ARPA-H commits $62.7M to partially autonomous heart-failure agents ā agents that assess symptoms, prescribe drugs, order labs, with FDA authorization as the target. More below.
The AMA released the CPT 2027 code set ā 299 new codes, 10 of them AI, effective January 1. Your tool has a pipe or waits until 2028.
FDA now has a Deputy Commissioner for Technology and AI ā Jared Seehafer, the first to hold the role, named eight days after the agencyās longtime digital health lead walked.
Stanford says walking away from AI vendors over data terms is routine now ā CTO Christian Lindmark has dropped vendors over data and contract terms and calls it routine; CHOP has done the same.
š§ Podcast: Podnosis ā āHow video games are changing medical educationā ā Sam Glassenberg, now EVP at Relevate Health Games, compressed a months-long diabetes caregiver curve into hours of gameplay. ~50,000 downloads.
š® My bet: the supervisory layer becomes a product category before it becomes an EHR feature. By Q3 2027 at least two health systems will buy agent-monitoring separately from the agents ā because the vendor selling you the agent is the worst possible party to grade it.
š§ The Curbside
āShould I fine-tune an open model for a specialty, or just prompt a frontier model?ā
Short answer: Fine-tuning wins on narrow, bounded tasks, and the evidence just got specific. EviNurse, a Qwen3-32B fine-tune on nursing evidence, hit 91.45% on a 3,438-question benchmark and beat general-purpose models in expert review (npj Digital Medicine, Sept 9).
Builder read / Watchout: It was built and evaluated in mainland China ā 316 nurses across every province ā so scope of practice and documentation standards donāt transfer. The recipe does: a 32B open model on consumer hardware beating frontier models on a bounded vocabulary. Steal the method, not the weights.
š¬ The Big Thing
Who watches the agent that writes the prescription?
ARPA-H committed $62.7M to a program called ADVOCATE to build partially autonomous, FDA-authorized AI for heart failure ā agents that assess symptom severity, prescribe medications, and order labs.
Atman Health, UpDoc, and Tempus AI are building them. $33.7M lands in year one.
Then thereās the part that changed how I read it.
Stanfordās award isnāt for an agent at all. Itās STEWARD ā a disease-agnostic supervisory system that monitors the clinical agents after deployment, catching unsafe recommendations and out-of-distribution behavior and producing inspectable per-claim rationales.
The government separated the agent from its supervisor, funded them as two different jobs, and handed the supervisor to a different institution.
Thatās not a technical detail. Thatās a statement about who gets to grade the work.
Duke validates across five health systems and rural sites on both Epic and Oracle Health. Kaiser Permanente deploys across 21 medical centers and 260+ clinics inside Epic workflows.
So the path is real, it runs on the EHRs you already live in, and the safety layer has its own accountable party.
š¤ āAutonomous prescribing is a lawsuit with a user interface.ā Partially autonomous. Every one of those actions already happens under a protocol, a standing order, or a pharmacist with a collaborative practice agreement. Whatās new isnāt the autonomy ā itās that the autonomy has to show its work continuously instead of once, at a 510(k) moment.
š¤ āARPA-H funds moonshots that die at the demo.ā Then watch Duke, not the agents. Multi-site, dual-EHR validation infrastructure outlives whatever gets built on it, and the private market has never once paid for it.
ā The supervisor is disease-agnostic; the agents are disease-specific. So the supervisor is the one with the general market. What is that product ā a service, a library, a certification body? Thereās a company sitting in that gap and I canāt name it yet.
š” Builderās Radar
AI now has 43 CPT codes. Yours probably isnāt one of them.
The AMA released the CPT 2027 code set on September 9 ā 299 new codes effective January 1, ten of them AI-related, bringing the total to 43. The Editorial Panel also updated Appendix S, the taxonomy sorting AI into assistive, augmentative, and autonomous.
That taxonomy isnāt academic. My read: autonomous is the only tier where the operating entity has a plausible path to billing without a physician encounter. Everything else is a line item you have to justify inside someone elseās fee.
If your service isnāt in the 2027 set, your next shot is the February panel ā submit by November, effective January 2028.
The FDA hired a technology chief before it replaced its digital health lead.
HHS named Jared Seehafer the FDAās first Deputy Commissioner for Technology and AI on September 8. The role is commissioner-level and agency-wide, which puts AI strategy above CDRH rather than inside it.
Read that as centralization, not staffing.
š® Where this lands: the test is the generative AI docket (FDA-2026-N-7874), open through October 19. If that yields a real review framework by spring instead of another discussion paper, the office has teeth. If not, itās a layer.
A journal is recruiting collaborators to write the validation standard.
Nature Medicine published a correspondence on September 9 calling for collaborators on the āValidation Accords,ā a consensus framework for validating generative AI before clinical deployment.
Bright Huo leads it and Gordon Guyatt is the last author ā an international working group, but the standard it produces will land on US deployments too. Their argument: generative AI gets validated on benchmarks and rarely gets tested in the setting where it will actually run.
Rare one where the ask is literally in the title ā ācall for collaborators.ā If youāve wanted a clinician-builder in the room while the evaluation rules get written, that room is open right now.
ā” Quick hits
Cleveland Clinic partnered with Luminai to read inbound external referrals ā many still arriving by fax ā into the EMR as structured data. A 2015 problem with a 2026 price tag, and still the highest-volume unstructured-document workflow in American medicine.
Meta shipped Muse, a consumer agent that runs inside a dedicated āSecure VMā with its own browser, with a Confidential VM coming later this year that encrypts the whole machine under a key only the user holds. Untrusted agent, hard sandbox, containment as the headline feature ā the same instinct ARPA-H just funded.
Dr. Josh Au Yeung co-founded Vitruvia Labs with a clinical + ML + privacy/cryptography founding team, pitched as going beyond āapplying llm wrappers.ā The privacy-engineering seat on a founding team is the tell.
Brian Fung is running a second cohort of his build-with-AI bootcamp for clinicians ā two weeks, live, starting September 28.
šļø From the Pods
šļø Podnosis ā āHow video games are changing medical educationā
Sam Glassenbergās team replaced static type 1 diabetes caregiver education with a decision game ā his framing is that it trains the brain to manage diabetes in hours instead of months. Roughly 50,000 downloads since launch.
š” Builder take: Patient education is the most under-designed surface in medicine and the one with the lowest regulatory bar. Your first shippable artifact is here, not in the EHR.
š Speaker Blindspot: Survivorship bias ā every example is a game that worked, and the claim that efficacy holds āno matter how old you areā rests on studies recruiting doctors who volunteered to play a game.
Yashaswini Singh, PhD on PE-acquired primary care: 20% more preventive care delivered, no detectable rise in low-value care, prices negotiated 8ā10% above independent practices.
š” Builder take: The lever that moved was administrative capture, not clinical quality. Build for the preventive-care gap and the coding of it, not the ownership model.
š Speaker Blindspot: Moving the goalposts ā asked three times whether a bad outcome is āinevitable,ā she offers a theoretical best case, concedes the data canāt confirm it, then admits she suspects the worse reading.
š” BTW
š” BTW: Gordon Guyatt ā on the byline of that Validation Accords call ā originally wanted to name the movement āscientific medicine.ā In his telling, the basic scientists at McMaster were āso enraged that I was calling what we were doing āscientific medicineāā that he went back to the drawing board and returned with āevidence-based medicineā instead. That was 1990. (JAMA/BMJ oral history, via AMA)
You have a unique combination of skills, experience and values. So do great things! ā¦ and tell me about them at kevin@clinicians.build.
ā Kevin & AI
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