watch in 2024! The administrative burden on physicians has grown tremendously, leaving less time for providers to dedicate to patient care. CodaMetrix helps solve that problem with their AI-powered solutions, allowing the providers to focus on their patients and giving the coders technology that helps them focus their expertise on complicated cases. #medicalcoding #AI #healthcare #transforminghealthcare

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🗣️ Unlocking the Potential of #SemanticInteroperability in Healthcare In the world of healthcare, #dataInteroperability isn’t just a technical problem—it’s a deeply semantic one. Eric Pan was kind enough to share an essay with me, titled Data Mappings as Poetry, that captures why semantics in health data is so critical yet often overlooked. 🔑 Why semantics matter: Semantics bridges the gap between raw data and meaningful insights. It’s the key to ensuring that advanced technologies—like AI and machine learning—can deliver reliable and impactful outcomes in healthcare. Yet, semantic interoperability is frequently treated as “data plumbing,” an unglamorous task done begrudgingly. It's seen as a chore. 🚧 The challenge: Addressing semantics requires more than just technical expertise. It demands interdisciplinary collaboration between engineers, data scientists, clinicians, product teams and users. Unfortunately, this nuanced work often gets overshadowed by the allure of more high-profile “white-collar” tech challenges. 🌟 What’s at stake: If we properly address semantics in health data, we unlock the full potential of advanced technologies—enabling smart and meaningful systems that genuinely improve patient care, and foster seamless collaboration across the healthcare ecosystem. 💡 Eric Pan’s essay is a call to action for us to view data mapping not as a mundane task but as an art form—a collaborative, empathetic effort that brings elegance and purpose to healthcare technology. It’s a vision that aligns interdisciplinary teams and celebrates the critical role of semantic interoperability in creating a connected healthcare future. Read Eric Pan’s essay here: https://lnkd.in/dCJsUDVB #HealthcareInnovation #DataInteroperability #SemanticInteroperability #HealthTech #ArtificialIntelligence #MachineLearning #DigitalHealth #DataMapping #InterdisciplinaryCollaboration #HealthCareTransformation

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🔍 Groundbreaking research reveals how healthcare's biggest players are actually implementing AI - insights from 63 C-suite leaders at top payers and providers. Define Ventures' comprehensive study, interviewing leaders from 10 of the top 20 providers and 5 of the top 10 payers, uncovers a pragmatic yet ambitious approach to AI adoption. Key findings: - 53% of leaders consider AI an immediate priority, with 73% increasing their financial commitments. - 76% are establishing programs involving AI pilots - For AI adoption, healthcare orgs are progressing with 3 distinct phases: Laying Groundwork, Test & Iterate, and All In. 2. ROI Focus: 54% believe AI's biggest near-term impact will be on patient and clinician experience. Leaders are prioritizing "soft ROI" early wins over hard financial metrics to build organizational confidence. 3. Use Case Priorities: - 83% of providers prioritize clinical documentation/ambient scribing - 68% of payers focus on member experience enhancement - Most organizations taking a "portfolio approach" mixing quick wins with strategic priorities 4. Build vs Buy Reality: 72% lean on external partners for applications, while 69% rely on external vendors for LLMs. However, 40% are investing in internal data infrastructure capabilities. The report's roadmap: Balance pragmatic implementation with strategic vision, focus on operational efficiency first, and build strong governance frameworks (73% have already established AI governance committees). 🔗 Read the survey: https://lnkd.in/g-kKRMhN #DigitalHealth #HealthTech #AIStrategy image: Define Ventures (above link)

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Michael Seibel makes a great point about facing your fear.   For MedTech founders and CEOs, patient safety comes first!   A product in healthcare holds higher quality standards, which need to be maintained from the get-go while building your startup.   Here are some tips on taking the challenges head-on:   ✅ Prioritize user feedback: Engage healthcare professionals early during the development phase.   ✅ Engage with potential customers: These conversations provide crucial market insights.   ✅ Tackle complex tasks head-on: Deffering challenges to focus on your daily to-do list is not a great idea.   ✅ No shortcuts: Prioritize matters that can impact the safety and efficacy of the product.   ✅ Taking the core design challenges head-on often leads to more robust solutions.   Innovation means you don't have all the answers, but every decision matters, which leads to a safer product. Uncomfortable tasks often signal important areas for growth.   Face your fears head-on!   ——— ♻️ Repost this if someone needs to hear this!   🔔 Follow Golddy Kaur for daily posts   👇 Share your thoughts     📹VC YT: @EO

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