Sumit Nagpal

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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My colleagues, James R. Bush, Adarsh Gosu and I were honored to lead an Executive Roundtable at the #BeckersAnnualMeeting last month. Leaders discussed the capabilities of Generative AI in health care, emphasizing the trust, governance, data modernization, and workforce training. Some highlights included: ☑ Establishing effective governance is crucial for successful AI implementation. ☑ The importance of change management can’t be overlooked. ☑ Building consumer trust and engagement is essential in AI adoption. ☑ Workforce upskilling is necessary for AI fluency and successful implementation. ☑ Designing AI solutions with scalability in mind is a must. A special thanks to Becker's Healthcare for the opportunity! Read a recap of our conversations on Beckers Hospital Review. https://lnkd.in/gEVWxwzq Want to learn more about Deloitte guidance for the potential of #AI in healthcare? We have a report with critical insights about implementation and governance. https://lnkd.in/gXE_HVG2 Bill Fera, Tina Wheeler, Adarsh Gosu, Dan Kinsella, Anne Phelps #AIinHealthCare #GenAI #FutureofHealth #Deloitte #hospitals #HealthIT *Information posted here is a personal opinion and is not a substitute for medical advice. Shared publications contain general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services.

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EHR and AIoT development trends in digital health What will be the trend of professional medical examnation and home self-examination health data? Welcome everyone to participate in the discussion!

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Let's talk AI with payers and providers—some interesting numbers to consider from the latest research (Sept 2024) (KLAS Research & Bain) Here are four eye-opening takeaways: 1. AI Strategy Surge: • 15% of providers now have an AI strategy, tripling from 5% last year • 25% of payers are leading the pack with established AI strategies • Both sides are bullish on generative AI's potential 2. Tech Spending Spree: • 75% of surveyed orgs boosted IT investments • Top priorities: cybersecurity, clinical workflow optimization, and data platforms • 70% of orgs doubling down on security 3. Payer Priorities: • Focus on care coordination, utilization management, and claims processing • 65% grappling with legacy tech challenges • Trend towards streamlining tech stacks and favoring existing vendors 4. AI Adoption Hurdles: • Regulatory and legal concerns top the list • Cost and accuracy issues (like AI hallucinations) are giving pause • Growing need for robust governance and ethical frameworks The report here: https://lnkd.in/gxjKPUaW Is your organization leading the charge or playing catch-up? #HealthcareAI #TechInnovation #FutureOfHealthcare

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Information Systems Research (ISR) has recently published a new article to the Articles in Advance page:   Article Title "How Hospitals Differentiate Health Information Technology Portfolios for Clinical Care Efficiency: Insights from the HITECH Act"   Authors Jessica Pye (deceased), Arizona State University Arun Rai, Georgia State University John Qi Dong, National Technological University, Singapore   Problem definition We examine how hospitals differentiate their HIT portfolios in response to cost inefficiencies in clinical care processes and HIT policy uncertainty.   Relevance Adapting HIT portfolios to address cost-based shortfalls and policy uncertainty is crucial in shaping service delivery and impacting care costs, making it a key concern for policymakers and hospital decision-makers. Theoretical foundations We combine behavioral theory and institutional theory to explain how hospitals differentiate their HIT portfolios through idiosyncratic learning in response to cost-based performance shortfalls and shifting isomorphic pressures from changes in HIT policy uncertainty.   Methodology We constructed a panel dataset of 11,316 hospital-year observations from 3,319 U.S. hospitals over 2007–2014 to investigate how hospitals’ HIT search differentiation is influenced by cost-based performance shortfalls and policy uncertainty during the phases of the HITECH Act, from conceptualization to enactment to enforcement.   Results Our research provides a key insight: Moderate policy uncertainty, particularly during the HITECH Act's phases, significantly shapes hospitals' search for novel HIT solutions to address performance shortfalls. Hospitals enhance their search differentiation when uncertainty decreases from conceptualization to enactment but reduce it as uncertainty diminishes from enactment to enforcement.   Contributions Our findings surface the utility of combining the behavioral theory of the firm with institutional theory to explain the interdependence among a hospital’s cost-based performance shortfalls, HIT policy uncertainty, and HIT search differentiation. They show how hospital managers and policymakers can reorient their strategies to leverage the interdependencies among these elements, thereby encouraging the pursuit of innovative HIT systems over widespread imitation, to effectively address cost-based performance shortfalls in hospitals.   Short quote Unlocking Healthcare Innovation: hospitals excel in deploying new technologies through peer benchmarking and navigating moderate regulatory uncertainty. Dive into our research to see the transformative impact of this benchmarking strategy combined with moderate policy uncertainty!"   #HealthcareInnovation #HITECHAct #PolicyImpact   Keywords search differentiation, health information technology, performance shortfalls, policy uncertainty, behavioral theory of the firm, institutional theory   Link to article: https://lnkd.in/djh84uad

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The healthcare system is broken, or at least hugely unoptimized, from any reasonable perspective (flatlined outcomes, falling patient/provider satisfaction, rising costs, etc.) The market for new health technology is framed around this flawed system. Almost all health tech innovation funding, private and increasingly public, is steered towards near-term product-market fit. The overall health ecosystem is incentivized to perpetuation decline and dilute transformative innovation. Perhaps it is time for a new approach at a systems level? AI MINDSystems Foundation #health #tech #science #research #outcomes #ecosystem

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In Patient Blood Management (#PBM), partnerships between innovation and hospitals are crucial to avoid past unnecessary blood management decisions. These partnerships need to extend beyond the ER or OR, impacting the entire patient experience. #Patients benefit from the education provided by their selected medical center, but the public lacks this relationship. Since hospital relationships are often based on proximity, who takes responsibility for public #anemia and PBM awareness? Our team does. We're not hired or seeking donations to raise this awareness. We believed that building a bridge of engagement would attract all interested parties. The only obstacle in this engagement is the apprehension of forming new partnerships. We are pleased to see a shift in this thinking. Creating a culture of public partnerships that evolve into patient partnerships within the hospital's multidisciplinary medical team will yield the best outcomes. Let's work together for the best public, patient, and overall anemia and PBM outcomes. Werfen Brazil Santa Casa de Porto Alegre Rishab Tyagi

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Walmart is selling its #telehealth business to Fabric 💸 Fabric is a #healthtech startup that unifies virtual and in-person care across intake, triage, routing, and treatment while automating workflows for staff. They raised a $60M round earlier this year funded by General Catalyst, Thrive Capital, GV (Google Ventures), and Salesforce Ventures. They also made two other acquisitions, Zipnosis (asynchronous #virtualcare) and GYANT (conversational AI assistant used for #digitalfrontdoor) within the past 18 months. 📈 This acquisition will get Fabric access to the 30,000 employers and 5 million members that Walmart served, expand provider network, add virtual behavioral health, and build on their employer’s and payer’s solutions. #digitalhealth M&A activity continue to be trending this year as we’re seeing more synergies come together when companies join forces and the challenging funding environment. I’m curious to see how Fabric will be able to merge these new acquisitions into their current workflow to improve care management. Any thoughts from you❓

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AI is only as good as its input and training data, as well as the questions we ask of it. When we build new systems, it’s easy for existing limitations to elicit a suboptimal solution for a diverse population. #aihealthcare #aihealthequity #healthequity #ai #datadisparity #healthdisparities

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I have always argued the centrality of partnership strategies for start-up success — and LIVEMED Telehealth™'s collaboration with Sully.ai is a perfect example of why. This specific partnership goes beyond a standard collaboration—it addresses healthcare innovation at the core, tackling major gaps. Together Sully.ai’s expertise and LIVEMED Telehealth™'s platform, will enable more efficient, timely, specialist care to hospitals that truly need it. 💡 This isn’t just about launching a product; it’s about solving real challenges in healthcare with smarter tools and tech. 🤔 With the focus on individual founder success, I wonder if some start-ups miss opportunities to leverage collaborative strengths, forgetting that the fastest way to fast-track our impact is together, not alone. Strategic partnerships can do so much more than just fill tech gaps: ➡ Trust building - By partnering with established names, you automatically leverage their credibility, which accelerates adoption. ➡ Access and reach - Partnerships open doors to new markets and customer bases that would otherwise take years to penetrate. ➡ Expertise - Collaborations bring unique insights and specialised knowledge, which allows companies to offer more comprehensive solutions. ➡ Scaling and expansion - With the right partner, companies can scale faster, tap into broader networks, and expand their influence far beyond their own capabilities. At LIVEMED Telehealth™, these partnerships aren’t just a footnote— they are the backbone of rapid, strategic growth. They amplify reach, credibility, and innovation—delivering solutions that are not just competitive but transformative. Congratulations to Saamer Siddiqi M.D., Mirza Baig, Jonathan Goldberg, Ahmed Omar and the whole team at Sully.ai for this significant step forward. 👏🏼 #StrategicGrowth #HealthcarePartnerships #StartupScaling #Telehealth #Innovation

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Traditional EHR systems often fall short in supporting the essential functions of Enhanced Care Management (ECM) under #CalAIM. ECM requires seamless coordination across physical, behavioral, and social determinants of health, proactive member engagement, and real-time data exchange—capabilities that extend beyond the scope of many EHRs. Our Incedo #CareManagement platform is fully aligned with ECM and fills the gap of traditional EHR systems. Incedo offers an integrated whole-person approach to care management and facilitates collaboration across providers and managed care plans to improve outcomes for California’s most vulnerable populations. If you’re looking for a complete #ECM solution, let’s talk about how Incedo can help. https://hubs.ly/Q02RnVwW0 #HealthcareInnovation

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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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🌟 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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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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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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Signify Research Ltd’s discusses the recent announcements in its latest insight, signaling a significant shift in US healthcare data exchange: • Official unveiling of the first cohort of Qualified Health Information Networks (QHINs), including eHealth Exchange, Epic Nexus, and more, fostering nationwide interoperability. • Final ruling of HTI-1, enhancing transparency and support for health data access, crucial for advancing healthcare delivery. • CMS Interoperability and Prior Authorization Final Rule aims to streamline processes, improving efficiency and access to care. Read the full article: https://buff.ly/3xQPvsn #TEFCA #Interoperability #healthcaretechnology #marketintelligence

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Navigating Real-World Evidence for Health Technology Assessment: Key Insights from Industry Experts 📊🔍 *The recent webinar featuring insights from April Betts (UCB), Stephen J. Duffield (NICE), and Rachel Cummings (Decisive Consulting) provided an in-depth look into the evolving role of real-world evidence (RWE) in health technology assessments (HTAs). Here are the key takeaways: ✔ Evolution and Importance of RWE: RWE is becoming a staple in healthcare, impacting regulatory decisions and market access. It addresses gaps inherent in randomized controlled trials (RCTs) by providing data on larger populations and real-world practices. 🌐🧬 ✔ Challenges and Opportunities: The integration of RWE faces challenges such as data quality, relevance, and regulatory acceptance. However, it presents opportunities to enhance evidence for HTAs, especially in demonstrating long-term effectiveness and safety. 🚧📈 ✔ Strategic Applications: RWE is critical in areas like cost-effectiveness analyses and can influence the decision-making processes of bodies like NICE. Effective RWE strategies involve early planning and continuous adaptation to evolving healthcare landscapes. 📝💡 ✔ Collaborative Efforts: Successful RWE utilization requires collaboration across various stakeholders, including academia, industry, and regulatory bodies. This collaboration helps ensure that RWE meets diverse regulatory requirements and adds value to HTA submissions. 🤝🌍 ✔ Future Directions: The use of RWE is expected to grow, with increasing sophistication in data analytics and broader regulatory acceptance. Stakeholders must remain agile and proactive in leveraging RWE to inform healthcare decisions and policies. 🔮📊 *These discussions highlight the critical role of RWE in shaping the future of healthcare decision-making, underscoring the need for strategic alignment and robust methodologies in its application. #HealthcareInnovation #RealWorldEvidence #HTA #Pharmaceuticals #HealthTech

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Like an unfazed young quarterback who keeps firing it downfield despite a spate of interceptions, CMMI keeps tossing around VBC models hoping something will connect. Contrary to its intent, CMMI's programs increased spending by $5.4 billion from 2011-2020 with another increase in net spending of $1.3 billion by 2030. Of the more than 50 models the Center has implemented, only 6 have generated "statistically significant" savings. Only 4 (Home Health Value-Based Purchasing, Prior Auth Model for Non-Emergent Ambulance Transport, Diabetes Prevention Program, and Pioneer ACO) were certified for expansion. CMMI points to the voluntary nature of the programs as a challenge to achieving cost savings. However, CMS hasn't done itself any favors here by aggressively ratcheting down payments and making downside risk >>> upside risk. (Notably, two upcoming programs -- TEAM and Inpatient THA/TKA PROMs are mandatory). Finding the VBC sweet spot was always going to require some trial and error. Perhaps CMMI has learned from the programs that failed or weren't chosen for expansion. TEAM doesn't seem to be all that different from CJR. Making Care Primary aims to closely integrate primary and specialty care (or, more likely, incentivize PCPs to take on more of this work). Not surprisingly, one of the criticisms is lack of provider input. The programs are too complex, too expensive to administer, and aren't transparent. CMMI should take note of several studies demonstrating the success of physician-led VBC efforts. Here are some other thoughts: - Offer financial grants in 5- or 10-year terms for any organization that designs its own VBC program and presents a reasonable and viable clinical/business model. CMMI would do itself a favor by partnering with or at least listening to innovators. - Medicare Advantage complexity and risk adjustment handwaving shouldn't be the only mechanisms by which advanced providers can profitably care for beneficiaries. That program isn't saving money either, but it's the only way many of these approaches can generate meaningful revenue (and most still aren't profitable). - Have regular meetings with those building VBC models, particularly those with strong physician leadership. Those meetings should be transparent and productive of action plans and iterative changes that increase model viability. - Be more open about what your goals and targets are. No one should be a victim of their own success, and if you keep moving the goalposts, you shouldn't be surprised when people get frustrated and drop out. I'm certain that, given fair incentives, a meaningful voice, and an equal seat at the table, healthcare innovators can design sustainable VBC programs. But there needs to be more collaboration and a willingness to listen and engage. Otherwise, you're just slowly adding to the alphabet soup of also-ran programs. #medicine #healthcare #health #vbc #healthcareinnovation #valuebasedcare

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Very interesting, insightful study. Flare Capital Partners AI in healthcare is hype. Most AI stories for healthcare are tech advancements. Not real clinical advancements or fitting into their workflows, bearing few. MedTech Innovators face these paradox. 1.Adoption requires Evidence. But evidence comes only from adoption. Clinical data can not be synthetic data for good AI. 2.Regulatory, validation requires money. But investors require regulatory, validation. 3.MedTech need faster adoption, but healthcare is slower among every profession, a cut-throat industry. They won't use it, if it is more than 2-3 mouse clicks. https://lnkd.in/gUh8sDHe

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