Ed Gutierrez

New Post: Adaptive Queue‑Management for Federally Qualified Health Centers: A Real‑Time Scheduling Framework and Its Impact on Primary Care Access - ## Abstract Access to primary‑care services in underserved regions is often limited by static scheduling, constrained workforce capacity, and fragmented patient‑flow processes. This exploratory research scaffold presents a synthetic, simulated, and projected roadmap that \(a\) ingests structured electronic‑health‑record \(EHR\) fields, unstructured clinical notes, and patient‑reported outcome telemetry, \(b\) transforms these inputs into a graph‑based semantic \[…\] \[Source & Legal Disclaimer\] This is an AI-generated simulation research dataset provided by Freederia.com, released under the Apache 2.0 License. Users may freely modify and commercially use this data \(including patenting novel improvements\); however, obtaining exclusive patent rights on the original raw data itself is prohibited. As this is AI-simulated data, users are strictly responsible for independently verifying existing copyrights and patents before use. The provider assumes no legal liability. For future Enterprise API access and bulk dataset purchase inquiries, please contact Freederia.com.

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AMCP Partnership Forum Addresses Gaps in Adoption of Precision Medicine. Alexandria, Va., June 26, 2025 — AMCP convened a diverse group of stakeholders for its Precision Medicine Partnership Forum to examine solutions that improve access, consistency, and quality in precision oncology. Attendees included patients, payers, pharmacy benefit managers, providers, pathologists, laboratory benefit managers, and leaders from advocacy organizations, coalitions, and professional associations. The multi-session event focused on aligning clinical guidelines, diagnostics, and managed care processes to ensure that innovation in cancer care leads to meaningful, equitable outcomes for patients. Forum participants explored persistent challenges across the precision medicine access ecosystem, particularly in oncology. Experts pointed to fragmentation and misalignment as key contributors to care gaps, using the example of non-small cell lung cancer (NSCLC), and emphasized the need for system-level changes that better inform clinical decision making, reduce time to initiation with targeted therapies, and support guideline-concordant care. Attendees recommended deeper collaboration between clinical organizations and managed care to support the uptake of biomarker testing, standardize a vernacular for stakeholders, and develop national quality standards to ensure clinical utility and enhance patient outcomes. “We need to accelerate how we align care with clinical evidence, advance pathologist-initiated biomarker testing at diagnosis, and elevate precision medicine to improve patient outcomes,” said AMCP CEO Susan Cantrell, RPh, CAE. “The more precise the treatment, the better the likelihood that a patient reaches a successful outcome. Getting the right people together for these critical conversations is essential to AMCP’s mission to ensure patients get the therapies they need at a cost they can afford.” AMCP will carry the momentum forward by integrating precision medicine across its research, advocacy, education, and convening platforms, including Nexus 2025, AMCP 2026, and virtual training opportunities. Additional efforts include collaborating with key partners, including the National Comprehensive Cancer Network (NCCN), the Association of Cancer Care Centers (ACCC), the Association for Molecular Pathology (AMP), and the American Society for Clinical Pathology (ASCP), to continue to address precision medicine care gaps. AMCP would like to thank Valuate Health Consultancy for assisting with the development and moderation of the Forum. Thank you to our generous sponsors: AbbVie, AstraZeneca, Genentech, Illumina, Johnson & Johnson, KlearTrust, Lilly, Merck, Pfizer, and Sanofi. Their support for this vital topic paves the way for more equitable and accessible treatment plans in oncology and beyond.

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At Ignite, Microsoft showcased how partnerships across industries are driving the next wave of AI transformation. Epic stood out as a healthcare leader, with Seth Hain and Jackie Gerhart demonstrating how intelligent platforms can empower clinicians, streamline workflows, and ultimately improve patient outcomes. This isn’t just about technology, it’s about redefining care delivery and enabling organizations to focus on what matters most, patients. #Microsoft #Healthcare #AI

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The recent release of Claude for Healthcare has garnered significant attention, particularly due to its claim of 99%+ accuracy in ICD10 code prediction. While there are numerous discussions addressing these inflated claims, further exploration led me to the situation with Gemini, which has made-up a new definition for MCP. Some of the investigations into these AI technologies seem to be veering into the absurd, as AI-generated responses are becoming indistinguishable, but often blatantly flawed, from traditional document-based retrieval methods.

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It was great to talk at HLTH Inc. USA about how we're moving from operating tools to supervising intelligent systems in the revenue cycle. This is the next step in a long productivity journey, shifting our teams from "assistance" and "operate" to "supervise." The complexity of medical coding—with its near-infinite combinations of ICD-10 codes and payer rules—can't be solved by brute force. It requires a new approach. We're developing agentic AI that uses a combination of purpose-built neural networks and tuned LLMs to make decisions within a "capture-to-code" workflow. These agents can determine if a claim is ready for billing and can be sent straight through to the EMR. Or they can intelligently flag a record for documentation clarification or expert review, preventing denials before they happen. It's about empowering our teams with systems that don't just automate tasks but make informed decisions. #HLTHUSA #AIHealthcare #RevenueCycle #Solver LinkedIn profile(s) to tag (highlighted in red):  HLTH Inc. Solventum Travis Bias

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Oracle Health just dropped a from-scratch, AI-driven, voice-first EHR for ambulatory care — not an upgrade, not a patch — a full rebuild on Oracle Cloud. This move raises two big questions: - Can Oracle keep its current customers from jumping ship? - Will targeting ambulatory care & smaller hospitals (vs. large AMCs) prove a smarter entry point — especially when bundling EMR + ERP?

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When lives depend on speed and reliability, infrastructure matters. Franciscan Health migrated critical workloads to Azure Virtual Machines, gaining: ✅ High availability for patient-facing apps ✅ Cost efficiency with flexible scaling ✅ Stronger security & compliance for sensitive health data This move isn’t just modernization—it’s a foundation for better care and future innovation. 🔗 https://msft.it/6043QulYh #Microsoft #Azure #VirtualMachines #HealthcareInnovation #CustomerStory #CloudTransformation #MicrosoftEmployee

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Oracle has introduced a new Electronic Health Record (EHR) system for ambulatory providers in the U.S., incorporating AI technology to enhance efficiency and minimize administrative burdens. The cloud-based platform, established on Oracle Cloud Infrastructure, integrates voice commands enabling healthcare professionals to swiftly access patient data like lab results and medications, eliminating the need to navigate through multiple interfaces. According to a news release on Aug. 13, Oracle emphasized that the system's AI agents offer contextual insights and automate tasks, empowering physicians to prioritize patient care. Learn more about this development at the link provided. #HealthTech #AI #EHRs https://lnkd.in/ensm8Vsn

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In the latest episode(#206) of The Big Unlock Podcast, I had an engaging conversation with Bharat Sutariya, Senior Vice President and Chief Health Officer at Oracle Health, on how AI is reshaping the future of healthcare delivery. Dr Sutariya shared his origin story with us and told us what led him to tech was his relentless focus and impatience to improve healthcare. “Right from the time when the monitors had green screens, with the CRT machines delivering lab reports, not working and the printer not working. Back in the residency days to now, I always had very little patience for things that don't work and always thought that patients deserve better. Our providers deserve better, and we need to reshape healthcare. So in that relentless drive to improve healthcare? I've always looked at, you know, technology as the most scalable answer to that problem. So that's what got me into technology from the early days of my residency. Then leading tech transformation at Detroit Medical Center and then onward.” Dr. Sutariya stated that healthcare is moving beyond systems of record toward systems of orchestration, where AI is no longer just documenting care, but actively helping coordinate workflows, reduce friction, and support clinicians in real time. We also discussed why simply “bolting AI onto legacy systems” may only deliver incremental change, while true transformation requires rethinking the entire healthcare technology ecosystem with AI embedded at its core. I found especially compelling the vision of moving ambient AI beyond note-taking into intelligent orchestration, from automatically preparing orders and referrals to streamlining prior authorization workflows, all while keeping humans firmly in the loop. Lots more to unpack  - take a listen! Listen to the full episode: https://lnkd.in/gVWJug3h #TheBigUnlock #AIinHealthcare #DigitalHealth #OracleHealth #HealthcareInnovation BigRio Damo Consulting Inc.

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Optum Frontier Therapies has been selected by PTC Therapeutics to distribute Sephience™ , a treatment the FDA approved on July 28 for a rare disorder called phenylketonuria (PKU), which prevents the body from breaking down phenylalanine (phe), an amino acid found in most proteins. There are an estimated 58,000 people living with PKU globally. Our ability to distribute this treatment will allow us to serve more patients and advance our mission of supporting people living with complex and rare diseases.

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Health Tech Policy Peeps: EHI Exports are supposed to include patient/provider secure message history (i.e., portal messages), yes? I've been pulling b(10) export documentation from the CHPL API and looking at what certified EHR products actually document as included in their EHI exports. athenahealth's Patient Engagement page (https://lnkd.in/dEG3kN_j) describes secure messaging as a core feature of their patient portal, integrated into athenaOne — which they market as their "fully-integrated EHR, medical billing & practice management, and patient engagement solution." But their EHI export documentation (https://lnkd.in/d9zThuJS) lists four export types spanning about 129 datasets, and I don't see secure messages in any of them. [EDIT: Thanks to Joe Ganley in comments, who clarifies that portal messages appear as "Patient Cases"! https://lnkd.in/gRTzJF75 does not make this evident, but I'm delighted to know that it exists. Documentation is hard, and public examples alongside the public documentation would help. Read on for background, since I'll have the same questions about other EHRs as I proceed with a cross-cutting analysis.] --- The certification criterion at 170.315(b)(10) requires exporting "all of a single patient's electronic health information that can be stored at the time of certification by the product, of which the Health IT Module is a part." The preamble to the Cures Act Final Rule (85 FR 25642) drives the point home: the export scope "is agnostic as to whether the EHI is stored in or by the certified Health IT Module or in or by any of the other 'non-certified' capabilities of the health IT product of which the certified Health IT Module is a part."

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The Evolution of the "Glass Box": Moving from Algorithms to Provenance. At the ASTP annual meeting last week, amidst great conversations, including a fantastic lunch with Amy Gleason, one theme kept surfacing: how do we practically operationalize trust in healthcare AI? We just formalized our thoughts on this in Penguin Ai's response to the ASTP/ONC Request for Information. Our core argument is that healthcare must reject "Black Box" AI in favor of strict transparency. But as we drafted our submission, I found myself questioning the industry's terminology. We all ask for "Glass Box" AI, but is that actually the correct term for what we need? In computer science, a "glass box" refers to how a model processes a prompt. It means the algorithm itself is simple and mathematically interpretable, like a decision tree. But to solve complex healthcare problems - like parsing a 200-page patient history for prospective HCC coding or cross-referencing payer guidelines for a clinical appeal - we have to use advanced foundational models. The models themselves are often opaque. What healthcare truly requires isn't just algorithmic interpretability. We need Evidence Traceability. A medical coder or a physician doesn't need to understand the neural network's vector weights. They need deterministic proof. If the AI suggests a diagnosis code, it must instantly link that output back to the exact, human-verified sentence in the source record, allowing them to pinpoint the exact bounding-box coordinates of the evidence. At #Penguin Ai we call it the “Glass Box” because it immediately signals transparency. But fundamentally, we are advancing the market's pursuit of data provenance. True traceability is what allows an AI to safely move from a 'read-only' sidecar to an active participant. Are we as an industry conflating model explainability with data traceability? And when it comes to clinical adoption, does the distinction matter as long as the human-in-the-loop can instantly verify the evidence? Would love to hear how other leaders are navigating this. #HealthIT

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