David Nace

California Health Care Foundation dropped a gem in July: health data exchange isn’t a futuristic buzzword, it’s cutting costs and boosting care today. A CHCF dive into real-world action shows across six expert interviews and over 30 peer-reviewed studies, early ROI is cropping up in places like jail transitions and housing support—but only when execution is sharp, Medicaid leadership is bold, and tech plays nicely across systems. https://lnkd.in/g6MAsqvW With a boost from the Data Exchange Framework (DxF), California’s HIEs are proving that when data moves, outcomes improve. Los Angeles Network for Enhanced Services (LANES), in partnership with Northeast Valley Health Corporation, achieved an 85% drop in emergency visits and a 68% reduction in hospitalizations for patients with diabetes — plus an 82% decline in asthma-related ED use. Manifest MedEx and Aledade, Inc. are also contributing measurable wins, using real-time ADT alerts to support better care transitions and reduce unnecessary ED visits. It’s not about one HIE — it’s about a statewide shift toward smarter, more connected care. Meanwhile, New York eHealth Collaborative, is estimated to generate $160–195 million in annual value—largely from administrative efficiency. State Health Alliance for Records Exchange (SHARE) has been blazing trails into the frontier of health data utility, integrating clinical data with social needs, corrections, EMS, immunizations, and disease registries. Even providers using spreadsheets feed into the system via HL7 transformation—making SHARE a true model for equitable, whole‑person care. Oklahoma’s MyHealth Access Network is making data count: by weaving external data into clinician workflows, they’ve boosted colon cancer screening rates and cut down on redundant imaging. These gains didn’t come from hardware alone—they’re built on strong governance and a shared vision of value. These aren’t hypotheticals. These are real‑world, measurable wins powered by clean, connected data flows. And let’s not forget the last mile: Behavioral health and sobering centers—like those referenced in the Daniel J. Chavez interview—are diverting people from high-cost emergency rooms and jails into lower-cost, community-based care. While the article only briefly mentions it, those are the kinds of high-value, high-impact use cases that thrive when health data moves at the speed of need. #HIE #LastMileInteroperability #HealthTechROI Converge Health

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👥 Who are the real customers in healthcare? It’s not just patients. From caregivers to payers, from frontline providers to digital health users—healthcare serves a broad ecosystem. Recognizing all customer types helps us design better experiences, deliver more value, and lead more effectively. 🌀 At the center is the patient—but surrounding them are: ✅ Families & caregivers ✅ Physicians & APPs ✅ Healthcare staff ✅ Payers & insurers ✅ Government & regulators ✅ Telemedicine users ✅ Students & academic institutions 🔍 Understanding your audience = delivering with purpose. #HealthcareLeadership #PatientCenteredCare #HealthcareStrategy #CustomerExperience #HealthEquity #DigitalHealth #MedicalEducation

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2025 was a consequential year for Medicare policies impacting wound care. What was at stake? Payment structures, coverage determinations, cost measures and more.   The @Alliance of Wound Care Stakeholders detailed how the wound care community engaged and advocated on these issues to shape policy outcomes in its 2025 Advocacy Impact Report.   There are many more policy changes to come that will directly impact wound care. Stay informed and engaged. Because if you’re involved in wound care, these issues matter.   https://lnkd.in/gNbMgnXd   #AdvancingWoundCare #AllianceImpact #HealthPolicy #HealthcareAdvocacy #WoundCareAdvocacy #WoundCare

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Integrating ambient AI into clinical workflows is feasible and effective, but only with rigorous governance, real-time monitoring, and adaptive workflows. 1️⃣ A stepped-wedge randomized trial tested ambient AI for clinical note generation across 66 providers in 8 specialties at UW Health. 2️⃣ AI utilization reached a median of 65.4%, with task-specific adoption guided by feedback loops and a real-time dashboard. 3️⃣ A coding error tied to a note template redesign dropped ICD-10 documentation accuracy from 79% to 35%; targeted fixes and training restored it. 4️⃣ An internal LLM coder, used for ICD-10 compliance audits, achieved high agreement with professional coders. 5️⃣ The governance model connected operational and research teams, enabling rapid troubleshooting and iterative improvements using the SEIPS and EPIS frameworks. 6️⃣ A difference-in-differences approach detected performance drift in metrics like time in notes and after-hours work, triggering prompt interventions. 7️⃣ The AI system reduced documentation time by ~20 minutes per day after providers adapted to revised workflows. 8️⃣ Provider feedback revealed improved efficiency but also barriers like consent complexity, tool quirks, and note quality concerns in certain settings. 9️⃣ All protocols, including trial design, LLM prompts, and monitoring dashboards, were released in an open-source playbook to aid replication. 🔟 This framework shows how to safely scale AI in practice while preserving clinical accuracy, regulatory compliance, and provider well-being. ✍🏻 Majid Afshar, MD, MSCR, Felice Resnik, Ph.D., Mary Ryan Baumann, Josie Hintzke, Kayla Lemmon, Anne Gravel Sullivan, PhD, Tina Shah, Anthony Stordalen, Michael Oberst, Jason Dambach, Leigh Ann Mrotek, Mariah Quinn, Kirsten Abramson, Peter Kleinschmidt, Tom Brazelton, Heidi Twedt, MD, FACP, FAMIA, David Kunstman, Graham Wills, John Long, Brian Patterson, Frank Liao, Stacy Rasmussen (Marver), Elizabeth Burnside, Cherodeep Goswami, Joel Gordon. A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice. NEJM AI. 2025. DOI: 10.1056/AIdbp2401267 ❗ Healthcare AI in 2025 - a reflection: https://lnkd.in/dgFCgBAC

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Proud to share that Humana is collaborating with b.well to help make healthcare information easier for individuals to access and use. A meaningful step toward more connected care. #HUMemployee

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CONGRATULATIONS Precision Healthcare Technologies! Our My MD Hub Health Records platform has been approved for inclusion in the CMS Medicare App Library—a federally backed, centralized marketplace for vetted digital health applications. Selection into the CMS App Library is not symbolic—it requires passing a rigorous, independent evaluation of security, privacy, and clinical effectiveness, and aligns the platform with CMS’s national interoperability framework. This places My MD Hub within a trusted federal distribution channel designed to integrate directly into care workflows—not sit on the sidelines as another disconnected tool. This milestone validates nearly 20 years of work by Precision Healthcare Technologies, building the compliance grading algorithms used by CMS and payers to help determine reimbursement across the healthcare system. But along the way, one issue became undeniable: - Healthcare doesn’t move without health records—and the system managing them is broken. - Providers process 800–1,000 record requests per month, while patients repeatedly complete the same paperwork over and over again. My MD Hub changes that by putting control of health records directly in the hands of the individual. However, health records alone mean nothing without intelligence. - What makes this platform truly different is Precision’s Stealth Workflow Intelligence—which connects 20 sectors of healthcare and consumer health based on real-time, ongoing medical necessity for each individual. This is not just interoperability—it’s orchestrated, necessity-driven connectivity. While this recognition comes through CMS, My MD Hub is fully payer-agnostic, supporting Medicare, Medicaid, commercial populations, and the growing number of individuals navigating care outside traditional insurance models. That matters because: - Over 140 million Americans are uninsured, underinsured, or avoiding care due to cost - More than 50% of primary care now occurs outside traditional insurance and EHR systems - YOU had better control your own data because there will be nobody to request it from. This is why YOUniversal Care was created—providing access to care options, transparent pricing, and flexible pathways across free, cash, subscription, insurance, or any combination. In a system where records are fragmented—or don’t exist at all—control of your health data is no longer optional. This is more than an approval. - It’s a shift toward intelligent, connected, patient-driven healthcare. #DigitalHealth #CMS #Interoperability #HealthcareInnovation #PatientAccess #HealthTech #ValueBasedCare #ConsumerDrivenHealthcare #MyMDHub #YOUniversalCare

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As Jay Rughani, Jane Rhee, and Julie Yoo point out in this a16z Bio + Health piece on “Infinite Healthcare,” healthcare today looks a lot like telecom decades ago—with a cost structure that reinforces a scarcity mindset. They argue that AI can shift healthcare from a system of scarcity to one of abundance, and I could not agree more. Many of us remember when phone calls were billed by the minute—more usage meant more cost. But as networks scaled, pricing shifted to unlimited plans. Usage surged and value expanded for both customers and providers. Our industry can follow the same path, but only if we shift to a payment model that aligns with the future we are trying to create. For decades, our healthcare system has been built on limits—limited clinicians, appointments, and coordination. Those limitations have normalized waiting and suffering—and added complexity. AI has the power to radically expand our capacity to care for people, helping us shift from simply reacting to illness to proactively supporting health every day. Technology alone will not change the system, though. Abundance cannot thrive inside a payment model that rewards episodic intervention instead of ongoing health management. If we want proactive, continuous care at scale, incentives must align with preventing illness, not just treating it. Scarcity shaped my dad and our family’s experience at the end of his life. Abundance can create an entirely different future.  https://lnkd.in/gNQ4QkHi

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The Clipboard is Still Winning. Here’s why $40B in EHR investment failed the patient. For decades, our digital health infrastructure has been fundamentally misaligned. The dirty secret of the healthcare system is that EHRs were engineered and optimized for billing transactions and lawsuit avoidance, not for continuity, human connection, or outcomes. They are provider-centric ledger systems. The result? Every healthcare interaction still begins from zero. Patients are forced to constantly re-explain their entire health history and provide the same documents because their vital data is trapped in institutional silos. This isn't a bug; it's the architecture given to us. We need to stop iterating on the systems of record and start building for the human. The category battle ahead isn't between apps, it's between paradigms: Institutional Control vs. Personal Agency. Where do you see the greatest wasted opportunity in the current digital health ecosystem? #HealthcareInnovation #PatientAgency #EHR

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AI is moving faster than governance—and healthcare is starting to feel the consequences. https://lnkd.in/exAXWDBs This week, Sutter Health and MemorialCare were hit with a class-action lawsuit over the use of Abridge AI, alleging patient conversations were recorded and processed without clear consent. Let’s be clear—this isn’t just about one tool or one system. It’s about a broader trend: Technology is being deployed faster than legal, compliance, and operational teams can fully evaluate it. AI scribes and ambient listening tools promise efficiency, reduced burnout, and better documentation. But without the right structure in place, they introduce real risk: • Patient consent gaps • Third-party data exposure • Unclear data storage and transmission pathways • Potential violations of Health Insurance Portability and Accountability Act and state-specific privacy laws The core issue isn’t AI adoption—it’s unstructured AI adoption. If policies, procedures, and workflows are not built before deployment, organizations are effectively testing risk in real time… on real patients. The organizations that get this right will: ✔ Align legal, compliance, IT, and clinical leadership upfront ✔ Define clear consent and disclosure protocols ✔ Map data flow and third-party relationships ✔ Integrate AI into workflow—not bolt it on AI is not slowing down. Counsel review cycles won’t magically speed up. That means the responsibility shifts to leadership: Build the governance framework first—or accept the exposure that comes with skipping it. Amanda Walker Copsey Andrew Feldman American Bar Association Health Law Section Sean Weiss Sally Ann Frank Mysty Blagg Courtney Hurtig Rebecca E. Gwilt Jennifer Bryan, MD, FAAFP Hal Katz Lisa D. Taylor Hillary Cavanagh Bridge Oncology

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AI & RWE in Community Oncology: Delivering What Matters Most to Practices and Patients The latest AJMC - The American Journal of Managed Care feature, Practical Considerations for AI in Community Oncology, underscores something those of us working in this space already know: ✅ Community practices are eager for data-driven solutions—but they have to be actionable, aligned to workflow, and mindful of real-world constraints. ✅ AI and RWE hold immense promise—but only when designed and deployed in partnership with the people delivering care on the ground. At MiBA we’ve seen how much impact thoughtful implementation can have: enabling clinicians to make informed, timely decisions; helping practices navigate value-based contracts; and supporting life sciences teams in understanding the true patient journey where most cancer care is delivered. The article makes a key point that resonates deeply: 🔷 It’s not just about technology—it’s about collaboration. Providers, payers, life sciences, and technology partners all have a role to play in ensuring AI and RWE live up to their potential in improving equity, efficiency, and outcomes. These are the kinds of conversations we need to be having more often—and the kinds of collaborations we need to accelerate if we want to make a meaningful difference for patients and practices alike. 📣 If you’re working on AI or RWE strategy in oncology and want to compare notes on what’s working, what’s challenging, and where the opportunities lie strategy—whether you’re a practice leader, a life sciences executive, or a payer— I’d love to connect and continue the dialogue.

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Patient portals are currently built like digital vaults, not daily clinical tools. Despite rising initial activation rates across health systems, the recurring daily usage of patient portals remains strikingly low. We are caught in a "Sales and Retention Paradox," where platforms act merely as static repositories for historical lab results rather than dynamic utilities for managing health. To cross the threshold of perceived value, we must recognize the Institutional Realities of digital adoption: ■ Transactional Isolation: Portals built only for acute-care messaging will never achieve high-frequency usage. ■ Habit-Driven Architecture: We must integrate high-frequency daily tasks—moving beyond the transactional visit to foster organic adherence within the digital ecosystem. At the HFiles , we study innovation adoption as a systemic behavior. True patient engagement requires re-engineering the digital experience to align with daily health habits, transforming compliance into a seamless routine. 🟢 Join these market insights every Tuesday in H.O.W Businix (Open) 👉 https://lnkd.in/dXeNEFbj #PatientEngagement #DigitalHealth #HealthTech #EHR #PatientPortal #HealthcareInnovation #HealthInformatics #CareCoordination #DigitalTransformation #Businix #HOWNetwork

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With OpenAI is paving the path to a first-level triage / PCP layer + empowered patients, and Anthropic now building context-rich interoperability tools that link fragmented workflows and remove unnecessary admin….we are entering a brand new era in healthcare. Innovation can now focus on providing better care and experiences vs. solving infra problems with point solutions.

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The next layer after the EHR The electronic health record digitized documentation. It did not digitize longitudinal decision-making. As healthcare shifts toward continuous oversight, a new question emerges: What governs decisions between encounters? - Not data capture. - Not dashboards. - Not alerts. Governed execution across time. The next foundational layer of healthcare will not replace the EHR. It will sit above it — mediating human input, AI reasoning, and automated intervention in a way that remains clinically accountable and economically aligned. Architecture determines durability.

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About two-thirds of physicians have incorporated AI-driven tools into practice based on AI use cases, nearly doubling from 2023 to 2024, the organization said in February. But nearly half (47%) of physicians surveyed said that increased regulatory oversight is needed to increase their trust in healthcare AI tools. Doctors overwhelmingly stated that they need data privacy assurances (87%) and do not want to be held liable for AI model errors in order to gain their buy-in.

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This week, the White House announced the Health Tech Ecosystem initiative and the CMS Interoperability and Patient Access Framework. These are significant steps towards liberating our clinical data from its traditional silos. To build a national health tech ecosystem, we will need to achieve widespread adoption of a FHIR-based API infrastructure. Additionally, we must focus on acquiring, optimizing, and delivering high-quality data that is secure, suitable for its intended use, and ready for artificial intelligence applications. This effort should include comprehensive, longitudinal patient histories, standardized data that meets national standards, and the contextualization and harmonization of both structured and unstructured data. #HealthTech #Interoperability #FHIR #CMS #ClinicalData #ValueBasedCare #DigitalHealth #Availity #AIinHealthcare #DataOptimization #HealthcareInnovation https://lnkd.in/eFnGSP8f

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Honored to be speaking at the Advanced Research Projects Agency for Health (ARPA-H) Agentic AI Event on Defeating Disease with Clinical Agentic AI. This moment feels important. We are moving beyond proof-of-concept AI and into an era where patient-facing, agentic systems must be safe, scalable, and deeply integrated into real clinical workflows. Getting this right requires close collaboration between clinicians, technologists, regulators, and health systems. I’m looking forward to joining an outstanding group of clinician-leaders to share lessons from radiology—one of the earliest adopters of clinical AI—and discuss how those hard-won insights can inform the next wave of agentic AI, including chronic disease management through programs like ADVOCATE. Grateful to ARPA-H and Haider Warraich for convening this conversation at a pivotal moment for healthcare. #HealthcareAI #AgenticAI #ARPAH #AIinHealthcare #HealthPolicy #DigitalHealth HOPPR

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Most health systems use only about 6% of the clinical data sitting in their EHRs, 6% of what is arguably one of the most valuable assets sitting on their balance sheet. Those same systems have spent billions -- collectively -- on EHR infrastructure over the past decade. The investment is massive. The utilization? The logical question isn't "how do we get better AI tools?" It's something more uncomfortable: why are we layering analytics and AI on top of data architectures that were never designed to talk to each other? Interoperability gets treated as a compliance exercise -- check the box, meet the federal mandate, move on. But if surgical supply costs represent roughly 40% of OR operating expenses, and the data that could drive smarter procurement decisions is trapped in disconnected systems across scheduling, inventory, and clinical documentation...the math doesn't work. From the OR floor, the frustration is concrete. Preference cards live in one system. Inventory counts live in another. Case costing data -- if it exists at all -- lives somewhere else entirely. The surgeon making real-time supply decisions has the least visibility into what those decisions actually cost. So, the way we manage these costs either boosts or busts operating margins in a meaningful way. And yet interoperability -- the connective tissue that would make cost-per-case analytics possible -- remains an afterthought. The 6% figure should bother everyone in healthcare operations. Not because we need more data. Because we're ignoring what we already have. #HealthcareOps #Interoperability #SupplyChain #OREfficiency #HealthcareAnalytics

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Today's Centers for Medicare & Medicaid Services Health Tech Connectathon made it clear we are no longer talking about the future of interoperability, we are watching it intersect with the realities of patient experience, digital identity, and AI deployment. Round of applause for Amy Gleason who boldly advocates on behalf of patients to have seamless access to our health information and holding all early adopters and attendees accountable. Promising to see the support and eagerness of this Administration to digitize the healthcare ecosystem for all patients. Mic drop moment goes to CMS Administrator Dr Mehmet Oz "..they[patients] own their data, they paid for it, we helped them in many ways, but that data needs to be something they feel they have agency over otherwise they're not going to feel comfortable, nor expect to be able to take it and share it with many of the solutions that are in this room." 🎤 Top of mind as I leave DC: 1) National Provider Directory (NPD) is in active beta 🔥 -Massive implications for patient navigation, referral accuracy, care coordination -Directory must evolve w/real-world use cases: patient and carepartner validation 🔑 -Would be great to have provider direct addresses to streamline trusted communications and reduce admin burden 2) "Kill the Clipboard" breakout exposed the real bottlenecks , most = fixable! Persistent problems include: -FHIR APIs that don’t return data -Geofencing blocking exchange -Consent for minors -Record locator services failing across boundaries -Overheard: biggest obstacle: “Our EMR” 👀 -Leveraging information blocking enforcement and multi-stakeholder collaboration = 🔑 3) Digital Identity is now the prerequisite for everything -Across demos, foundation was clear: digital identity & ID verification are becoming the new rails for: benefits verification, enrollment, record access, patient agents -Potential Minimally Viable Product for patient access may: verify → request → aggregate → choose → share (via QR code) 4) The conversational AI breakout revealed: -LLMs and clinical AI won’t scale without trust, transparency & skilled humans -“Every patient has a different tolerance and need for AI.” -AI scribes remain deeply problematic in oncology 👀 -“Expert-in-the-loop” must mean domain-expert, not just “a human.” -Deploying AI on top of workflows w/fax machines and pagers could be DOA -Up-skill clinicians and patient-facing staff, redesign result-sharing (pathology, imaging, labs), and create disease-specific patient/provider sandboxes, not just developer sandboxes If you attended, add your takeaways below!!! Kristen Valdes Ryan Howells Deven McGraw Scott Stuewe Donald Rucker Steven Posnack Arda Kara Mitch (Kost) Chaney Ryan Dempsey Aneesh Chopra Bakul Patel Aashima Gupta Anna McCollister Jan Oldenburg Grace Vinton Dave deBronkart Shahid Shah Kamal Jethwani

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