Tim Riddle

Having sat on both sides of the table - trust me when I say, most providers have no idea how much leverage they're leaving behind. Payor price transparency data is real, it's accessible, and it changes everything about how contract negotiations should work. The problem? Too many providers have been burned by bad data and overpromising vendors, so they've written the dang whole thing off. That's exactly why I came out of retirement for this. Pete nails it here. Give it a read.

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Attaining high quality in your Master Patient Index is critical for clinical safety and operational efficiency and quality. A small amount of duplication (eg 1-2%) of patient records is unavoidable. We are only human after all. But so many master patient indexes accumulate levels of 10-15% duplication over years of operation, and critical incidents or sentinel events start regularly cropping up because too many patients have an important allergy or a diagnosis that's buried in one record whilst another of their identities is in the one being seen by clinicians. As Darren Devitt out in this post, it can take a bit of work to make your FHIR implementation effectively handle the $merge operation that is integral to good master data management (MDM) for patients. Good MDM processes and discipline are integral to all healthcare data, and transcend FHIR adoption; but don't let your FHIR interoperability strategy be associated with fragmented patient records and ultimately derailed. $merge, Patient.Link, Linkage resource and Person Resource are powerful tools that your organisation can apply to achieve high master patient index integrity using FHIR. And then you can get stuck into unmerge of incorrect merges 😜

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There’s a lot of excitement about #AI in healthcare right now. And there should be. We’re seeing new tools, new use cases, and new opportunities every day. But here’s what I’ve learned from leading teams in this space: It’s not the tech that makes or breaks implementation. It’s engaging with and gaining the trust of the right people. The teams. The workflows. The conversations. The trust. Most AI efforts will stall not because the model was wrong, but because the process didn’t include the people doing the work. → The scheduler who’s juggling 50 calls an hour. → The nurse who’s managing four complex patients at once. → The manager trying to balance patient care, staffing, and operations. These are the people who know what needs fixing. And they’re the ones who will carry the change forward.... if we include them. Technical skills are table stakes. But collaboration, listening, and clear communication? That’s where AI projects actually succeed. It’s easy to chase a breakthrough and get hyped up about something that could be exciting. It’s harder to engage the key stakeholders and build something the team believes in. But that’s the work. That’s what makes it real. The future of healthcare AI won’t just be engineered. It will be co-created.

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On Wednesday, over 60 health tech companies signed a pledge orchestrated by the Centers for Medicare and Medicaid Services to make health data-sharing easier and to build apps for patients to access and act on their health data. CMS Administrator Mehmet Oz said in a press release that the agreement signals a coming “paradigm shift in the U.S. healthcare system.” Some of the biggest names in health care and technology agreed to the pledge, including Amazon, Apple, Google, OpenAI, Epic, Microsoft, CVS Health, and UnitedHealth Group

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Becker’s shared how UnitedHealth Group is helping to transform healthcare with AI. Crimson AI is a prime example: one health system in New York leveraged the predictive analytics solution to identify patterns of waste and reduce operative supply spending by 16%.   Built on responsible AI principles and a human-centered approach, Crimson AI demonstrates what can be possible when technology and insights come together.   Read more at Becker’s: https://lnkd.in/eRbrqqer    #HealthcareInnovation #CrimsonAI #Optum #PredictiveAnalytics #SmartHospitals #HealthTech #AIinHealthcare #OREfficiency #DigitalHealth #HealthcareIT

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Proud to share this independent study that shows how our AI-enabled platform eHealth Connect® is driving measurable results—faster care, greater efficiency, and healthier bottom lines. 

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Why your EHR "AI-Ready" data might be your biggest liability……. We are moving into an era where "buying a model" is the easy part. The real challenge—the one that determines if your AI actually works in the ER or just fails in the lab—is overcoming Representational Debt. This is the technical "interest" we pay when we try to use data built for billing and storage to drive intelligent clinical decisions. Most hospital IT teams find that their EHR data, while massive, is fundamentally "noisy" for AI. If we want to build systems that doctors actually trust, we have to solve three core engineering problems within our data pipelines: The Ontological Gap: Moving beyond Billing Codes Most hospital data is structured around the Revenue Cycle (ICD-10/CPT codes). The problem? These codes are "proxies" for payment, not clinical ground truth. We need orchestration that bridges this gap by extracting actual clinical intent from unstructured physician notes and lab trends. Temporal Resolution: Unlike a stock market feed, patient vitals might be recorded every minute during a crisis and then not at all for twelve hours. Standard AI models hate these gaps and often "hallucinate" averages to fill them. A truly Time-Aware Pipeline doesn't just fill gaps; it treats the time between events as a vital piece of information. Data Leakage: Data leakage occurs when a model accidentally sees "the answer" in the training set before it's supposed to. We must engineer strict Temporal Fences in our data orchestration to ensure the AI only sees what the clinician saw at that exact micro-second. The Expert Take: A "Foundation Model" is only as effective as the Clinical Feature Store supporting it. In 2026, the hospitals that see a real ROI won't be the ones with the biggest GPUs; they will be the ones with the most sophisticated Data Orchestration. The Question for CMIOs, CIOs Is your team spending 80% of their time on the model, or 80% on the data pipeline? #HealthIT #HealthcareAI #DataEngineering #CIO #CMIO #MLOps #DigitalHealth #HealthcareIT #UShealthcare Nutek Healthcare

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Great article from HLTH about how the lack of interoperability of healthcare data limits the possibilities to transform health outcomes and streamline care. https://bit.ly/3HCns5l At synseer, we are building an ecosystem that collects data not only from synseer wearables, but from other popular wearables as well. That way, consumers can use the totality of their data to improve their health and wellness. Looking forward to having synseer participate in more discussions on this issue at October’s HLTH innovation conference. Be sure to stop by to talk to our CMO, Jim Hickey, at the synseer booth at HLTH's Start-up Pavilion. #synseer #healthcare #data #wearables #digitalhealth #HLTHUSA

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Identity is the foundation of digital trust in #healthcare #interoperability. Our partnership with Verato ensures that when data moves, it can be trusted.

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Important Development - CMS leaning-in to technology-enabled clinical care The Center for Medicare and Medicaid Innovation (CMMI) recently announced an important new program called the ACCESS initiative that attempts to drive better chronic disease care and outcomes for Medicare members through technology-enabled care models. The program has a few key features: 1. Aligns payments with clinical outcomes (as opposed to fee-for-service) 2. Opens the door for ACCESS Care organizations who will take responsibility for managing a pts chronic condition but with more flexibility on how they do it and what technologies they use 3. Meant to “complement” traditional care - PCPs can refer clinicians to ACCESS orgs and receive regular updates and may bill a new-management payment for coordinating care with these orgs.  4. Will focus on 4 clinical tracks - early cardio-metabolic conditions (HTN, HL, obesity and pre-DM); cardio-metabolic conditions (DM, CKD, ASVD), MSK conditions (chronic Back pain), and BH conditions (Depression and Anxiety). While it’s great to see CMS enable greater flexibility for technology-enabled, outcome-driven care - will this model inadvertently WORSEN fragmentation of care? Especially those with multiple conditions, is there a risk in them getting DM management from one clinic; their behavioral health care from another, all the while having a PCP try to play quarterback and manage everything else? https://lnkd.in/giTW7nEp

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Thank you Sarah Moors from Digital Health Insights for taking a deeper dive into the patient privacy ramifications of CMS's new "Make Health Tech Great Again" initiative. Healthcare organizations must still protect data privacy. The HIPAA rules are still in place. I love these specific take aways from your article. 😳Many consumer health apps fall outside HIPAA protections, meaning sensitive patient data could end up sold to advertisers or used in ways patients never intended.  😳This is a test of responsibility. Access to richer patient data could enable more personalized AI tools and remote monitoring, but companies that cut corners on privacy could face regulatory backlash and consumer rejection.  😳Can the administration balance innovation with protection for vulnerable populations? Read Sarah's entire article here. #patientprivacy #dataprivacy #interoperability #makehealthtechgreatagain Stephanie Kindlick Anthony Murray Hassan F. Abdallah JD, CHC, FACHDM Jillian Schmitt Moliehi Weitnauer Angela Rose, MHA, RHIA, CHPS, FAHIMA https://lnkd.in/gvhrRzat

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Becker's Healthcare recently highlighted how UnitedHealth Group is investing $1.5B in AI this year — not as a side experiment, but as a way to rethink how core processes work across the enterprise. For me, the focus is on applying AI where it can make a meaningful difference: simplifying administrative work, improving speed and accuracy and helping people navigate care more easily. When done thoughtfully and responsibly, AI has the potential to reduce friction for providers, employers and members alike. Thoughtful reporting on where this investment is headed and why it matters: https://lnkd.in/dbMedMDx

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Infrastructure seems to be all the buzz in digital health talks. I say this somewhat tongue in cheek as it always was discussed. But I see multiple talks and articles highlighting building the right infrastructure recently. Anyway, CMS and HHS are talking about it too - they recently outlined major new initiatives aimed at modernizing healthcare infrastructure including: - National provider directory - Modern ID for Medicare beneficiaries - Digital Insurance cards with real-time coverage info - Streamlined ID models (like Login.gov) so that people can verify their identiy once and use it across multiple systems. - Scaling up bringing real-time claims data directly into clinical workflows - Trusted data exchange to improve interoperability and data sharing. All great stuff and as Rebecca E. Gwilt said 'no notes'. Except maybe how did we not have this before. Ah yes, because now we are catching up on the infrastructure. 🤷🏽‍♀️ #digitalhealth #healthtech #CMS #interoperability #telehealth #datasharing #healthcareinnovation https://lnkd.in/eGjbSxt7

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🚨 CMS just froze all MA risk adjustment data corrections (RAPS/EDPS + RAOR) for PY 2020-2024 CMS RAPS | Who’s already retooling their GTM playbook to support audit resilience? 🚨 Translation: Health Plans can’t fix submissions or report overpayments until RADV samples are finalized. Obligations under SSA §1128J(d) + 42 CFR 422.326 still stand. Why it matters for MedTech & Digital Health: 📉 Pipelines stall: Risk Adjustment optimization tools look non-urgent - expect delayed deal cycles. 🔎 Audit pressure spikes: Vendors must pivot from “speed” to “substantiation” or risk commoditization. 💸 Revenue models will be strained: Usage-based SaaS and CAPEX diagnostic tech hit pause under margin-tight HCC V28 shifts. 🏥 ACO/VBC buyers push harder for integrated diagnostic-to-contracting solutions or they’ll stick with incumbents. Strategic considerations: 1️⃣ Short-term: Bundle audit readiness into renewals, educate on non-sampled overpayment tactics. 2️⃣ Mid-term: Shift to SaaS+services for RADV defense, align to MSO-PC models. 3️⃣ Long-term: Develop a Market Access and Reimbursement Strategy for new CPT/HCPCS enablement, while waiting for CMS to lift the freeze. 👉 This “pause” isn’t neutral, but rather reshapes how diagnostic and RA vendors prove value! Thank you to Prince Baawuah, DrPH, MPH, CSM® for highlighting this notice #MedicareAdvantage #RiskAdjustment #DigitalHealth #MedTech #ValueBasedCare #MarketAccess #ReimbursementStrategy

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Prior authorization is becoming increasingly data-driven. Organizations that leverage this data effectively will outperform those that rely on manual processes alone. I focus on building intelligence through: ✔ Analysis of approval and denial trends across payers ✔ Identification of high-risk services requiring enhanced documentation ✔ Predictive insights to anticipate authorization challenges This allows organizations to move from reactive to proactive management. Instead of responding to denials, they prevent them. Instead of managing delays, they anticipate them. Data transforms authorization from a task into a strategic function. That shift is critical for future performance. #HealthcareAnalytics #PriorAuthorization #RCMStrategy #DataDriven #HealthcareLeadership #UtilizationManagement #PredictiveInsights #RevenueIntegrity

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Three stories from this week that are really the same story: CMS refreshed the Prior Authorization for Drugs proposed rule on April 23 with technical workflows and metrics guidance. Payers will report FHIR API endpoints and usage metrics to CMS, with specific Implementation Guides mandated and sunset dates for older versions. Hospital price transparency enforcement started April 1. Machine-readable files now need median, 10th, and 90th percentile allowed amounts when charges are negotiated as percentages or algorithms. Type 2 NPIs encoded. A senior official on the hook for accuracy. Meanwhile Utah passed an AI insurance disclosure law. Indiana banned AI-sole-basis claim downcoding. Alabama set parameters for AI in prior auth. California SB 942 and Texas HB 149 are already in effect. The theme is the same. Every data point in healthcare is being pushed toward machine-readable, auditable, provenance-backed. Policies, benefit definitions, contract logic, claim reasoning, all of it. The platforms that matter in 2027 are not the ones with the slickest AI. They are the ones that can answer 'where did this number come from?' with a specific page, a specific paragraph, and a specific source, every single time. Show your work. That is the whole product. The industry needs an open standard for benefit plan content, not another closed black-box platform. Traceability by design, not by demo. #HealthTech #Interoperability #PriorAuthorization #PriceTransparency #HealthcareAI

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The pace at which AI is reshaping clinical care has rapidly accelerated over the past 12 months. AI-based technologies are enabling increasingly autonomous care delivery, making AI a critical tool for addressing gaps in workforce, expanding access, and improving patient outcomes. Yet achieving the full potential of clinical AI depends on building clinician confidence, gaining clarity about legal liability, and aligning payment models to value. Manatt Health was proud to support the Peterson Health Technology Institute (PHTI) in convening a roundtable discussion on the requirements for safe, effective, and scalable use of clinical AI. The discussion focused on mental health chat bots and autonomous hypertension management.  Four themes emerged from the discussion: 1️⃣ Evidence standards should compare AI to current standards of care and scale with clinical risk. 2️⃣ Performance benchmarks should be based on clinical outcomes, and safety standards should adapt as the evidence grows. 3️⃣ New technologies may be initially tested in lower-risk populations but should scale quickly to high-risk populations to maximize impact. 4️⃣ Widespread adoption will depend on building clinician confidence, gaining clarity about legal liability, and aligning payment models. Read the full proceedings here: https://lnkd.in/eWUURHrB Caroline Pearson, Prabhjot Singh, MD PhD, Julia Harris, Corinna Cline, Joshua Tauber, Naomi Newman, Allie (Levy) Chafetz, Lili Muskal

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CMS just published the FHIR Implementation Guide for the ACCESS Model APIs. Four APIs for the pipeline. Here's a layout The pipeline is as follows: Screen → Enroll → Report → Manage. Miss a step, miss payment. $check-eligibility — Pre-screen any Medicare beneficiary against 8 possible outcomes. This is non-binding. You're checking if the patient qualifies for your track (eCKM, CKM, MSK, or BH) before committing. $align — Formal enrollment. You submit at least one qualifying ICD-10 Condition resource. CMS may randomize the patient into a 12-month control group. If aligned, a 3-month lock-in starts and CMS auto-creates FHIR Subscriptions pushing you event notifications. $report-data — Submit PROMs, clinical outcomes, quality measures within defined windows. Miss the baseline report within 60 days of alignment and CMS automatically unaligns your patient. $unalign — There are four valid exit reasons: relocation, loss of contact, clinical exclusion (must include the disqualifying ICD-10), or patient-initiated (only after 90-day lock-in). The entire system runs on async processing: POST → 202 Accepted → poll $submission-status. OAuth 2.0 Client Credentials. FHIR R4. US Core 6.1.0. We're certainly building this now at RevelAi Health and Limber Health for MSK Access. Not after the July 2026 launch. Now. The subscription event architecture alone — baseline windows, quarterly cadence, lock-in expiry notifications — requires infrastructure your current systems likely don't have. Full interactive API map linked below. Engineering-level and executive-level views. And if you missed our webinar on MSK ACCESS that Dr. Marc Gruner, Dana Prommel Strauss, Benjamin Schwartz, MD, MBA, and Nirav J. Modi starred in-- you can still watch it by visiting the MSK ACCESS website and entering your email if you were one of the other 200 registrants, or request access now! #ACCESSModel #CMS #CMMI #HealthcareAI #FHIR #ValueBasedCare #MSK #OrthopedicSurgery #PopulationHealth #HealthIT

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