HHS Webinar June 25: What Did HHS Hear About AI in Clinical Care?
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AI Corner: Chat GPT 5.5
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The RFI was released December 19, 2025, and appeared in the Federal Register shortly afterward (12/23). Comments were due February 23, 2026.
Now HHS/ONC has scheduled a public webinar to discuss what it heard.
Webinar: Adoption of AI in Clinical Care: Updates from the HHS RFI
Date/time: Thursday, June 25, 2026, 3:00–4:00 pm ET, 12:00-1:00 PT
Registration entry point:
https://healthit.gov/event/adoption-of-ai-in-clinical-care-updates-from-the-hhs-rfi/
Why This RFI Matters
HHS framed the RFI as a “OneHHS” effort, meaning it was not just an FDA question, not just a CMS question, and not just an ONC question. The Department asked for input across the full health care AI ecosystem: developers, buyers, clinicians, health systems, patients, caregivers, payers, researchers, and others.
For reimbursement readers, the key point is that HHS explicitly put payment policy on the table. The RFI asked what payment or program design changes HHS should prioritize to incentivize effective AI use in clinical care. It also asked where AI tools have met or missed expectations for performance and cost, and what kinds of tools might improve outcomes, provide new quality insights, or reduce costs.
That is a broader frame than the usual narrow Medicare coding question. HHS was asking, in effect: if AI is going to become part of routine clinical care, what should federal payment systems do differently?
See the RFI text re: Reimbursement, below as Sidebar 1.
The Industry Wish List Begins to Appear
A March 2026 STAT Plus article by Mario Aguilar reviewed some of the RFI comments. STAT reported that about 7,300 comments had been submitted, although only a fraction were posted publicly at the time of the article.
The article described a familiar but important pattern: health tech companies used the RFI to ask for very concrete changes that would benefit their own business models. That is not a criticism; it is exactly what RFIs are for. The useful thing for policy readers is that the comments show where the industry thinks the current bottlenecks are.
Examples from the STAT summary included:
Abridge suggested that transcript-grounded clinical documentation could support more auditable risk adjustment, including social needs that are not always captured well in billing codes. It also suggested CMMI models for AI-enabled administrative simplification.
Aidoc argued that AI imaging tools need better reimbursement pathways and should not simply be bundled invisibly into existing imaging codes. It suggested payment pathways tied to reductions in diagnostic delay, preventable harm, and avoidable downstream utilization.
Doctronic pushed the question further, asking how AI-performed clinical services, and clinician review of AI-performed work, could be paid. This gets directly to the disruptive question: if AI does part of the doctor’s work, what exactly is the billable service?
Epic and Oracle reportedly emphasized funding for adoption, including infrastructure and AI-enabled EHR capabilities. This echoes the earlier history of federal incentives for EHR adoption, though AI is not the same policy problem as basic EHR installation.
Tempus AI urged a lighter FDA pathway for some categories of AI products, including digital pathology-related categories. That is especially relevant for readers watching the convergence of AI, oncology, diagnostics, and FDA-regulated software.
This Was Not the First 2025 AI Reimbursement Signal
The December HHS RFI should also be read alongside earlier CMS activity in 2025.
In July 2025, CMS included AI/software reimbursement questions in both the proposed CY 2026 OPPS rule and the proposed CY 2026 Physician Fee Schedule rule. In OPPS, CMS asked for comments on payment policy for Software as a Service — SaaS — including AI-enabled tools used in outpatient and physician-office settings. In the PFS context, CMS also raised the problem that current practice expense methodology does not easily capture SaaS and AI-driven technologies, which often involve licensing, updating, integration, cloud services, data management, and workflow costs rather than the traditional “equipment, supplies, and clinical labor” inputs. [See my recent case study, 92229, about SaaS vs RUC.]
That is the core reimbursement problem in one sentence: Medicare payment systems were built around human time, supplies, and depreciable equipment. AI often arrives as software, subscription, infrastructure, workflow redesign, and quality improvement. The old pricing machinery does not fit very well.
What to Watch on June 25
For the June 25 webinar, I would listen for several things.
First, does HHS treat AI reimbursement as a coding-and-payment problem, or as a broader payment model problem? The difference matters. A new CPT code may help a few products. A new payment model could reshape incentives for whole categories of AI-enabled care.
Second, does HHS distinguish clinical AI from administrative AI? Ambient documentation, prior authorization, risk adjustment, imaging triage, diagnostic interpretation, and digital pathology are all “AI,” but they raise very different payment, evidence, and accountability questions.
Third, does HHS have a view on “deflationary” AI? The press release emphasized AI that could reduce burden, improve care, and lower costs. But in fee-for-service Medicare, new separately payable technologies usually increase spending before they reduce anything. CMS has always struggled with this tension.
Fourth, does HHS point to CMMI? Several industry comments appear to see CMMI as a possible test bed for AI payment models. That could become important if CMS does not want to create broad national fee-for-service payment for every AI product category.
Fifth, will FDA, ONC, and CMS move together? AI policy can fragment quickly: FDA focuses on safety and device regulation, ONC on data and interoperability, CMS on coverage and payment. The December RFI was notable because HHS asked the question at the Department level.
Bottom Line
The December 2025 HHS AI RFI was not just another “tell us what you think” exercise. It was a signal that HHS is actively considering how regulation, reimbursement, and federal R&D policy should change as AI moves from demos and pilots into clinical operations.
For reimbursement readers, the big issue is no longer whether AI is interesting. The issue is whether Medicare and other payers can create payment pathways that reward genuinely useful AI without creating a new spending bubble for every algorithm with a clever business plan.
The June 25 HHS/ONC webinar should be worth watching.
Registration entry point:
https://healthit.gov/event/adoption-of-ai-in-clinical-care-updates-from-the-hhs-rfi/
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Sidebar 1 [Fed Reg 12/2025]
Reimbursement
HHS’s payment policies and programs have massive effects on how health care is delivered in the United States, often times with unintended consequences.
Hypothetically, if a payer is taking financial risk for the long-term health and health costs of an individual, that payer will have an inherent incentive to promote access to the highest-value interventions for patients. Under government designed and dictated fee-for-service regimes, however, coverage and reimbursement decisions are slow. Rarely does covering new innovations reduce net spending; and waste, fraud, and abuse is difficult to prevent, often times leading to massive spending bubbles on concentrated items or services that are not commensurate with the value of such products.
Given the inherent flaws in legacy payment systems, we seek to ensure that the potential promises of AI innovations are not diminished through inertia and instead such payment systems are modernized to meet the needs of a changing healthcare system. We seek feedback on payment policy changes that ensure payers have the incentive and ability to promote access to high-value AI clinical interventions, foster competition among clinical care AI tool builders, and accelerate access to and affordability of AI tools for clinical care.
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Grounding notes: the Federal Register RFI says HHS sought public comment on accelerating AI in clinical care, with comments due February 23, 2026, and framed the levers as regulation, reimbursement, and R&D. The HHS press release emphasized regulation, reimbursement, and R&D, plus interoperability, HIPAA, patient/caregiver experience, provider burden, quality, and costs. STAT reported about 7,300 submitted comments and summarized comments from Abridge, Aidoc, Doctronic, Epic, Oracle, and Tempus. The webinar PDF gives June 25, 2026, 3:00–4:00 pm EDT, and says HHS leadership will discuss key takeaways from the RFI. The OPPS proposed rule included a comment solicitation on payment policy for SaaS, including AI-enabled software used in outpatient and physician-office settings. (Federal Register) For PFS, secondary summaries of CMS-1832-P describe CMS seeking comments on SaaS/AI payment and practice-expense valuation limits. (hklaw.com)
