Out of the FHIR Podcast

Gene Vestel

Talking about FHIR evestel.substack.com

  1. Episode 23 - Max Nussbaumer

    FEB 4

    Episode 23 - Max Nussbaumer

    In this episode, I sat down with Max Nussbaumer to talk about why he founded Max Health, why he’s bringing his work from Europe into the U.S. market, and what he believes is about to change in healthcare faster than most people realize. Max has deep roots in the FHIR ecosystem from academia at the Technical University of Munich, to Firely, to years of consulting across Europe. Now he’s building something bigger: a company focused not just on FHIR infrastructure, but on how that infrastructure enables real, visible impact for patients through AI, Smart on FHIR, and even wearable integrations. But the real theme of this conversation wasn’t “FHIR adoption.” It was this: Healthcare is about to be reshaped not by standards alone, but by what AI can now do with standardized data. FHIR Is No Longer Niche Max pointed out something many of us have felt over the past year: FHIR used to be a niche standard discussed at connectathons and DevDays.Now it’s the plumbing behind consumer AI health integrations from tools like ChatGPT and Claude. For the first time, health data is entering general-purpose reasoning systems that people use every day. That changes the game. Not because FHIR is new, but because AI can finally use FHIR data at scale. “Software Is Inflationary” One of Max’s best lines: What used to take a year to build can now be built in days. This is showing up at hackathons, startups, and even among 18-year-old builders experimenting with AI, spatial awareness, and real-time health event detection. The barrier to building healthcare software has collapsed if you understand the underlying problems. The differentiator is no longer coding skill.It’s domain understanding and knowing what problem is worth solving. The Real Problem: Incentives, Not Technology Max made a powerful comparison: In aerospace, countries cooperate on standards to prevent planes from colliding mid-air.In healthcare, we still don’t have true global data standards because the financial incentives don’t demand it. Healthcare costs continue to rise (approaching a quarter of U.S. GDP), yet most digital tools help people navigate the system, not reduce the need to use it. The real opportunity for AI + FHIR is: * Preventing unnecessary ER visits * Supporting preventative care * Giving patients usable access to their data to power their self care * Enabling decision support before care becomes expensive Where AI Changes Healthcare First According to Max, the most immediate impact won’t be in replacing doctors. It will be in: * Extracting structured FHIR data from unstructured inputs * Real-time scene and event understanding (AI + spatial awareness) * Reducing overload in emergency systems * Supporting remote diagnostics and distributed care models * Turning patient data into actionable, evidence-based guidance We’re moving from: “How do we move data between systems?”to“How do we use this data to keep people out of the system?” The Future of FHIR: Less Open, More Precise We also discussed the direction of FHIR R6 and the move toward tighter, more stable core resources while allowing innovation to happen in defined spaces. Max’s view: this won’t reduce innovation it will accelerate it. Builders will have more certainty that what they implement won’t shift under them, while AI makes data mapping across standards increasingly trivial. A Global View Having worked across Europe and now the U.S., Max sees strengths and weaknesses in both systems. What’s clear is that: Both systems need better use of data, and patients need more control and transparency. That’s a central theme of Max Health and why he remains deeply committed to open source and global standardization efforts. Where to Find Max * Newsletter: maxhealth.tech * LinkedIn: Max Nussbaumer * Conferences, connectathons, and anywhere FHIR builders gather The Big Takeaway This episode wasn’t about FHIR history. It was about this moment. AI has arrived at the exact time when healthcare finally has a usable data standard. The combination means we can stop talking about interoperability as a goal and start using it as a foundation to solve real problems. And the people who understand both the data and the problems are about to build very quickly. Get full access to FHIR IQ playbook at evestel.substack.com/subscribe

    28 min
  2. Episode 22 - Chris Hutchins

    JAN 21

    Episode 22 - Chris Hutchins

    Top 10 Takeaways: COVID, Data, and the Coming AI Reckoning in Healthcare 1) Healthcare didn’t lack data. It lacked urgency.The pandemic didn’t introduce new analytics capabilities. It changed the cost of being slow. When delay becomes lethal, organizations suddenly discover they can make decisions in hours instead of quarters. That tells you something uncomfortable: speed was optional until it wasn’t. 2) The winning move wasn’t better dashboards. It was deciding which questions mattered.Pre-COVID analytics chased curiosity. During COVID, analytics chased survival. The shift wasn’t technical sophistication it was ruthless prioritization. Moneyball lesson: when resources are constrained, focus beats breadth every time. 3) Interoperability works best when you shrink the problem space.Northwell didn’t unify 70+ EHRs. They built a currently admitted patient index a small, high-value dataset tied directly to decisions. That’s classic systems strategy: optimize the part of the system where leverage is highest. 4) Real-time analytics requires trust more than compute.Two daily huddles. Locked pipelines. Tight access controls. The goal wasn’t “more data.” It was shared belief in a small number of metrics. In complex systems, trust is the scarcest input. 5) AI turns data quality from a nuisance into a risk multiplier.Bad data used to waste time. Now it produces confident, well-phrased errors at scale. AI doesn’t clean your data it accelerates whatever state your data is already in. This changes the ROI math on governance overnight. 6) The most dangerous bias isn’t malicious. It’s missing context.Models assume you’ve provided enough information. Healthcare almost never does. Missing baselines, fragmented history, and unspoken nuance quietly distort outputs. This is the hidden error term no benchmark fully captures. 7) Consumer AI creates a parallel healthcare system with no referee.Patients are already using AI for triage, interpretation, and reassurance outside clinical workflows. There’s no visibility, no accountability, and no feedback loop when the model is wrong. That shadow system will shape outcomes whether clinicians like it or not. 8) Accountability in healthcare AI is misaligned and unstable.Clinicians and health systems bear liability once AI output enters care. Vendors largely don’t. Patients bear risk when they self-diagnose with consumer tools. That imbalance won’t survive contact with real harm. Regulation is coming but likely late and blunt. 9) AI exposes healthcare’s incentive structure, not just its data gaps.If AI reduces unnecessary visits, insurers benefit first. If it increases demand through anxiety, providers feel the strain. Like Moneyball, the advantage won’t come from better tools it will come from understanding who wins and loses under new rules. 10) The real competitive advantage isn’t smarter models. It’s judgment.AI can summarize, predict, and suggest. It can’t know what matters most right now. The organizations that win won’t be the ones with the fanciest AI. They’ll be the ones that combine clean data, tight feedback loops, and humans who know when not to trust the machine. Get full access to FHIR IQ playbook at evestel.substack.com/subscribe

    44 min
  3. Episode 21 - Pooja Babbrah

    JAN 12

    Episode 21 - Pooja Babbrah

    In Episode 21 of Out of the FHIR, I sat down with Pooja Babbrah, Executive Vice President of Strategy and Industry Alignment for NCPDP. We bonded over our shared history in the pharmacy world dating back to the rivalry between Medco and PCS and dug deep into why pharmacy is the sleeping giant of healthcare interoperability. Here are the key takeaways from our conversation: 1. Pharmacists Are Care Team Members, Not Just Dispensers We often view pharmacy as a transactional space, but Pooja highlighted the shift toward clinical services. From COVID vaccinations to managing chronic conditions, pharmacists are often the most accessible healthcare providers in rural communities. However, to fully integrate them into the care team, they need access to clinical data (labs, diagnosis) that currently lives trapped in the EHR. 2. The “Better Together” Story: NCPDP + FHIR A common question Pooja gets is: “Why don’t we just do everything in FHIR?”. Her answer is crucial for architects to understand: * NCPDP has mastered real-time transactions over the last 40 years (claims adjudication, eligibility). You don’t fix what isn’t broken. * FHIR is the clinical bridge. It allows pharmacists to pull the clinical context needed for prior authorization or care coordination, which can then be wrapped into an NCPDP standard for the payer. It’s not an or; it’s an and. 3. The AI & Patient Empowerment Frontier We discussed the controversial but exciting potential of AI in pharmacy. While headlines panic about “AI refills,” the reality is that basic maintenance meds (like statins) are perfect candidates for auto-refill workflows, provided the pharmacist is looped in to check labs and vitals. Pooja and I both agreed that the “Holy Grail” is an AI agent that acts as a proactive partner scheduling appointments, reconciling meds, and reminding you to pick them up so caregivers aren’t left managing complex logistics alone. 4. Interoperability is a Business Problem, Not a Tech Problem I shared my recent nightmare trying to schedule a colonoscopy stuck in phone queues and filling out 50-question Word documents because the referral data didn’t move. Pooja noted that while the “pipes” (TEFCA, FHIR) are being built, the business incentives to share that data are still lagging. What’s Next? Keep an eye on the NCPDP Collab (a workflow-focused event in February) and the new consumer-facing real-time benefit check pilots. Get full access to FHIR IQ playbook at evestel.substack.com/subscribe

    32 min
  4. Episode 20 - Paulius Mui, MD - X Primary Care

    JAN 5

    Episode 20 - Paulius Mui, MD - X Primary Care

    This episode of Out of the FHIR features Paulius Mui, MD, a family physician and entrepreneur, exploring the critical intersection of clinical medicine, technology, and data standards. Dr. Mui shares his journey from residency to becoming a tech-savvy clinician and advocate for primary care, discussing the challenges of quality measurement, the evolving healthcare workforce, and how technologies like FHIR and AI scribes are transforming or failing to transform clinical practice. 🌶️ Spicy Takes * The Quality Measurement Farce: Gene points out the absurdity of current metrics, like ADHD “management” only requiring two follow-up visits a yeah a bar so low it’s practically meaningless. * The AI Scribe Illusion: A recent study suggests AI scribes don’t actually save physicians time; they just shift the workload from documenting during a visit to reviewing and editing after it. * The NP Training Gap: Dr. Mui highlights the concern over the “boom” in nurse practitioner programs with minimal in-person training compared to the rigorous, repetitive clinical hours required in traditional residency. * “Vibe Coding” vs. Healthcare Reality: While AI-assisted prototyping (vibe coding) is great for front-end ideas, the back-end healthcare infrastructure remains notoriously difficult and rigid. 💡 Key Takeaways * Innovation via Proximity: The most effective solutions come from those closest to the problem. Clinicians who understand both medical and technical workflows are best positioned to fix healthcare’s bottlenecks. * Skills-Intelligence for Quality: Healthcare should move away from just “checking boxes” and toward measuring specific competencies (like pattern recognition or antibiotic stewardship) to identify where clinicians need support. * Stop Reinventing the Plumbing: Healthtech startups shouldn’t have to rebuild back-end infrastructure (FHIR connectivity, etc.) from scratch. Standardized “plumbing” allows for faster innovation. * The Power of a “Beginner’s Mind”: Dr. Mui encourages experts to lead with inquiry. Writing and sharing simple questions often leads to deeper insights than trying to maintain an “expert” persona. * Sustainability is the Goal: With healthcare spending nearing a third of the US GDP, technology’s primary role must be to create a sustainable model that actually improves patient experience and clinical outcomes. Get full access to FHIR IQ playbook at evestel.substack.com/subscribe

    19 min
  5. 12/12/2025

    Episode 19 - with Aaron Neiderhiser and Phil Ballentine

    This week, I’m sharing a special conversation I had with Aaron Neiderhiser of Tuva Health and Phil Ballentine from Atropos Health (together they host the High Dimensional Health Data Podcast) . We’ve been trying to schedule this for months, and I’m glad we finally hit record because we got right into the weeds of why healthcare analytics is still so painful and how we are fixing it. If you’ve followed my work, you know I’m obsessed with the intersection of FHIR and Analytics. But there is often a disconnect between the “high priests” of standards and the data engineers trying to run SQL queries in relational databases. In this episode, we bridge that gap. We discuss: * The SQL on FHIR Conference: Why the industry is standardizing “View Definitions” to make FHIR portable across different data warehouses. * CQL vs. SQL: Why Clinical Quality Language is great for requirements, but SQL (aided by AI) is another way to execute at scale. * The “Dump Truck” Theory: Why APIs aren’t always the answer for analytics teams who just want bulk data access. * Automating Interop: How I’m using AI Agents to do the grunt work of mapping and flattening data, so you don’t have to wait on “Larry” (the fictional, overworked hospital IT admin) to run a report for you. It was a blast recording with the High Dimensional team they bring a refreshing, “not just drinking the FHIR Kool-Aid ” reality to the conversation that is often missing from standards discussions. Enjoy the listen! Gene Spicy Takes * The “Windows ME” of Standards: We discussed how the industry seems to be collectively skipping FHIR R5 (like Windows 95/98 to 2000) and waiting for FHIR R6 to become the normative standard, avoiding the “trough of disillusionment” associated with intermediate versions. * The “Larry” Bottleneck: We personified the interoperability problem as “Larry” the overworked IT guy at the health system who smokes two packs a day, takes three lunches, and ignores your ticket for a claims feed. The goal of Bulk FHIR is to bypass the “Larry problem,” but we aren’t quite there yet. * Phil’s Hot Take: In a moment of pure chaos, Phil claimed Windows ME was the best operating system ever made. (We agreed to disagree). Fun Facts & Why You Should Listen * The Portuguese Connection: I shared a story about meeting Grahame Grieve (the “Father of FHIR”) at a FHIR camp in Portugal, highlighting how the “open” nature of the standard was intentional, even if it creates headaches for data modelers today. * Real-Time Solutions: We discuss actual tools (like the Tuva Project and Health Samurai) that are solving these problems now, not just theoretically. * Why Listen: If you have ever stared at a nested JSON object and wondered how to get it into a dashboard without crying, this episode explains exactly how the industry is solving that problem. Get full access to FHIR IQ playbook at evestel.substack.com/subscribe

    53 min
  6. Michael Westover on the perils of vendor data sharing

    11/13/2025

    Michael Westover on the perils of vendor data sharing

    In today’s rapidly evolving healthcare landscape, the integration of data between payers and providers has become crucial for delivering value-based care. In this episode of the out of the fhir podcast, FHIR Data guy sits down with Michael Westover , VP of Payer Partnerships and Informatics at Providence, to discuss his journey in healthcare, the challenges of data integration, and strategies for successful value-based care. The Journey to Value-Based CareMichael Westover’s path to his current role began with a strong foundation in healthcare consulting, where he guided states and municipalities on healthcare benefits. His desire to be closer to the action led him to pursue an MBA with a healthcare emphasis, eventually joining a startup focused on data integration and analytics. Westover highlights the importance of understanding both the business and clinical sides of healthcare, stating that the business of healthcare differs significantly from patient care. Challenges of Data Integration One of the most pressing issues in healthcare today is the complexity and fragmentation of data systems. Westover describes the cumbersome process of sharing data with vendors, where a simple request for longitudinal data can take months to fulfill due to the vast number of different systems involved. He emphasizes that healthcare organizations often struggle with outdated methods of data exchange, relying on CSV files and manual queries that can lead to errors and inefficiencies. The Importance of StandardizationWestover advocates for standardizing data practices to improve interoperability. He notes that while there are national initiatives like TEFCA aimed at enhancing data exchange, there remains a significant gap in sharing the right data. By collaborating with payer partners to identify crucial data needs, Providence has successfully established strong relationships that benefit both parties. This collaboration allows for more accurate data exchange, which is essential for effective value-based care. Success Stories notable example of successful data integration is Providence’s partnership with Humana. Their collaboration focuses on using national data standards, such as FHIR, to streamline data exchange through standardized APIs. This approach enables both organizations to access and share critical information, such as member rosters and clinical data, efficiently. Westover explains that aligning incentives and fostering open communication have been key to this success, as both parties recognize the importance of accurate data in achieving high-quality patient care. Key Takeaways: Westover’s insights shed light on the vital role of data integration in advancing value-based care. Key takeaways include: 1. The journey to effective data integration requires a deep understanding of both clinical and business aspects of healthcare. 2. Standardizing data practices is essential for overcoming the challenges of fragmentation and inefficiency. 3. Building strong partnerships with payers can lead to improved data exchange and better patient outcomes. 4. Successful collaborations, like that between Providence and Humana, demonstrate the power of aligning incentives and fostering open communication. As the healthcare industry continues to adapt to value-based care models, the importance of effective data integration cannot be overstated. By learning from successful partnerships and advocating for standardized data practices, healthcare organizations can work together to improve patient outcomes and streamline operations. Get full access to FHIR IQ playbook at evestel.substack.com/subscribe

    43 min
  7. 11/07/2025

    Episode 17 - Eric Melymuk & John Dobak

    Welcome back to Out of the FHIR. This isn’t just any episode. This is a reunion. FHIR Data guy brings together two heavy-hitters from his past, Eric Melymuk Principal Engineer at Progyny and John Dobak Senior FHIR Analytics Engineer at b.Well a trio of veterans who all came up in the “bad old days” of HEDIS and traditional quality measurement. This is the story of a technology stack (and a mindset) that defined healthcare data for decades, and the new stack that’s poised to replace it. They dive deep into the messy, complicated, and fascinating transition from the world of custom SQL, claims data, and regulatory checklists to the new frontier of FHIR, CQL, and true clinical interoperability. Hot Takes * The “Mind Shift” Thesis: Perfectly stated by Eric, is that the move from traditional SQL-based reporting to FHIR + CQL (Clinical Quality Language) isn’t just a syntax change. It’s a fundamental mind shift away from “logic customized to my organization” and toward “universal clinical intent.” This is the unlock. * Beware the “Gray Water”: The biggest risk of the new FHIR-based world is creating “dirty FHIR data.” It’s data that is technically compliant (it passes the validator!) but is clinically useless. He calls this “gray water,” and it’s the next great crisis. Organizations treating FHIR as a low-cost, check-the-box “cost center” are just propagating this gray water downstream, poisoning the well for everyone else. * The “Consumer Reports” Blind Spot: For decades, HEDIS and Star Ratings have been the “Consumer Reports for healthcare” (John’s analogy). The problem? We’ve been hiding the magazine from the consumers. The real promise of FHIR isn’t just better back-end reporting; it’s finally putting that quality data into the hands of the patients making the decisions. * LLMs as the Co-pilot, Not the Pilot: ”Do we even need measures in the age of AI?” Yes. But AI and LLMs aren’t the replacement for clinicians or measures. They are the co-pilot (Eric’s term) that helps builders create the logic and test cases, and they may become the translator that finally makes this data understandable to a patient. * The Cultural Battle: This isn’t a technology problem; it’s a culture problem. The entire panel agrees: if your organization views FHIR and interoperability as a regulatory “cost center,” you’ve already lost. The winners will be the ones who find executive champions (Eric’s point) who understand this is a new product and the strategic foundation for everything that comes next. From Brittle SQL to a FHIR Future This conversation is a journey from the past to the future of healthcare data. Act 1: The Old World (The HEDIS Grind) The guys reminisce about the “hardest problem” in health tech: traditional quality reporting. It was a world of brittle, custom-built SQL engines, siloed (and non-technical) quality departments, and a total dependency on claims data not because it was the best data, but because it was the only consistent data. Act 2: The New Stack (The FHIR/CQL Unlock) Gene pivots the conversation to the “new stack.” The difference is night and day. * Old Way: NCQA hands you a 200-page book (Volume 2) and says, “Good luck.” You have to design the schema, the logic, the whole thing. * New Way: NCQA hands you the code. The schema is the FHIR Implementation Guide (IG). The logic is the executable CQL file. The entire low-level, error-prone interpretation is abstracted away. Act 3: The Messy Middle (The “Gray Water” Problem) But this transition is where the real drama is. The panel identifies two massive risks: * The Data Itself: We’re moving from clean claims data to messy, unstructured clinical (EHR) data. The old logic (built on claims “artifacts” like Place of Service codes) simply doesn’t map. * The “Cost Center” Trap: Because of regulatory mandates, organizations are scrambling to create FHIR data. They’re doing it cheap, fast, and without clinical governance. This creates John’s “gray water”FHIR bundles that are valid but meaningless, which will break everything downstream. Act 4: The Real Goal The episode concludes by refocusing on the why. Eric makes the passionate case that we’ve “lost sight” of the goal. It’s not about checking boxes for payment; it’s about improving care. The new stack (FHIR, CQL) is the first real chance to build systems that give data back to providers and patients in real-time, finally fulfilling the original promise of quality measurement. The Playbook: Learnings from the HEDIS OGs * 1. Don’t Replace the Warehouse, Feed It. This is a key strategic insight from John. CQL and FHIR do not replace your SQL data warehouse. They work together. Use the CQL engine to process the messy, real-time FHIR data, and then use the output (the FHIR MeasureReport resources) to feed your traditional SQL warehouse for population-level analytics. It’s the best of both worlds. 2. Your FHIR Implementation Is Your Product. The panel’s biggest warning: do not treat your FHIR implementation as a “cost center” or an IT project. It is a product. It requires governance, clinical input, and executive champions. If you don’t, you’ll spend millions building a “dirty data” engine that provides no value. * 3. Use the EOB as Your Bridge. How do you get from a claims-based world to a clinical-data world? Eric points to the bridge: the ExplanationOfBenefit (EOB) FHIR resource. It’s designed to model adjudicated claims. This allows you to “dip your toe in” by mapping your existing, clean claims data into a FHIR structure first, before you tackle the mess of raw EHR data. 4. Get Your Feet Dirty (The Community is Open). The single best way to learn is to do. The HL7 FHIR community (on Zulip) is famously open. As John notes, you can even feed an entire Implementation Guide into an LLM and start asking it questions. The barrier to entry has never been lower. Get full access to FHIR IQ playbook at evestel.substack.com/subscribe

    31 min
  8. Episode 16 - From Blue Button to Bulk FHIR with Mark Scrimshire

    10/29/2025

    Episode 16 - From Blue Button to Bulk FHIR with Mark Scrimshire

    In this episode, I speak with Mark Scrimshire, Chief Interoperability Officer at Onyx, about his extensive journey in healthcare interoperability, the evolution of data sharing standards, and the future impact of regulations and technology. Mark Scrimshire’s Journey to FHIR® Mark recounts his two-decade career, which provides a vivid history of modern interoperability. His journey began around 2009 during the American Recovery Act, where early initiatives like CMS’s “Blue Button 1.0” allowed patients to download their claims history—often as a massive, unusable text file thousands of pages long. His pivotal moment came as an Entrepreneur in Residence at CMS, where he was tasked with building a modern API for Medicare beneficiaries. Instead of creating a proprietary standard, he chose to adopt the emerging HL7® FHIR® standard. This project evolved into Blue Button 2.0, a landmark API that proved the viability of using FHIR® at a national scale. He was instrumental in defining key resources like the Explanation of Benefit.. This work at CMS laid the groundwork for the 2020 CMS Interoperability and Patient Access final rule, which mandated that payers provide patient access via FHIR® APIs. Seeing this regulatory shift coming, Mark co-founded Onyx to build a platform that helps healthcare organizations comply with these rules and leverage the new data-sharing paradigm. The Power of Regulation as a Catalyst A central theme of the conversation is the role of government regulation in driving change. Mark argues that mandates are essential for overcoming industry inertia. He uses the upcoming Prior Authorization rule as a key example. While the rule only mandates the API for certain government-funded plans, he predicts that the efficiency gains (getting an answer in 15 seconds via an API versus days via fax) will create immense market pressure for payers to offer the same capability for their commercial plans. This transforms a compliance requirement into a strategic business transformation. Interesting Observations * Flipping the Script on Data Integration: Mark powerfully articulates a common problem in healthcare IT: an “80/20 rule” where organizations spend 80% of their effort just trying to get the data and only 20% actually using it for analysis and insight. He argues that standardized FHIR® APIs and trust frameworks are designed to “flip this script,” allowing organizations to spend only 20% of their effort on connectivity and 80% on creating value from the data. * The Core Challenge is Trust, Not Technology: Mark asserts that the biggest barrier to seamless interoperability is not a lack of technology but a lack of scalable trust. Establishing individual connections between thousands of payers and providers is a manual, time-consuming process that costs “man-years” of effort. The solution lies in building robust trust frameworks (like TEFCA or security protocols like UDAP) where an entity can be vetted once and then securely connect with anyone else in the network, dramatically reducing friction. * Regulation as a “Bridgehead” for Market Transformation: Mark views regulations not as the end goal but as a “bridgehead” a starting point that establishes a new technical and business reality. Once the infrastructure (like FHIR® APIs) is in place due to a mandate, the market naturally finds innovative and more efficient ways to use it, pushing adoption far beyond the original scope of the rule. * FHIR® as an Enabler for AI, Not a Relic: Addressing the question of whether AI makes standards obsolete, Mark argues the opposite. He states that having well-structured, standardized data from FHIR® APIs makes AI more efficient, accurate, and less resource-intensive. Without standards, AI models would have to waste immense computational power on parsing unstructured documents (like PDFs) and de-identifying data, a process FHIR® makes unnecessary. Standardized data is the clean, reliable fuel that will power the next generation of healthcare AI. Get full access to FHIR IQ playbook at evestel.substack.com/subscribe

    26 min

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