Yan Chow, MD, MBA

This isn't a post about #AI, but about data foundation and #interoperability in #healthcare. The demonstration of AI through #LLM is not sexiest part of this presentation. There's no silver bullet, we should know that at this point. Instead, I draw your attention to the rich discussion around the applicability of #OpenEHR and #HL7 #FHIR standards, and the importance of understanding why each of these #standards was developed and what for. Data definitions, data schemas, and how we apply standards to structure and represent information, both in storage and transportation, are key. Any further comments from me would be spoilers. I hope you enjoy the presentation and share your point of view, folks. Have a great week!

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To follow up on Dede Ainbinder recent post: If we use the current EHR data to build a AI clinical decision support tool it is unlikely to capture our clinical decision making process. EHR's are inherently designed to maximize billing and minimize risk of litigation. A clinical decision support tool based on this data will likely do the same. There is a large sunken cost fallacy here where we continue to hang on to garbage data. Just because the data gathering and storage process was capital and time intensive doesnt mean the data is valuable. To truly capture the clinical decision process we need to capture data which sits outside billing and litigation. Its hard to imagine a future where this data isnt used for billing and cannot be called upon during litigation. #EHR #healthdata #clinicaldecision

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Key trends and takeaways from HLTH 2024: 1. AI's Evolving Role: AI dominated discussions, with executives acknowledging its potential while also recognizing challenges in accuracy and clinician trust. There's a shift towards focusing on the practical applications of AI, with a call for partnerships to ensure reliable testing and implementation. 2. Infrastructure Focus: Beyond the glitzy AI tools, there's a growing emphasis on the "picks and shovels" needed for healthcare data accessibility, including infrastructure, compliance, and interoperability. Executives believe that improving data flow will facilitate the effective use of AI. 3. Middlemen Under Scrutiny: Pharmacy benefits managers (PBMs) faced criticism for their role in rising drug costs, with discussions highlighting misaligned incentives and the need for transparency in healthcare pricing. 4. Women's Health Spotlight: Women's health initiatives gained attention, particularly following government funding announcements and personal stories shared by advocates. However, investment in women's health remains minimal compared to overall healthcare funding. 5. Interest in Psychedelic Medicine: The potential of psychedelics for treating mental health conditions garnered significant interest, with discussions about funding and research moving forward, especially within the Veterans Affairs system. Executive Takeaways: Leaders from various sectors emphasized the importance of consumer-focused strategies, collaboration, and the need for responsible AI usage. There was a consensus on the critical role of addressing healthcare accessibility, improving patient experiences, and fostering innovations that genuinely enhance care delivery.

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Healthcare technology is in trouble. After the relative boom time we experienced through during the pandemic, the fervor to innovate in health systems and payers seems to have dried up. While organizations continue to post stellar earnings, they also continue to lay off experienced health technology people en masse. Why? I think it's time for a bit of honest reflection. 70% of all enterprise healthcare technology projects fail. 17% of of all large scale IT projects go so badly that they threaten the very existence of the company itself. Bridging Business & IT, LLC For projects with a total price tag of over $1MM, that failure rate jumps to over 90%. And the ever prescient Clayton Christensen believed that the failure rate for all new product introductions is 95%. This is not new information. What is new is the most recent E&Y Pulse Survey that has health system CIOs believing that 7 in 10 of their healthcare IT projects have had no discernible #ROI. None. And this is for the projects that didn't fail. https://lnkd.in/gRgVt_Xs This is an existential crisis that health technology must face honestly and soberly. Lack of planning and poor communication are the core culprits. Clunky and outdated Waterfall project methodologies can be blamed for many of these failures. And frankly Agile disciples could use a bit more planning before they start iterating so they know what they're building. There are, however, some problem actors and business models that need to be called out. The historically biggest culprits, in my humble opinion, are large, institutional, enterprise software vendors and their server-based architectures. For decades they feasted on seven figure licensing deals, sometimes humble-bragging to potential implementation partners about 5:1 or 7:1 implementation cost to license cost ratios. Companies just went along with it, because no one gets fired for buying IBM, right? But the failures in this segment are legendary. And many have indeed been a key cause in the parent company failure. As for the ROI, there was a bright spot in the E&Y Pulse Survey. Despite not having established a demonstrable ROI, 96% of them still wanted to move forward with the projects, believed the investment was worth it. So the issue isn't necessarily that the projects aren't generating value, the issue is that the organizations (and their vendors) didn't do a good job up front validating agreed upon ROI metrics and measures. They don’t fully understand the value it is (or isn't) creating. This is our collective job to be better at this. So what can we do to reduce the failure rate and get health systems and payers back into investing in #innovation? #ROI #startups #valueengineering #goldenpath #LCNC #opensource

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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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After a brief writing hiatus… Part III of “Who Pays for Healthcare AI” is live. The third installment defines five performance-based pricing models for healthcare AI and explores: • Four types of Return on Investment (ROI) in healthcare and life sciences • The importance of shielding at-risk pricing models from operational externalities • How better pricing model design can mitigate negative working capital risk under performance-based models • Taming the beast: attribution Check out Part III below, and subscribe to receive the final post of the series! https://lnkd.in/dPZSHMiy

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With $8.2B invested into digital health so far, 2024 is shaping up to be a $10-12B annualized investment year. This would make funding comparable to 2023. I suspect with continued venture investment, boards will require exits. One thing I’m particularly interested in is terms of recent acquisitions and growth equity rounds. What type of downside protection (e.g., structure) is not disclosed to media that protects the investor? Will funds who have specifically raised capital to buy stakes in VC-backed companies at significant discounts? And what revenue/EBITDA multiples are looking like for M&A in 2024/2025? Every founder has to spin their story in a positive light when speaking to media. I know this because PR agencies reach out to me about their clients (p.s. I don’t consider myself a member of the media). The private health tech market feels like it could significantly rip or drop in the next 12-24 months. Therefore, my general advice to early-stage founders is to assume you will not raise capital beyond your seed round. If the investor market heats up in 2025, you will have the option to raise a series A at that time if you’ve built a strong business. If you’ve already raised series c or beyond, then one of your goals will be to time the exit (M&A or IPO) appropriately so that you garner an attractive multiple. There are few private health tech startups that have founder board control, can reinvest positive cash flows, and stay private forever. So by necessity of the structure, exits are desired. - - - - Image Credit: Rock Health

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As we move through 2024, the digital health landscape is undergoing a remarkable transformation. Here are the top trends that are defining the industry, and how Remote Patient Monitoring (RPM) and Chronic Care Management (CCM) technologies are driving these changes: 1️⃣ : AGI's Advancements in Healthcare • AGI plays a key role in drug development to cost optimization. • RPM and CCM leverage AI/ML to process patient data • AI governance in CCM ensures transparency and addresses ethical concerns. 2️⃣ : Accelerating Data Interoperability • RPM and CCM enable unified patient records and advanced analytics. • Supports data exchange and meaningful insights across systems. 3️⃣ : Retailers as Healthcare Providers • Retail clinics are expanding into chronic disease management. • RPM and telehealth extend retailers' reach as healthcare providers. • CCM platforms integrate care pathways across settings. 4️⃣ : Digital Obesity Care and Personalization • RPM monitors lifestyle factors for a holistic obesity care approach. • CCM integrates personalized behavioral interventions for weight management. 5️⃣ : Nutritional Interventions in Healthcare • RPM tracks nutritional habits, providing insights for food-as-medicine. • CCM incorporates personalized dietary plans into care plans. 6️⃣ : Mental Health and Well-Being Solutions • RPM enables remote monitoring of mental health, enabling timely interventions. • CCM seamlessly integrates mental health support into chronic care. 7️⃣ : Women's Health Takes Center Stage • CCM allows personalized care plans and data-driven insights for women's health. • RPM provides valuable data to support women's healthcare decision-making. 8️⃣ : GenAI's Growing Role Across Healthcare - RPM and CCM facilitate GenAI integration, from diagnostics to treatment. - GenAI algorithms enhance clinical decision support. 9️⃣ : Convergence of Wearables and At-Home Devices - RPM enables continuous monitoring of vitals and chronic conditions through wearables. - RPM fosters increased patient engagement and active participation in care. Are you ready to transform your connected care offerings and stay ahead of the digital health curve? DM us now!!

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As the discourse shifts from models to compound AI systems / agents, we need better AI benchmarks to evaluate multi-modal and multi-step task performance, especially in healthcare and life sciences. When we wrote the first paper demonstrating ChatGPT's performance on the USMLE, we chose the US Medical Licensing Exam as a benchmark for accessibility, speed, and ease. This benchmark was never intended to represent AI model performance on real-world clinical tasks. Today, I still see so many research teams and startups using benchmarks (like the USMLE) that are ill-fitted for assessing the true clinical or scientific performance and utility of the models they are developing for real-world contexts. Benchmark development may be seen as a "less sexy" area of research, but it is of paramount importance. Years after the rise of the transformer, we still lack adequate benchmarks for so many single-step tasks in biomedicine. With compound AI systems (i.e., architectures that integrate multiple AI models to perform complex tasks) emerging, we need new benchmarks for agentic behaviors. I'd argue that developing an agent with novel capabilities without at least proposing a companion benchmark (if an industry standard does not yet exist) may hinder the adoption of said agent, especially for high-stakes workflows. Designing more benchmarks that capture/simulate real-world clinical and scientific workflows will help us mitigate the major discrepancies observed between in silico and in vivo performance and better support safe + effective deployment of AI in biomedicine. There are already brilliant people focused here, and we need more. DMs are open if you're researching or working in this area of multi-step/multi-modal benchmarking in healthcare and life sciences! #healthcare #ai #artificialintelligence #generativeai

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A Timely Boost to Accelerate Universal Health Coverage Goals! We are thrilled to announce that Qure.ai's recent $65 million Series D funding marks a pivotal moment in our journey to revolutionize global healthcare. This boost in resources will empower us to expand our global footprint, enhance our product portfolio, and deliver more affordable, high-quality healthcare to underserved communities. Aligned with the Universal Health Coverage (UHC) goals, Qure.ai remains committed to decentralizing care, ensuring it’s accessible and close to the communities that need it most. Our unique blend of AI innovation, strategic business acumen, and deep clinical expertise positions us to tackle some of the most pressing global health challenges. We extend our heartfelt thanks to our investors, partners, and our exceptional team for their unwavering support and belief in our mission. Together, we will continue to impact lives globally, ensuring that cutting-edge, AI-driven healthcare solutions reach those who need them most. PATH Digital Square at PATH FIND FHI 360 Management Sciences for Health KNCV TB Plus Stop TB Partnership Private Sector Constituency to Stop TB Partnership TBPPM Learning Network TBPPM Learning Network USAID World Health Organization Ministry of Health and Family Welfare, Government of India MeitY Startup Hub Startup India URC Elizabeth Glaser Pediatric AIDS Foundation Ministry of Electronics and Information Technology The Rockefeller Foundation Bill & Melinda Gates Foundation The Global Fund Friends of the Global Fight Against AIDS, Tuberculosis and Malaria India Health Fund JSI Clinton Health Access Initiative, Inc. Jhpiego

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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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🌟 Generative AI and Healthcare Transformation: A New Era of Innovation 🌟 I am constantly asked about #AI applications for healthcare transformation. I continue to take people back to the pain points or problems being solved. The healthcare industry is undergoing a significant transformation, driven by the integration of generative AI. This revolutionary technology is currently reshaping the way we approach care management, early disease detection, and administrative tasks. Early Benefits of Generative AI: Enhanced Care Management: AI serves as a "co-pilot" for healthcare professionals, assisting in managing patient care more efficiently and accurately. This leads to improved patient outcomes and more personalized care plans. Early Disease Detection: AI's ability to analyze vast amounts of unstructured data enables early identification of diseases, potentially saving lives and reducing healthcare costs. It's a game-changer in preventive healthcare. Reducing Clinician Burnout: By automating repetitive administrative tasks, AI allows clinicians to focus more on patient care. This not only improves job satisfaction but also enhances the quality of care provided. Affordability and Efficiency: AI-driven processes streamline operations, making healthcare more affordable and accessible. From optimizing workflows to reducing operational costs, AI is paving the way for a more sustainable healthcare system. Challenges and Considerations: Ethical and Legal Frameworks: Ensuring AI is used responsibly requires robust ethical, legal, and policy frameworks. Trustworthy AI adoption is crucial for patient safety and health equity. Technology Infrastructure: Organizations need to update their technology infrastructure, including cloud capabilities, to fully support AI implementation. As we embrace these advancements, it's essential to stay informed and engaged in the conversation about how AI can continue to transform healthcare for the better. #HealthcareTransformation #GenerativeAI #HealthTech #Innovation #AIinHealthcare Thanks to sources McKinsey & Company (https://lnkd.in/g7HZHEST) and MedCity News (https://lnkd.in/gi95t4qJ)

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Introducing Trident AI, connector to #AWS #HealthLake to instant CCD to FHIR translation. In today's #Healthcare landscape, the push for #Interoperability is paramount. Effective communication across diverse healthcare systems allows for better coordination and patient care. However, achieving seamless interoperability across various health data systems poses significant challenges. Understanding the Challenges #Healthcare Data comes in multiple formats and often contains complex, unstructured information that traditional systems need help to handle efficiently. This complexity hinders integrating and utilizing data effectively, impacting #Patient #Outcomes and operational efficiencies. AWS HealthLake and Its Limitations #AWS #HealthLake provides robust solutions for storing, transforming, and analyzing health data, adhering to #FHIR standards which promote interoperability. Despite its strengths, HealthLake faces challenges, particularly with complex data processing and in-depth analytics for unstructured data like #ClinicalNotes. These limitations can slow down the integration and utility of critical health data. Trident AI: #FHIR #Connector Enhancing Capabilities Enter #TridentAI, a sophisticated tool designed by #TroveHealth to complement and enhance the capabilities of AWS HealthLake. Trident AI acts as a #FHIR Connector, adeptly handling data in the FHIR format. It consumes and processes this data and addresses the challenges posed by HealthLake's limitations. How Trident AI Makes a Difference Trident AI enhances HealthLake's processing capabilities by ensuring that even the most complex and varied data can be efficiently interpreted and integrated. This enhancement allows healthcare providers to gain quicker, more accurate access to patient information, thereby improving #DecisionMaking and #PatientCare quality. Integrating Trident AI with AWS HealthLake represents a significant advancement in #HealthcareDataManagement. By addressing HealthLake's inherent limitations, Trident AI facilitates a more robust data processing environment, driving forward the goals of healthcare interoperability. For healthcare organizations looking to leverage the full potential of their data, the combination of HealthLake and Trident AI offers a powerful solution to overcome traditional barriers. It reflects Trove Health's commitment to pushing the boundaries of what's possible in #Healthcare #Technology, ensuring that interoperability is not just a goal but a practical reality.

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How can we partner with patients and leverage digital innovations? Why should life-science, provider, and payer organizations invest in patient partnerships? The featured Deloitte Digital report "Transforming the Patient Experience" focuses on the evolution of patient-centric approaches in the life sciences and healthcare sectors. The report discusses the importance of integrating patient feedback in the development of medical treatments and technologies, the role of digital innovations in enhancing patient engagement. The report emphasizes the need for a comprehensive partnership between patients and healthcare providers to improve health outcomes. It also highlights various case studies and strategies for creating a more patient-centered healthcare system. Highlights: PATIENT-CENTRIC INNOVATIONS: 💙 Digital technologies and telemedicine became widely adopted, allowing for more patient engagement and data-driven insights. CO-CREATION WITH PATIENTS: 💙Patient-centricity involves patients as equal partners in decision-making processes. 💙Co-creation with patients should span from the initial brainstorming to product launch, integrating their feedback continuously. INTEGRATING ENGAGEMENT: 💙Full partnership with patients includes understanding their preferences, skills, and needs. 💙Effective engagement requires early involvement and adequate compensation for patients' time and input. DIGITAL SOLUTIONS: 💙Digital health technologies empower patients to monitor and manage their health, improving medication management and access to therapies. 💙AI and advanced analytics provide personalized patient experiences, improving engagement and outcomes. HOLISTIC PATIENT SERVICES: 💙Life sciences companies are moving towards in-house patient services, focusing on a comprehensive approach that includes financial, clinical, engagement, education, and therapy access. 💙Partnerships within the ecosystem are essential for creating unified patient experiences. Share your research and perspectives with Journal of Patient Experience Special Collection on Technology and Digital Innovations in Patient Experience https://lnkd.in/gZJKXy8V Attend Patient Experience Symposium Boston September 16-18, 2024 https://lnkd.in/eNKSpJ8G The Symposium features expert speakers and research on Patient Experience, Engagement, and opportunities to leverage technology. #DigitalHealth #PatientCentered #PatientExperience #ArtificialIntelligence #AI #PatientEngagement #PatientReportedOutcomes Deloitte article https://lnkd.in/eHS6gWq6 Phil Ripperger

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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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By joining value-based care's patient focus with AI's data-driven insights, healthcare is on the way to creating a future where both quality and affordability are able to effectively intersect! The combination of AI and VBC is building a healthcare system that's not only more productive, but more accessible and equitable for all. #AI #VBC #ValueBasedCare #Healthcare

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PERSPECTIVE. AI is reshaping the landscape of corporate strategy, and it’s crucial for board members to be prepared. Understanding how AI can streamline executive workflows, enhance operational efficiency, and maintain ethical oversight is no longer optional—it’s a strategic imperative. Board directors must ensure that AI integration aligns with the organization’s long-term goals, while carefully assessing risks and benefits. Starting small, reviewing outcomes, and refining approaches will help boards guide thoughtful and responsible AI implementation. How is your organization’s board addressing AI in its strategy? Let’s continue the conversation on preparing boards for the future of AI-driven corporate strategy. #healthequity #Boardgovernance #riskmanagement #crisismitigation #BCBR12 Santa Clara University Leavey School of Business Children’s Hospital Association

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5 Things EscrowAI is Doing to Help Customers Meet the Coalition on Health AI’s (CHAI) Assurance Standards BeeKeeperAIis committed to helping healthcare organizations realize the Coalition for Health AI’s (@CHAI) Assurance Standards for effective, equitable, reliable, transparent, and secure AI/ML/Gen AI solutions. Due to our privacy and security safeguards integrated and automated into our privacy enhancing collaboration platform, EscrowAITM, we are enabling our customers to meet these essential standards in the following ways: 1. Enhancing Usefulness, Usability, and Efficacy EscrowAI ensures AI models are reliable, user-friendly, and improve healthcare workflows, while providing measurable benefits like better outcomes and efficiency. 2. Ensuring Fairness and Equity EscrowAI mitigates bias by securely enabling diverse data use, ensuring AI performs equitably across all patient groups, reducing disparities in healthcare. 3. Promoting Safety and Reliability EscrowAI continuously monitors AI systems to ensure they are safe, reliable, and capable of adapting to healthcare changes without failure. 4. Supporting Transparency and Accountability EscrowAI enables clear, interpretable AI decisions, allowing stakeholders to understand how models work and holding AI developers accountable. 5. Safeguarding Security and Privacy EscrowAI protects sensitive healthcare data throughout the AI lifecycle, ensuring privacy and security while complying with HIPAA and other regulations. Join us at the AI @ HLTH Pavilion, Booth 4611, on Tuesday, October 22nd, from 2-4 PM to learn how EscrowAI can help your organization meet CHAI’s Assurance Standards for trustworthy AI. Our team will be on hand to discuss how our solutions can enhance transparency, fairness, safety, and security while accelerating your time to market. Don’t miss this opportunity to explore how we can support your journey towards responsible healthcare AI!

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