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ChatGPT Plugged Into Epic Without a Partnership: What the September 1 EHR Integration Actually Is, Who Holds the Liability, and Why CIOs Now Have Three AIs Fighting Over One Patient Chart

OpenAI plugged ChatGPT into Epic EHR on September 1. Every headline called it a historic partnership. There is no partnership. Here is what actually happened…

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16 hours ago

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Table of Contents

1. What actually shipped on September 1

2. The plumbing is boring and that is the whole story

3. Epic’s very loud silence

4. Three AIs, one chart, zero referees

5. The liability question nobody has priced

6. Governance, HIPAA, and the opt out that does not exist

7. Trial matching and the pharma subplot

8. What to actually do with this

Abstract

• OpenAI announced on September 1, 2026 that ChatGPT for Healthcare now connects to Epic environments, read only, with two modes: pull chart data into ChatGPT, or embed ChatGPT inside supported Epic workflows

• A companion Healthcare Public Data plugin wires in official sources including ClinicalTrials.gov, PubMed, RxNorm, DailyMed, CMS Coverage, and other CMS datasets

• This is not a partnership. It rides Epic’s free open FHIR APIs, the same on-ramp used by thousands of other apps. Epic did not co-announce; its public comments frame the integration as one of those thousands of apps that health systems can choose to enable.

• UCSF Health is piloting. AdventHealth leaders have commented on the broader OpenAI healthcare workspace. OpenAI is publishing safety numbers: 99.1 percent of responses rated safe across 4,363 physician ratings, and connector accuracy from 93.2 to 98.6 percent depending on the public data source.

• The interesting questions are downstream: liability when a summary omits the one med that mattered, patient opt out (there isn’t one), FDA clinical decision support boundaries, and the fact that most large health systems already pay two other vendors to do exactly this job

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The integration runs on Epic’s free public FHIR APIs, the same ones any developer can use. A health system admin registers an app, adds credentials, publishes it. Clinicians sign in with their existing Epic logins. ChatGPT sees exactly what the doctor can see. Nothing more.

Epic’s official response on launch day: OpenAI’s app is ‘one of thousands’ that connect through free APIs, and health systems choose which to enable. Translation: we didn’t invite them, we can’t stop them, liability is yours.

OpenAI published physician safety ratings: 99.1% of responses rated safe across 4,363 evaluations. Do the math. That’s roughly 39 unsafe responses in a controlled setting. At real health system scale, 0.9% is a patient safety committee agenda item, not a rounding error.

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Thoughts on Healthcare Markets & Technology

Part I: OpenAI Just Wired ChatGPT Directly Into Epic and Nine Official Health Data Sources, and Every Hospital AI Governance Committee in America Just Had Its Next Two Quarters Planned For Them

OpenAI just wired ChatGPT directly into Epic and nine official health data sources. HCA, UCSF, Cedars-Sinai, and Memorial Sloan Kettering are launch partners. This changes the stack…

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4 days ago

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Thoughts on Healthcare Markets & Technology

Part II: OpenAI Just Wired ChatGPT Directly Into Epic and Nine Official Health Data Sources, and Every Hospital AI Governance Committee in America Just Had Its Next Two Quarters Planned For Them

OpenAI just wired ChatGPT directly into Epic and nine official health data sources. HCA, UCSF, Cedars-Sinai, and Memorial Sloan Kettering are launch partners. This changes the stack…

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4 days ago

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Table of Contents

1. What actually shipped on September first

2. The plumbing, or how patient data probably gets from Epic into a chatbot

3. Epic has been playing this game for years, mostly with OpenAI’s own models

4. About that 99.1 percent

5. The startup blast radius

6. The governance hangover

7. What to watch between now and the next HIMSS

Abstract

• OpenAI announced an Epic integration for ChatGPT for Healthcare, letting clinicians pull authorized patient context into ChatGPT and, in some deployments, embed ChatGPT inside the EHR layout itself

• A new Healthcare Public Data plugin connects nine official sources including PubMed, ClinicalTrials.gov, DailyMed, RxNorm, and CMS Coverage as structured, queryable connectors rather than generic web search

• OpenAI is leaning hard on physician eval numbers: 700k plus reviewed responses, 27 clinical use cases, 4,363 ratings, 99.1 percent rated safe, and 93 percent plus accuracy on connected data sources

• Launch partners include UCSF, HCA, Cedars-Sinai, Memorial Sloan Kettering, Boston Children’s, Baylor Scott and White, and AdventHealth, which is a serious roster for a v1

• The essay covers the likely technical architecture, Epic’s own AI position and its complicated Microsoft relationship, what the evals do and do not prove, which startups should be nervous, and why the real work is governance, not integration

What actually shipped on September first

OpenAI dropped a healthcare announcement the day after Labor Day, which is either a scheduling accident or a very deliberate way to ruin the first week back for every CMIO in the country. Two things shipped. First, an Epic integration for ChatGPT for Healthcare that brings authorized patient context out of the chart and into the chat window. A clinician can ask what changed since the last visit, which labs need review before this afternoon, whether meds got touched, whether a specialist wrote something important that got buried on page forty of a scanned fax. ChatGPT assembles the answer from the record and points back to the supporting chart data. Second, a Healthcare Public Data plugin that gives structured access to nine official sources, including ClinicalTrials.gov, CMS Coverage, RxNorm, DailyMed, and PubMed. Not search over these sources. Actual connectors, with the ability to work against specific records, identifiers, fields, and policy versions.

The Epic piece comes in two flavors. One is EHR context flowing into the ChatGPT workspace, so a clinician preps for clinic in ChatGPT instead of clicking through Chart Review tabs. The other is ChatGPT embedded directly into an EHR layout in supported deployments, meaning the model shows up inside the workflow instead of asking the clinician to leave it. That second flavor is the one that matters commercially, because the entire history of clinical software teaches one lesson over and over: whatever lives inside the Epic frame wins, and whatever requires a second browser tab dies a slow death measured in abandoned pilots.

Everything sits inside ChatGPT for Healthcare, a governed workspace with role based access, SSO, audit logs, and an applicable BAA, which makes OpenAI a business associate under HIPAA for these deployments. Individual clinicians on the eligible clinician tier can get the public data plugin, but the EHR integration is enterprise only, which is the correct call and also conveniently a great enterprise sales motion. Launch partners include UCSF, HCA, Cedars-Sinai, Memorial Sloan Kettering, Boston Children’s, Baylor Scott and White, and AdventHealth. That is not a list of gullible pilot shops. HCA alone runs around 190 hospitals and one of the most industrialized IT operations in the industry. When they show up in the launch graphic, procurement conversations at every other system get shorter.

The plumbing, or how patient data probably gets from Epic into a chatbot

The announcement is light on architecture, which is normal for a launch post and maddening for anyone who has ever actually stood up an Epic integration. So some informed reading between the lines. The phrase authorized patient context is doing heavy lifting. The plausible path is the standard one: SMART on FHIR app launch for the embedded experience, FHIR R4 reads against the Epic instance for chart data, scoped to the patient in context and the user’s security class, with the health system controlling which resources are exposed. Epic’s APIs cover the USCDI data classes plus a long tail of Epic specific endpoints, and any vendor who has been through the open.epic and Vendor Services gauntlet knows the difference between what the brochure says is available and what your specific customer’s version, build, and security team will actually let you touch. The embedded layout language maps to Epic’s web embedding patterns, where an outside app rides inside Hyperspace or Hyperdrive with a launch token carrying user and patient context. None of this is exotic. What is new is who is on the other end of the pipe.

The parts the post does not answer are the parts every security review will ask in the first ten minutes. Is patient data retained by OpenAI, and for how long, and is any of it eligible for model training under any configuration, and what does the audit log actually capture, prompt text included or just metadata. Zero data retention is table stakes language in healthcare AI contracting now, and the post says nothing either way, which means the answer lives in the enterprise agreement, which means it is negotiable, which means everyone should negotiate it. Minimum necessary is another fun one. HIPAA’s minimum necessary standard was written for humans requesting records, and it gets philosophically weird when the whole value proposition is a model that reads broadly across the chart so it can tell you what matters. A model that pulls the entire longitudinal record to answer whether the potassium is trending is doing something a records clerk would get written up for. Nobody has a clean answer here, and OCR guidance is not exactly sprinting to provide one.

Then there is the question of whose permission this all runs on. Epic does not have a public quote in the announcement, which is worth noticing. The integration presumably runs through the standard vendor pathways, and Epic controls those pathways, and Epic has demonstrated repeatedly that it will use that control when it feels like it. Ask Particle Health, currently litigating an antitrust case after Epic cut off portions of its data access in a dispute nominally about treatment purpose under Carequality. Ask CureIS, which filed its own suit alleging Epic squeezes third parties that touch its customers. The point is not that Epic will kneecap OpenAI. The point is that the world’s most valuable AI company just built a flagship healthcare product whose critical dependency is the goodwill of a privately held company in Verona, Wisconsin that has never once lost a staring contest.

Epic has been playing this game for years, mostly with OpenAI’s own models

Here is the part that makes the whole thing delicious. Epic has been shipping generative AI features since 2023, over a hundred of them at this point across In Basket draft replies, note summarization, coding suggestions, patient message drafting, and its Ask ART style chart questioning tools. And the models under most of that hood have historically been OpenAI models, delivered through Azure OpenAI, because Epic’s strategic AI partner is Microsoft, and Microsoft’s strategic AI partner is, or at least was in the uncomplicated days, OpenAI. So for a couple of years the arrangement was tidy. OpenAI made the models, Microsoft wrapped them in Azure compliance clothing, Epic embedded them in workflow, health systems paid Epic and Microsoft, and OpenAI got paid at the bottom of the stack without ever holding a BAA or sitting in a hospital security review.

This announcement is OpenAI deciding the bottom of the stack is a bad place to live. Going direct to health systems with its own branded workspace, its own BAA, its own embedded Epic experience, and its own enterprise sales team puts OpenAI in competition with the feature roadmap of its distribution partner’s most important healthcare relationship. Epic now gets to decide how enthusiastically to support an integration that competes with Ask ART and friends, Microsoft gets to decide how it feels about its model supplier disintermediating an Azure revenue stream, and health system CIOs get to sit through three different vendors pitching what is functionally the same chart summarization demo, two of which run on the same underlying model family. Somewhere a strategy consultant is billing four hundred an hour to draw this as a triangle.

Epic’s counterweight is real, though. Cosmos sits on de-identified records covering roughly 300 million patients, and Epic’s pitch is increasingly that the interesting AI is the AI trained and validated on that corpus, delivered natively, with no third party BAA and no new vendor risk assessment. Epic also holds a bit under half the US acute care hospital market by facilities and more than half of beds, and its customers skew toward exactly the large academic and multi-state systems on OpenAI’s launch partner list. Which means the launch partners are, almost by definition, Epic shops that decided the native roadmap was not moving fast enough or was not general enough. That is the actual market signal in this announcement. Seven brand name systems just said out loud that they want a general purpose reasoning layer over the chart, not another point feature per workflow, and they are willing to onboard a new business associate to get it.

About that 99.1 percent

OpenAI came armed with numbers, and to their credit the numbers are more specific than the usual AI healthcare vapor. A network of hundreds of physicians across 60 countries, 49 languages, and 26 specialties has reviewed more than 700,000 model responses to date. For the EHR context work specifically, physicians rated responses across 27 use cases, things like pre-visit review, medication reconciliation, clinical timelines, and handoff summaries, with 4,363 ratings and 99.1 percent of responses judged safe. A separate two round eval on nuanced questions over large US healthcare datasets found more than 93 percent of responses rated good or better on accuracy for each of five connected sources.

Now do what this audience always does and squint at the denominators. Safe is a floor, not a ceiling. A response can be rated safe and still be unhelpful, incomplete, or subtly wrong in ways that do not trip a harm flag. 99.1 percent safe across 4,363 ratings means roughly 39 responses were rated something other than safe, and the interesting document is the one describing those 39, which use cases they clustered in, what the failure modes looked like, and what inter-rater agreement was. Handoff summaries and med rec are precisely the use cases where the cost of an omission is asymmetric, where the thing the model fails to surface matters more than anything it says. Rating a summary safe requires the rater to know what was in the chart that the summary skipped, which is a much harder evaluation than reading the output and vibing. Same story on the 93 percent good or better accuracy figure. Good or better is a bar that includes good, and one wrong answer out of fifteen on coverage policy versions or trial eligibility criteria is a number that would get a human analyst put on a performance plan.

None of this is a dunk. Publishing use case level physician evals at all puts OpenAI ahead of most of the market, and 700k reviewed responses is a genuinely large human feedback operation. The gripe is that these are vendor conducted, vendor summarized evals with no public methodology, no confusion matrices, and no per use case breakdown, at exactly the moment health systems are being told to treat AI procurement like device procurement. HTI-1 already forces certified EHR developers to publish source attribute transparency for predictive decision support. The cultural expectation is drifting toward model cards with actual statistics. The vendor who publishes the ugly table first, failure modes and all, is going to win a surprising amount of trust from clinical informatics people who are professionally allergic to marketing percentages.

The startup blast radius

Every platform announcement in healthcare AI triggers the same ritual, in which founders post that this validates the space while their investors quietly reopen the competitive slide. So, honestly, who gets hurt. The most exposed category is the pure chart summarization and pre-visit prep startups, the companies whose entire product is a FHIR pipe, a prompt library, and a nice UI for asking questions of the record. That was always the thinnest wrapper in the industry, and it now competes with the model vendor itself, embedded in Epic, holding a BAA, with a physician eval program bigger than most startups’ user counts. Those companies have maybe a year to become a workflow or become a memory.

OpenEvidence is the more interesting case. It built a very large clinician user base and a rich valuation on being the trusted medical answer engine, with licensed content partnerships and a distribution flywheel through individual doctors. The Healthcare Public Data plugin walks directly at the evidence retrieval part of that, and everyone in the industry can see the next move the LinkedIn commentariat already called: content partnerships with the likes of UpToDate or other medical knowledge publishers, at which point ChatGPT for Healthcare is an answer engine with the chart attached. OpenEvidence’s defense is specialization, physician trust, and the fact that Wolters Kluwer and Elsevier get to choose their partners carefully, since licensing your crown jewel content to the platform that might eat you is a decision publishers have gotten burned on before. Watch where the UpToDate license lands. It is the most consequential unsigned contract in clinical AI.

The ambient documentation crowd, Abridge and Ambience and Suki and Microsoft’s Dragon Copilot, are safer for now because ambient capture is a genuinely hard audio and workflow problem, and Abridge in particular has spent its multi-billion valuation building deep Epic integration and health system relationships. But the strategic pattern should bother them: OpenAI went from model supplier to application vendor in one announcement, and there is no law of nature saying documentation is not next. Meanwhile revenue cycle and coverage tooling people should look hard at the CMS Coverage connector. Structured, version-aware access to NCDs and LCDs inside a general reasoning workspace is quietly a prior auth and denials research tool, and the number of RCM point solutions that are essentially a coverage policy lookup with an interface is larger than anyone in RCM wants to admit. And a note for the interop and data infrastructure layer broadly: every model vendor that goes direct to the chart increases the value of clean, permissioned, well governed pipes and the legal scaffolding around them. Records do not move themselves, and the compliance surface area of AI reading charts at scale is about to make everyone rediscover why release of information is a regulated discipline and not a file transfer.

The governance hangover

The sharpest early commentary on this launch came from clinical informatics people, not investors, and the concern was consistent. When an organization builds its own AI tools on top of the EHR, it controls the guardrails, the logging, the scope of what the model can see, and the eval loop. When users connect the org’s Epic instance to a general purpose chat product, those guardrails now live wherever OpenAI decided to put them, and the org’s visibility depends entirely on what monitoring and evaluation tooling OpenAI exposes to workspace admins. If that tooling is thin, health systems will be flying blind on how the feature is actually used, which prompts are being run against which patients, and what the failure rate looks like in their own population rather than in OpenAI’s eval set. Audit logs that satisfy HIPAA are not the same thing as observability that satisfies a quality committee.

To be fair to the doomers’ critics, the barriers to chaos are real. Nobody’s average attending is connecting the Epic prod environment to ChatGPT from the parking lot. This requires a BAA, workspace configuration, IT enablement, security review, and all the usual enterprise ceremony, and the EHR integration is not available on individual accounts at all. The uncontrolled shadow AI problem, clinicians pasting chart text into consumer chatbots, predates this launch and is arguably reduced by giving people a sanctioned, logged, BAA-covered place to do the same thing. The honest framing is that this launch converts a shadow governance problem into an explicit governance workload, which is progress, but workload nonetheless.

And the workload is genuinely large. Someone has to decide which roles get access, which use cases are blessed, what the escalation path is when the model whiffs on a med list, how output gets labeled, and how any of this squares with the regulatory perimeter. The FDA’s clinical decision support guidance keeps non-device status for tools where the clinician can independently review the basis for the recommendation, which is why everyone’s marketing copy leans so hard on pointing back to supporting chart information, and why the moment these tools start triaging or prioritizing patients rather than summarizing them, the device question gets loud. States are piling on too. California already requires disclaimers on generative AI clinical communications to patients, Colorado’s AI act looms over high risk automated systems, and the patchwork only grows. Add the malpractice question nobody has case law for yet, where a clinician relied on an AI pre-visit summary that omitted the one thing that mattered, and the governance committee’s agenda writes itself. Governance is not the boring part of this launch. Governance is the product surface where this succeeds or dies, and the vendors who treat monitoring, evals, and admin controls as first class features rather than compliance homework are going to take the enterprise market.

What to watch between now and the next HIMSS

A few tells will reveal how this actually goes. Watch whether Epic says anything at all, and in what tone, because a warm co-marketing motion versus pointed silence versus a new Vendor Services pricing memo are three very different futures. Watch whether Cerner, sorry, Oracle Health, shows up in the supported EHR list next, since the announcement’s careful phrasing about supported EHRs suggests Epic is the first pipe and not the last, and Oracle is desperate for a differentiator. Watch the UpToDate and broader content licensing chessboard, because whoever assembles chart context plus licensed evidence plus public data in one governed workspace has functionally rebuilt the clinician’s entire information environment. Watch whether OpenAI publishes real eval methodology, per use case numbers, and admin-facing monitoring tools, because that is the difference between a healthcare product and a healthcare-flavored product. And watch the pilot partners’ podium talks in about a year, because UCSF and HCA will have actual utilization data, and health systems are constitutionally incapable of not presenting a slide about it.

The meta point is simple and worth saying plainly. Foundation model vendors have decided healthcare distribution is worth owning directly, the EHR vendors have decided AI is a native feature and not a partner category, the content publishers hold licensing leverage they have not fully spent, and the startups in between are about to find out which of them were companies and which were features. Patient data plumbing, governance infrastructure, and clinical evidence licensing just became the three most strategic assets in the stack. Everything else is a prompt away from being commodity. Plan the next two quarters accordingly, and maybe send the AI governance committee some coffee. They are going to need it

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The Epic integration comes in two flavors. One pulls chart context into ChatGPT. The other embeds ChatGPT inside the Epic layout itself. That second one is the commercially …

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The Epic integration comes in two flavors. One pulls chart context into ChatGPT. The other embeds ChatGPT inside the Epic layout itself. That second one is the commercially important version.

Here is the twist: Epic has been shipping over a hundred generative AI features since 2023, mostly powered by OpenAI models through Azure. OpenAI just decided being at the bottom of that stack is a bad deal.

OpenAI now holds its own Business Associate Agreement, its own enterprise sales motion, and its own embedded Epic experience. That puts it in direct competition with the feature roadmap it has been quietly powering for two years.

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Thoughts on Healthcare Markets & Technology

Why CMS Stopping 1.6 Billion Dollars in Fake Medicare Lab Claims Proves the Analytics Layer Is Now Trivially Cheap, While the Services Layer That Proves a Lab Never Existed Remains the Actual Moat

CMS just announced 1.6 billion dollars stopped in fake Medicare lab payments. They credited AI and machine learning. The real story is more interesting than that…

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5 days ago

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Table of Contents

1. The press release, decoded

2. Anomaly detection is a solved problem, sorry

3. The part where someone drives to the strip mall

4. Suspension, revocation, and the due process meat grinder

5. Cat and mouse in Texas

6. What this means if you build, invest, or sell in program integrity

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Abstract

• CMS announced 1.6 billion dollars in prevented or recovered fraudulent Medicare lab payments, including 732 million from revoking 157 lab providers, 500 million plus in payment suspensions across 185 labs (out of 600 investigated), 276 million recouped from 442 overpayments, and 127 million tied to 85 law enforcement referrals.

• The detection side of this story is genuinely easy now. Claims data plus an LLM writing analysis code gets you 90 percent of the flagging logic in an afternoon. The features are public knowledge and have been for a decade.

• The hard 10 percent is everything after the flag: site visits proving 14 labs were never operational, medical review, credible allegation standards, suspension mechanics, revocation authority, and surviving an appeals gauntlet designed to protect legitimate providers.

• The Texas cases in the release show the adversarial loop in action: a lab gets denied 1.2 million, shifts billing patterns within weeks to dodge the edits, and gets caught again only because humans kept watching.

• Implication for builders and investors: the model is not the product. The defensible asset in fraud is the case file, the evidentiary chain, and the boots. Services layer economics apply, with everything that means for margins and moats.

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732 million from revoking 157 labs. 500 million-plus in payment suspensions across 185 labs out of 600 investigated. 276 million recouped from overpayments. 127 million from law enforcement ref…

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Thoughts on Healthcare Markets & Technology

Part I: The Fintech Nobody Has Built Yet: Why the One Big Beautiful Bill's Medicaid Provider Tax Phase-Down and Directed Payment Caps Create a Bridge Lending, Copay, and Coverage-Churn Business

The One Big Beautiful Bill puts Medicaid supplemental payments on a step-down schedule written into federal law. No hospital CFO in an expansion state needs to guess when the cash hole arrives. They can model it today…

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8 days ago · Thoughts on Healthcare

🎧 Part II Podcast episode for paid subscribers only. Also available on Apple Podcasts and Spotify.

Thoughts on Healthcare Markets & Technology

Part II: The Fintech Nobody Has Built Yet: Why the One Big Beautiful Bill's Medicaid Provider Tax Phase-Down and Directed Payment Caps Create a Bridge Lending, Copay, and Coverage-Churn Business

The One Big Beautiful Bill puts Medicaid supplemental payments on a step-down schedule written into federal law. No hospital CFO in an expansion state needs to guess when the cash hole arrives. They can model it today…

Listen now

8 days ago · Thoughts on Healthcare

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Table of contents

1. The plumbing everyone pretends to understand

2. What the bill actually broke, with dates

3. The cash flow hole is the product

4. A lender for supplemental payments

5. The thirty five dollar copay nobody has ever collected

6. Churn as an asset class

7. Why banks will not do this and PE-backed RCM will do it badly

8. How it dies

9. What to fund

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Abstract

• OBBBA (P.L. 119-21, signed July 4, 2025) rewires the nonfederal share of Medicaid: provider tax safe harbor steps down from 6% to 3.5% of net patient revenue in expansion states between FY2028 and FY2032, new taxes are frozen at enactment, uniformity waivers for MCO taxes are gutted, and state directed payments get capped at Medicare rates with legacy programs stepping down 10 points a year starting in 2028.

• Layered on top: work requirements by Jan 2027, six-month redeterminations for expansion adults, retroactive coverage cut to one month for that population, and up to $35 per-service cost sharing on expansion adults above 100% FPL starting Oct 2028.

• CBO scores roughly $0.99T in federal Medicaid and CHIP reductions over ten years and about 8-10M more people losing Medicaid or CHIP coverage by 2034, translating into millions more uninsured. Hospitals do not lose that money evenly; they lose it in specific, dated, lumpy chunks tied to supplemental payment programs that already pay 6 to 18 months late.

• Three fintech shapes fall out of that: (1) a specialty lender advancing against supplemental payment receivables through the 2028 to 2031 transition, (2) a point-of-service and payment plan layer for a Medicaid population that has never received a bill, and (3) a coverage-churn recovery business that buys or finances self-pay AR contingent on re-enrollment inside the new shortened retro window.

• The first is the real venture, mostly because commercial banks find hospital supplementals too strange to underwrite and the people who understand them are actuaries and Medicaid finance directors, not lenders. The other two are adjacent and defensible but sit closer to turf PE-backed RCM already circles.

• Main risks: Congress stretching the schedule, states backfilling with general fund money, and the asset class literally shrinking on purpose. Underwrite it as a transition product with a hard sunset and a pivot into general safety-net liquidity.

The plumbing everyone pretends to understand

Start with the thing that is technically public knowledge and yet somehow only about four hundred people in the country actually get: the nonfederal share of Medicaid is not mostly state general fund money. A big slice of it, something in the range of a sixth to a fifth nationally and way more in some states, comes from taxes levied on the providers who then receive the Medicaid payments. The hospital pays the state, the state books that as its match, the feds send down FMAP on top of it, and the state hands most of the pile back to hospitals as supplemental payments. Everybody in the loop is better off except the federal treasury, which is why Washington has been trying to strangle this arrangement since roughly the Bush administration and why it never quite dies.

Forty nine states plus DC run at least one provider tax. Alaska is the holdout and Alaska is the holdout on most things. The rules that kept this from being an unlimited money printer were the safe harbor and the uniformity requirement. Safe harbor said if your tax stays under 6% of a provider class’s net patient revenue, CMS will assume you are not just laundering federal dollars and will not make you prove a hold harmless test. Uniformity said you have to tax the whole class the same way and cannot, say, tax Medicaid managed care plans at ten times the rate you tax commercial plans, which is exactly what California did with its MCO tax and which exactly what several other states copied once they saw it work.

The money comes back through three main pipes. Upper payment limit programs for fee for service, which top hospitals up to what Medicare would have paid. Disproportionate share payments, which have their own separate drama and were not touched here. And state directed payments, which are the managed care version of UPL and which ballooned from a rounding error in 2017 to over $110B in annual approved spend by 2024 according to MACPAC’s count. SDPs are the one to watch, because SDPs are where the provider tax dollars mostly go now, and SDPs are what the bill went after hardest.

One more piece of plumbing before the fun part. None of this money shows up when the service happens. A hospital treats a Medicaid patient in January. The base capitation payment from the MCO shows up on a normal claims timeline. The SDP uplift for that encounter gets calculated after the quarter or the year closes, flows through the MCO on whatever schedule the state contract says, and is subject to CMS having approved the preprint for that rating period, which itself often happens retroactively. UPL payments are typically annual. So a meaningful share of a safety-net hospital’s Medicaid revenue is a receivable with a twelve to eighteen month tail, a counterparty that is a state government, and an approval dependency on a federal agency. If that does not sound like a fintech asset, keep reading anyway, because it is about to become a fintech asset with a countdown clock.

What the bill actually broke, with dates

The One Big Beautiful Bill Act is a very long document that does a lot of things, and the Medicaid section is a very long chapter that does a lot of things, so the exercise here is to pull out the provisions that change hospital cash flow and pin each one to a date. Dates matter because the whole thesis rests on the losses being predictable.

Provider taxes first. As of enactment, no new provider taxes and no increases to existing ones. If you were below the ceiling, you are stuck there. Then the ceiling itself moves, but only in expansion states. Starting in federal fiscal year 2028, meaning October 1, 2027, the safe harbor for expansion states drops half a point per year: 5.5% in FY2028, 5% in FY2029, 4.5% in FY2030, 4% in FY2031, and 3.5% in FY2032 and forever after. Nursing facilities and intermediate care facilities are carved out of the phase-down, which tells you who had the better lobbyists in June 2025. Non-expansion states keep 6% but cannot touch anything. So the map now has a hard split: Texas and Florida hospitals keep their tax revenue frozen in amber, while California, New York, Michigan, Ohio and the rest of the expansion world watch it step down on a schedule you could put in a spreadsheet today.

Uniformity second. The bill codifies what CMS had already been signaling in rulemaking, which is that the MCO tax trick of taxing Medicaid plans far more heavily than commercial plans no longer qualifies as uniform. States that already had these taxes get a transition window, up to three fiscal years at the Secretary’s discretion, but the direction is one way. California’s MCO tax alone was moving something on the order of $7B to $8B a year through the system. That is not a rounding error for a state budget or for the hospitals and physician groups the state promised it to.

State directed payments third, and this is the one that hits hospital P&Ls the hardest. New SDPs submitted after enactment are capped at 100% of the Medicare rate in expansion states and 110% in non-expansion states. Programs approved before enactment that pay above that cap, and there are plenty paying at average commercial rate, step down 10 percentage points per rating period starting January 1, 2028 until they hit the cap. Rural hospitals got a slightly kinder grandfather date. The practical effect is that a hospital in an expansion state currently receiving an SDP at, say, 180% of Medicare will see that uplift shaved to 170, 160, 150 and so on each year until it lands at 100. Depending on its starting level, that is a multi-year glide path for the most generous programs and a much shorter one for the middling ones.

Now the enrollment side, because it drives volume and payer mix, which drives the base against which all of the above is calculated. Work requirements for expansion adults ages 19 to 64, 80 hours a month of work, school, or community engagement, must be live by January 1, 2027, with hardship extensions available to December 31, 2028 for states that can show a good faith effort. Redeterminations for expansion adults go from annual to every six months for renewals after December 31, 2026. Retroactive coverage drops from 90 days to 30 days for expansion adults and 60 days for everyone else as of January 1, 2027. And starting October 1, 2028, states must impose cost sharing of up to $35 per service on expansion adults with income above 100% of the federal poverty level, capped at 5% of family income, with primary care, mental health, substance use, and FQHC and rural health clinic services exempt.

CBO’s read on all of this, give or take a revision, is roughly a trillion dollars less federal Medicaid and CHIP spending over the ten year window and on the order of 8-10 million fewer people enrolled in Medicaid or CHIP by 2034, many of whom will end up uninsured at least part of the time. The provider tax provision on its own was scored around $190B. SDP limits around $150B. Work requirements and associated eligibility tightening around $320-330B, mostly through people falling off the rolls rather than through anyone actually going to work. The point is not the total. The point is that every one of those numbers has a start date and a slope.

The cash flow hole is the product

Here is where the mental model needs to shift from policy analysis to balance sheet. A hospital does not experience the OBBBA Medicaid provisions as a policy. It experiences them as a series of holes in a fourteen month cash flow forecast, each hole a different size and shape and each arriving on a different date.

Consider a mid-sized safety-net system in an expansion state. Call it $2B in net patient revenue, 35% Medicaid by volume, running a hospital tax at 5.8% of net patient revenue and receiving SDP uplift that brings Medicaid managed care rates to roughly 150% of Medicare. In FY2028, the tax cap drops to 5.5%, so the state either cuts the tax and shrinks the pool or backfills with general fund money it does not have. The SDP starts stepping down in January 2028, so the uplift drops to 140% of Medicare. Meanwhile, six month redeterminations started a year earlier and the expansion adult population is churning, so a chunk of what used to be Medicaid volume is now self-pay volume with a 30 day retro window instead of 90. By October 2028 that system is also supposed to collect $35 copays from patients who have never seen a bill from a hospital in their lives.

Each of these lands on a different line of the forecast. The tax cut hits the supplemental payment receivable. The SDP step-down hits the same receivable but on a different clock. The churn hits gross revenue and bad debt simultaneously. The copay creates a new receivable category from scratch. None of them are fatal individually. Together they compress operating cash in a way that the hospital’s existing credit facility was not sized for, and the bank that provided that facility is going to look at a Medicaid supplemental payment schedule and ask what a preprint is.

This is the opportunity. Not the losses themselves, which are just losses, but the timing mismatch between when the losses are known and when the cash actually moves. A hospital CFO in an expansion state can tell you today, with unusual precision, how much supplemental revenue will disappear in each of the next five years. That precision is rare in healthcare and it is the raw material of a lending business. Fintech, at its core, is the business of pricing predictable cash flows that traditional lenders find too weird to touch. Medicaid supplementals are about as weird as it gets, and they just became predictable.

A lender for supplemental payments

The core company is a specialty finance shop that advances cash against expected supplemental payments, structured somewhere between receivables factoring and a revolving facility, sold to safety-net and rural hospitals in expansion states during the 2028 to 2031 transition.

The mechanics look like this. The lender builds a model of each state’s SDP, UPL, and provider tax programs, including the approved preprints, the rating periods, the MCO pass-through schedules, and the statutory step-down. For each hospital client, the lender estimates the supplemental receivable for the next four to six quarters, applies a haircut for state payment timing risk and federal approval risk, and advances a percentage against it. The hospital gets cash in month one instead of month fourteen. The lender takes a spread that reflects the counterparty being a state government, which is not nothing, but is a very different credit than a commercial payer or a patient. When the supplemental actually arrives, it pays down the advance. Rinse and repeat, with the advance amounts shrinking each year on the statutory schedule.

Why does this work as a product and not just as a slightly exotic bank loan? Three reasons, and none of them are secrets, they are just things banks have decided not to learn.

First, the underwriting is program-specific, not hospital-specific. A regional bank underwrites a hospital by looking at days cash on hand, EBITDA margin, and the general obligation of the system. A supplemental payment lender underwrites the state program. Is the preprint approved through the rating period? Has the state historically paid on time? Did the legislature fund the state share in the budget that just passed? Is the MCO contract clear about pass-through timing? This is Medicaid finance expertise, the kind that lives in state Medicaid agencies, in a few actuarial firms, and in the finance departments of hospital associations. It does not live in commercial lending. A company that hires that expertise and turns it into a credit model has a moat that looks a lot like the moat a specialty pharma royalty lender has: everyone could in principle do it, nobody else has bothered to build the models.

Second, the client cannot get this money anywhere else at a reasonable price. Safety-net hospitals are exactly the systems with the weakest credit profiles, the thinnest margins, and the highest dependence on supplementals. The muni bond market is closed or expensive to a lot of them. Their bank lines are sized to normal operations. Private credit has mostly not touched them because the story was too complicated. The bill just made the story simple: here is a dated cash flow, here is a dated loss, bridge the gap.

Third, the asset shrinks on a known schedule, which is bad for the total addressable market and great for the credit risk. A lender can size each facility knowing that next year’s supplemental will be smaller by a statutorily defined amount. That is a rare luxury. Most receivables lending has to model the counterparty’s business going sideways in ways nobody predicted. This one has the going-sideways written into federal law with a start date.

The numbers are large enough to matter. If SDPs alone were running north of $124B a year in approved spend by 2025, and the bill compresses the above-Medicare portion over several years, the pool of supplemental receivables outstanding at any moment is tens of billions of dollars. Even a small share of that flowing through a specialty lender with a few hundred basis points of spread is a real business. Add UPL and the tax-funded FFS supplementals, and the addressable receivable base is comfortably big enough for a venture-scale credit company, at least through the phase-down period.

The obvious objection is that this is a melting ice cube. Correct. The statutory glide path means the supplemental receivable base in expansion states is smaller every year, and by the time the SDP step-downs finish, the business is advancing against a fraction of what it started with. The honest response is to build it that way on purpose. Structure the company as a transition-period lender with a hard sunset on the supplemental product and a plan to migrate the client base into general safety-net liquidity products by year four. The relationships built by being the only lender who understood a hospital’s Medicaid finance in 2028 are the relationships that get you the working capital line, the equipment financing, and the receivables factoring on commercial and Medicare AR in 2033. The supplemental product is the wedge. The wedge does not need to last forever, it needs to last long enough to build a book of hospital clients that nobody else bothered to court.

The thirty five dollar copay nobody has ever collected

Second idea, smaller, adjacent, and weirder. Starting October 1, 2028, expansion adults with income above 100% of FPL owe up to $35 per service for a lot of non-exempt care, and the hospital is the one who has to collect it.

Think about what this population looks like from a billing office’s perspective. They have never received a hospital bill. They do not have a card on file. A meaningful share do not have a bank account, and a larger share do not have a credit history that any of the standard propensity-to-pay models can read. The hospital’s existing patient financial services stack was built for commercially insured patients with deductibles and for uninsured patients being screened for charity care. Neither workflow fits someone who is technically insured, technically owes $35, and is technically capped at 5% of an income the hospital does not know.

The natural instinct is to say the hospital will just eat it. Some will, and the bill does not let states drop providers for refusing to collect. But the copay is real revenue, the volume is enormous, and a system treating hundreds of thousands of expansion adults a year is looking at seven or eight figures of new patient responsibility that its current tools cannot touch. It is not the size of the copay that matters, it is that no infrastructure exists for it.

A fintech here is a point-of-service and post-service collection layer purpose-built for the Medicaid copay. Card-on-file at registration with a hard cap logic that knows the 5% of income ceiling and stops charging when it hits it. Payment plans denominated in amounts that make sense for someone earning $16,000 a year, which means single digit dollars a month, not the $50 minimums built into commercial tools. Integration with the state’s eligibility data so the tool knows whether this patient is above or below 100% of FPL and whether this service is exempt, because primary care, behavioral health, and SUD visits carry no copay and the last thing a hospital wants is to bill a copay it was legally barred from collecting. A bad debt module that sorts uncollectible copays into a bucket that can be reported for uncompensated care purposes. And, because this is a fintech and not a billing utility, a financing product that lets the hospital sell the copay receivable at a discount to a buyer who has better data on this population than the hospital does.

The unit economics are thin. Thirty five dollars, minus whatever the tool charges, minus collection cost, is not a lot of money per transaction. What makes it interesting is that the volume is the entire expansion adult population above 100% of FPL in every state that expanded, and that there is a clear regulatory date after which every hospital in those states needs the tool on the same morning. That kind of synchronized, regulatorily mandated demand is what lets a thin margin business get to scale fast enough to matter.

The competition is the existing patient payments vendors, and they will absolutely try to bolt this on. Their problem is that their propensity-to-pay models were trained on commercial patients and their workflows assume a patient who understands what a deductible is. Building for Medicaid patients means starting from cash, prepaid cards, and payment plans measured in dollars, which is a different product with a different data spine. The incumbents can build it. Whether they build it before October 2028 and whether they build it well are open questions, and open questions are where startups live.

Churn as an asset class

Third idea, and the one that sits closest to the data-heavy end of the health tech world. The combination of six month redeterminations, work requirements, and a 30 day retro window is going to produce a very large population of people who lose Medicaid coverage for procedural reasons, show up at a hospital while uncovered, and are in fact eligible if someone bothers to re-enroll them.

The experience with work requirements in Arkansas in 2018 and with the post-pandemic unwinding in 2023 and 2024 both showed the same pattern: the majority of disenrollments were procedural, not substantive. People did not fail the eligibility test, they failed to return a form, or did not know there was a form, or moved and never got the form. Under the old rules, a hospital that treated one of these patients had 90 days of retroactive coverage to get them re-enrolled and bill Medicaid for the visit. Under OBBBA, expansion adults get 30 days. That window is now short enough that a hospital’s existing eligibility vendor, which typically works a self-pay account weeks after discharge, will miss it routinely.

The fintech shape here is a company that buys or finances self-pay accounts from expansion adults at a discount, contingent on the company’s ability to get the patient re-enrolled inside the retro window and convert the self-pay account into a Medicaid claim. The hospital gets cash now for an account it was going to write off. The company takes the enrollment risk and the timing risk and keeps the spread between what it paid for the account and what Medicaid reimburses. Think of it as receivables factoring where the receivable does not technically exist yet and the factoring firm’s job is to create it.

The data spine is what makes this a health tech company rather than a collections agency. The company needs to know, at the moment of registration or ideally before, that this patient was on Medicaid six months ago, that they fell off for a procedural reason, that they are likely still eligible, and that the state’s re-enrollment process can be completed inside 30 days. That means real-time eligibility data, historical enrollment data, work requirement exemption logic, and a workflow that starts at the front desk rather than in the business office. It is the kind of thing that a company with deep access to provider data and state eligibility systems could build faster than anyone else, which is a not-so-subtle observation about who the natural founders are.

The competition is the existing eligibility and enrollment vendors, several of which are owned by private equity and bolted onto larger RCM platforms. They will point out, correctly, that they already do Medicaid enrollment for hospitals. What they do not do is take balance sheet risk on the outcome. They charge a contingency fee when they succeed and walk away when they do not. A company willing to buy the account outright and eat the failures is offering the hospital something different: certainty, today, in exchange for a discount. Whether the discount is attractive depends on how good the company’s eligibility prediction is, which is exactly the kind of model that gets better with scale and worse in the hands of a vendor that treats it as a side business.

Why banks will not do this and PE-backed RCM will do it badly

It is worth being clear-eyed about who else could build each of these, because the answer shapes what kind of company to fund.

Commercial banks are the natural lenders to hospitals and they will not build the supplemental payment product. Not because it is unprofitable but because it requires a credit committee to understand Medicaid financing at a level that no regional bank has ever needed. Bank hospital lending is asset-based and covenant-based. It looks at the whole system. A supplemental payment facility looks at a single state program and prices the state’s likelihood of funding and paying it on schedule. Getting a bank credit committee comfortable with that would require the committee to learn what a preprint is, what a rating period is, why the CMS approval letter sometimes shows up after the payment, and why the state legislature’s budget process affects the receivable. That is a year of education for a product line that shrinks by statute. Banks will let a specialty lender do it and then buy the specialty lender in 2031, which is a perfectly fine exit.

Private credit funds have the appetite and the sophistication and lack the origination. A fund could absolutely buy a book of supplemental payment advances. What it cannot do is call two hundred safety-net CFOs, explain the product, model each state’s program, and paper the deals. Origination in this market is a relationship business run by people who have sat in hospital association finance committee meetings and know which state Medicaid directors actually pay on time. Private credit is the capital, not the company.

PE-backed RCM platforms are the competitor for the copay and churn businesses and they will try both. The problem is structural. RCM platforms make money on contingency fees against collected dollars, and their whole operating model is optimized for maximizing collections on accounts that already exist. Taking balance sheet risk on accounts that do not exist yet, or building a payment tool for a population whose average balance is $35, is off-strategy for a business that measures itself in percent of net collections on commercial AR. They will build something, it will be a bolt-on, it will be priced like everything else they sell, and it will be run by people whose bonuses depend on the commercial book. That is not a knock on the platforms, it is a description of why the copay and churn products can be built by a focused company and sold or partnered into those platforms later.

The founders who can actually build these are a specific type. They have worked in Medicaid finance at a state agency or a hospital association, or have run a supplemental payment program at a large safety-net system, or have built eligibility and enrollment products and understand the state data plumbing. They are not, in general, fintech people. Fintech people can be hired. The Medicaid finance knowledge is the scarce input, and it is scarce in a way that does not show up on a resume search, because the people who have it mostly do not think of themselves as founders and have never talked to a venture investor. Finding them is the actual work.

How it dies

Every thesis needs a section on how it fails, and this one has several plausible deaths, some of which have already been rehearsed in Congress.

The first is delay. The provider tax phase-down does not begin until October 2027 and the SDP step-downs do not begin until January 2028. That is more than a year from the date of this essay, and it spans a midterm election and the start of a new Congress. Hospital lobbies have already made noise about stretching the schedule, and there are members on both sides who represent rural districts full of hospitals that live on supplementals. A two year delay does not kill the lending business, it just pushes the origination window out. A permanent repeal of the phase-down does kill it, at least in the form described here. The odds of full repeal look low given the deficit math and the fact that the provisions are the pay-fors for other things the majority wanted, but low is not zero and the company needs to be structured to survive a delay.

The second is state backfill. When the safe harbor drops, a state has a choice: shrink the supplemental pool or replace the lost tax revenue with general fund dollars. Most states will not have the general fund dollars, which is the whole point of the provision, but a few will, and those states’ hospitals will not need bridge financing. California and New York are the obvious candidates to backfill some portion. That reduces the addressable market in exactly the states with the most supplemental dollars. The counterargument is that even in backfilling states, the timing lag on supplementals does not go away, and a lender that advances against the receivable still has a product. It is just a smaller product.

The third is that the ice cube melts faster than expected. If states respond to the tax cap by restructuring their supplementals more aggressively than the statutory minimum, the receivable base could shrink ahead of the schedule the company modeled. This is a modeling risk rather than an existential one, and the mitigation is conservative advance rates and short tenors. Nobody should be writing a three year facility against a supplemental payment in 2029.

The fourth is specific to the churn business: states get better at redeterminations. If ex parte renewal rates climb and procedural disenrollments fall, there are fewer people falling off the rolls and fewer accounts to buy. This would be good for everyone except the company. The unwinding experience suggests states are not going to get good at this quickly, and the six month cadence roughly doubles the number of opportunities to mess it up, but a company built on administrative failure is a company with a ceiling.

The fifth is boring: regulatory scrutiny of the lending itself. A specialty lender advancing against Medicaid supplementals is, in effect, arbitraging federal matching dollars, and there are people at CMS who would not love that framing. The mitigation is that the lender never touches the Medicaid dollars directly. It advances against a hospital’s expected receivable, the same way any receivables lender does, and the state pays the hospital exactly as before. Nothing about the flow of funds changes. But a public story about hedge funds profiting from Medicaid cuts writes itself, and a company in this space should have its communications strategy figured out before the first story runs, not after.

What to fund

Stripped down, the recommendation is this. The supplemental payment lender is the venture. It has a defensible moat built on expertise nobody else has bothered to acquire, a client base nobody else is courting, a receivable base measured in tens of billions, and a credit profile that is unusually predictable because Congress wrote the loss curve into the law. It is a transition product with a sunset, and it should be built and funded as one, with a clear plan to migrate the client relationships into general safety-net liquidity products before the supplemental book winds down. The exit is a bank or a private credit platform buying the origination engine and the book sometime around 2030 or 2031, at which point the founders will have built something that looked impossible to underwrite in 2026 and looked obvious in hindsight.

The copay product and the churn product are real but smaller and closer to incumbent turf. They make sense as products inside a company that already has deep provider data and state eligibility access, or as focused startups that plan to sell into the RCM platforms within a few years. The churn business in particular is a data company wearing a factoring company’s clothes, and the right founding team is one that starts from the eligibility data and adds the balance sheet, not the other way around.

The common thread is that OBBBA did not just cut Medicaid. It turned a set of vague, politically contingent, slow-moving cash flows into a set of dated, sloped, statutorily defined ones. Predictability is the raw material of finance. Healthcare has never had much of it on the Medicaid side, and now, for a five year window in expansion states, it does. The window closes in 2032. The companies that get built before it closes will own the safety-net hospital relationships that everyone else ignored while they were busy building yet another prior auth tool. That is not a bad place to be standing when the ice cube finally melts

.

Provider taxes in expansion states drop from 6% to 3.5% of net patient revenue between FY2028 and FY2032. State directed payments step do…

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Provider taxes in expansion states drop from 6% to 3.5% of net patient revenue between FY2028 and FY2032. State directed payments step down 10 points per year starting January 2028. That is roughly $340B in program changes with specific dates.

The wrinkle: a meaningful share of Medicaid supplemental revenue already has a 12-18 month tail. The cash hole and the receivable lag stack on top of each other. Existing bank lines were not sized for this.

The fintech that does not exist yet: a specialty lender that underwrites the state program, not the hospital. The moat is Medicaid finance expertise, not balance sheet size. The asset shrinks on a statutory schedule, which is actually good for credit risk.

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🎧 Podcast episode for paid subscribers only. Also available on Apple Podcasts and Spotify.

Thoughts on Healthcare Markets & Technology

Fixing 340B Without Blowing It Up: The Specific Regulatory Changes to Ceiling Prices, Contract Pharmacies, Rebates, Patient Definition, and Transparency That Would Make the Program Actually Work

The 340B drug discount program moved $124 billion in purchases last year. It is run under a 1992 statute that never defined what a patient is, never limited contract pharmacies, and never required anyone to report what happened to the savings. A thread on why that matters…

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8 days ago · Thoughts on Healthcare

To listen to paid episodes in Apple or Spotify, link your Substack subscription via the show settings on those platforms (instructions inside the Substack app under Subscriptions → Podcast).

Table of Contents

1. The mess in one paragraph

2. Define patient like an adult

3. Contract pharmacies need a leash, not a cage

4. Rebates, but with guardrails

5. Duplicate discounts and the Medicaid data problem

6. Make the discount show up somewhere visible

7. Give HRSA actual teeth and an actual budget

8. What Congress has to do vs what HRSA can do

9. Who wins, who loses, who pretends to lose

Abstract

• 340B is a roughly 124 billion dollar a year program run by a 1992 statute, a couple dozen employees, and a lot of vibes

• Most of the fighting (contract pharmacy restrictions, rebate pilots, state laws, duplicate discounts) traces back to four or five undefined terms

• This piece lays out the specific reg changes that would fix most of it: a real patient definition, a contract pharmacy registration and data standard, a rebate model with hard turnaround and audit rights, a claims-level duplicate discount clearinghouse, mandatory savings reporting, and enforcement authority HRSA can use without getting sued into a ditch

• Splits each fix into what HRSA can do alone vs what needs Congress

• Ends with the honest scorecard of who gains and who loses, and why the loudest opponents of reform are not always the ones with the most to lose

  Thoughts on Healthcare Markets & Technology is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

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In 2010, guidance changed the contract pharmacy rule from one per entity to unlimi…

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🎧 Part I Podcast free on Apple Podcasts and Spotify.

Thoughts on Healthcare Markets & Technology

Part I: The Mandatory Model Operator: the risk bearing episode company hospitals need before TEAM downside hits on Jan 1, 2027, sized for a $5M preseed & a $25M seed, w the contract by contract plan

742 hospitals enter two-sided Medicare financial risk on Jan 1, 2027. The industry built to help them was acquired by UnitedHealth, CVS, and Aetna - and repurposed for Medicare Advantage. The vacancy is real and the deadline is fixed…

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9 days ago · Thoughts on Healthcare

🎧 Part II Podcast episode for paid subscribers only. Also available on Apple Podcasts and Spotify.

Thoughts on Healthcare Markets & Technology

Part II: The Mandatory Model Operator: the risk bearing episode company hospitals need before TEAM downside hits on Jan 1, 2027, sized for a $5M preseed & a $25M seed, w the contract by contract plan

742 hospitals enter two-sided Medicare financial risk on Jan 1, 2027. The industry built to help them was acquired by UnitedHealth, CVS, and Aetna - and repurposed for Medicare Advantage. The vacancy is real and the deadline is fixed…

Listen now

9 days ago · Thoughts on Healthcare

To listen to paid episodes in Apple or Spotify, link your Substack subscription via the show settings on those platforms (instructions inside the Substack app under Subscriptions → Podcast).

Table of Contents

1. Why this and why now

2. Where the old suppliers went

3. What the business actually does

4. Sizing it without lying

5. Who pays and why they pay

6. The preseed: five million dollars and twelve months

7. Weeks one through eight

8. Months three through six

9. Months seven through twelve

10. The milestones that unlock the mega seed

11. What the twenty five million buys

12. Where it breaks

    Thoughts on Healthcare Markets & Technology is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Table of Contents

• Roughly 742 hospitals are in a mandatory CMS bundled payment model for five surgical episodes, and on January 1, 2027 the model flips from its initial upside‑only year to three participation tracks, with most urban hospitals moving into Track 3 with up to 20 percent two‑sided risk.

• The bundled payment operator industry that hospitals relied on a decade ago was bought by payers and either dissolved or turned inward, so a majority of TEAM hospitals are entering downside risk with no operating partner and a consultant’s spreadsheet.

• The business is a tech enabled episode operating company that manages the 30 day post discharge window, administers physician and post acute gainsharing, runs the documentation program that sets target prices, and, at the seed stage, sells downside protection backed by its own capital.

• The near term revenue pool is a share of a savings opportunity in the high hundreds of millions per year across TEAM alone, growing with each mandatory model CMS adds, starting with the specialist model that goes live the following year.

• A five million dollar preseed should buy twenty hospitals under contingency contract before the risk switch, twelve thousand episodes under management, and measured operational results on the metrics that drive reconciliation.

• The twenty five million dollar seed capitalizes the downside guarantee, which is the product that turns a services vendor into the entity every mandatory model hospital has to call.

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Optum projects a majority of mandatory TEAM participants will lose money averaging $1.2M per facility. The reconciliation…

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Optum projects a majority of mandatory TEAM participants will lose money averaging $1.2M per facility. The reconciliation reports land in early 2028 - after hospitals are already deep into year two of real downside.

The old convener companies (Remedy, naviHealth, Archway) worked. They just got absorbed by payers who needed post-acute utilization management for their own members, not hospital-facing episode operators.

The resulting business: a tech-enabled episode company that manages the 30-day post-discharge window, runs gainsharing, improves target prices through documentation, and sells downside protection backed by its own balance sheet.

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Thoughts on Healthcare Markets & Technology

The Exemption Machine: the Medicaid work requirement business nobody has built, why it fits a $5M preseed and a $25M seed, and the contract by contract plan to get there before January 1, 2027

Starting Jan 1, 2027, ~18.5 million Medicaid expansion adults must prove 80 hours/month of community engagement or a medical exemption or lose coverage. Federal projections put disenrollment in the millions. Most of those losses are paperwork failures, not job gains…

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10 days ago · Thoughts on Healthcare

To listen to paid episodes in Apple or Spotify, link your Substack subscription via the show settings on those platforms (instructions inside the Substack app under Subscriptions → Podcast).

Table of Contents

1. Why this and why now

2. The mandate with the abandoned supply

3. What the business actually does

4. Sizing it without lying

5. Who pays and why they pay

6. The preseed: five million dollars and twelve months

7. Weeks one through eight

8. Months three through six

9. Months seven through twelve

10. The milestones that unlock the mega seed

11. What the twenty five million buys

12. Where it breaks

    Thoughts on Healthcare Markets & Technology is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Abstract

• Starting January 1, 2027, all states that have adopted the ACA Medicaid expansion (or equivalent expansion coverage) must condition Medicaid coverage for applicable expansion adults on 80 hours per month of qualifying community engagement activity or a documented exemption, with some states, including Nebraska, authorized to implement earlier at state option.

• The interim final rule interprets the medical frailty exemption as a clinical determination tied to functional impairment rather than a simple diagnosis code lookup, and no organization in the ecosystem is currently staffed to produce those determinations at the required scale.

• The business is a tech enabled clinical exemption and reinstatement service sold on contingency to FQHCs, community behavioral health providers, hospitals, and managed care plans, structurally modeled on the SSDI advocacy and hospital eligibility vendor industries.

• The addressable pool is roughly 18.5 million subject enrollees, several million of whom have qualifying conditions, with a per member value to the payer of roughly $6,000 to $8,000 a year in capitation and a per member value to providers measured in avoided bad debt.

• A $5 million preseed should buy three early state beachheads, twenty thousand completed determinations, a measured exemption rate, a reinstatement win rate, and signed contingency contracts with a dozen provider organizations and one plan before the national go live date.

• The $25 million seed funds the expansion to all applicable expansion states in the first half of 2027, when the disenrollment wave actually hits and every plan and health system finance chief is suddenly reading the rule.

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States assumed they could automate exemptions with a diagnosis code sweep. A federal int…

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🎧 Podcast episode for paid subscribers only. Also available on Apple Podcasts and Spotify.

Thoughts on Healthcare Markets & Technology

Companies to Incubate for Health Systems: A Field Guide Spanning Prior Auth Automation, Virtual Card Interchange, Workforce Intelligence, Payer Contract Analytics & the RCM Plays Hiding in Plain Sight

Hospitals are famously terrible software buyers. 18-month sales cycles. Pilots that stall. CIOs buried under Epic tickets. And yet the incubation model says: build INSIDE the health system, not into it. Here is why that matters…

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12 days ago · Thoughts on Healthcare

To listen to paid episodes in Apple or Spotify, link your Substack subscription via the show settings on those platforms (instructions inside the Substack app under Subscriptions → Podcast).

Abstract

1. The premise, or why hospitals are the best worst customers

2. Revenue cycle and the prior auth forcing function

3. The CFO stack: cards, treasury, receivables, bad debt

4. Workforce: the agency markup is the product

5. Benchmarking businesses and the data network effect

6. The quiet operational layer

7. The vibe code test

8. How these die

9. Where the money actually is

Table of Contents

• Thesis: health systems are terrible software buyers and phenomenal design partners, which makes them ideal incubation anchors for companies built inside their workflows rather than sold into them

• Covers roughly 40 company concepts across five buckets: revenue cycle and prior auth, financial infrastructure, workforce, benchmarking and intelligence platforms, and operational tooling

• Key numbers along the way: about $13B in annual PA administrative burden, roughly 13 to 16 hours per physician per week on prior auth, roughly 40 to 100 percent agency markups, 1.5 to 5 percent virtual card interchange, 2 to 4 percent systematic payer underpayment, tens of billions in hospital bad debt, and on the order of $66B plus in annual 340B discounts

• Argues that roughly a third of these can be vibe coded to a credible seed demo in weeks because the pattern is structured data in, LLM reasoning in the middle, action-oriented UI out

• Ends with an honest accounting of what kills these companies: sales cycles, IT governance committees, pilots that never convert, and performance pricing that sounds great until the finance team has to attribute savings

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Prior auth alone is a 13 billion dollar annual administrative burden. Physicians spend roughly 13 hours a week on it. CMS just …

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🎧 Part I Podcast free on Apple Podcasts and Spotify.

Thoughts on Healthcare Markets & Technology

Part I: MCIT, TCET & RAPID Compared: A Field Guide to Medicare's 3 Breakthrough Device Coverage Pathways, Why Two Are Effectively Dead, & What the August 2026 RAPID Proposed Notice Actually Changes

FDA has issued 1,284 breakthrough device designations. Medicare is not obligated to pay for a single one. That gap has now produced three separate federal policy attempts in five years…

Listen now

13 days ago · Thoughts on Healthcare

🎧 Part II Podcast episode for paid subscribers only. Also available on Apple Podcasts and Spotify.

Thoughts on Healthcare Markets & Technology

Part II: MCIT, TCET & RAPID Compared: A Field Guide to Medicare's 3 Breakthrough Device Coverage Pathways, Why Two Are Effectively Dead, & What the August 2026 RAPID Proposed Notice Actually Changes

FDA has issued 1,284 breakthrough device designations. Medicare is not obligated to pay for a single one. That gap has now produced three separate federal policy attempts in five years…

Listen now

13 days ago · Thoughts on Healthcare

To listen to paid episodes in Apple or Spotify, link your Substack subscription via the show settings on those platforms (instructions inside the Substack app under Subscriptions → Podcast).

Table of Contents

1. The problem all three pathways address

2. MCIT, the one that died

3. TCET, the one that exists, barely

4. RAPID, the newest lane

5. The side by side

6. What this means for device companies and investors

7. FAQ

   Thoughts on Healthcare Markets & Technology is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Abstract

• FDA authorization does not mean Medicare pays. The gap between market authorization and durable Medicare coverage routinely runs years, and for breakthrough devices that gap is the single biggest killer of commercial models.

• MCIT (finalized January 2021, repealed November 2021) promised four years of automatic national coverage the day FDA authorized a breakthrough device. It never took effect.

• TCET (final notice August 2024) is the current live pathway: capped at roughly five devices a year, nomination roughly 18–24 months before your anticipated FDA decision, coverage with evidence development on the back end. Exactly one device has publicly gone through the front door.

• RAPID (announced April 2026, proposed procedural notice published August 2026) is the new joint CMS and FDA play: a proposed NCD posted the same day FDA authorizes, final coverage roughly 60 days later for Class II and 90 for Class III. Eligibility is narrow, IVDs are out, and TCET intake is paused while this stands up.

• Comment period on the RAPID notice closes October 13, 2026. Nothing about coding or payment is addressed, and CMS has now moved from proposing to **finalizing** repeal of the IPPS and OPPS alternative breakthrough pathways on the payment side, starting with FY 2028 applications. Coverage is speeding up while payment is tightening. Plan accordingly.

The problem all three pathways address

Start with the number that makes device CFOs drink. FDA has handed out more than 1,284 breakthrough device designations as of March 31, 2026, and the designation comes with priority review, sprint discussions, extra FDA attention, the works. What it does not come with is a dollar. Medicare, which covers the population most breakthrough devices are actually built for, treats FDA authorization as the starting gun for a completely separate multi year process, not the finish line. A company can clear a PMA, pop champagne, issue the press release, and then discover that the largest payer in the country has no obligation to reimburse a single unit.

The mechanics of the gap are worth spelling out because the three pathways in this piece are all attempts to compress different parts of it. Coverage, coding, and payment are three separate machines. Coverage means Medicare agrees the thing is reasonable and necessary. That happens either nationally through a National Coverage Determination, which historically takes nine to twelve months once CMS actually opens one and CMS opens very few, or locally through Medicare Administrative Contractors making their own calls across a patchwork of jurisdictions. Most devices never get an NCD at all. They live in MAC purgatory, where coverage varies by region, claims get adjudicated case by case, and a sales team spends two years explaining to hospitals why the same procedure pays in Florida and denies in Ohio. Coding runs on its own annual and quarterly cycles through CPT and HCPCS. Payment gets set through the fee schedules and, for new inpatient tech, through mechanisms like the new technology add on payment. Each machine has its own clock, its own staff, and its own indifference to your burn rate.

Stack the clocks and the practical result is that a breakthrough device can sit in commercial limbo for four, five, sometimes seven years after authorization before Medicare coverage looks anything like settled. Venture math does not survive that. A Series C medtech company raising on the promise of Medicare volume cannot tell LPs the reimbursement plan is “wait for a MAC medical director to retire.” So for the better part of a decade, industry, Congress, and two administrations of very different flavors have taken swings at building an express lane. Three of those swings have names: MCIT, TCET, and RAPID. One is dead, one is on life support, and one just got published in the Federal Register with fresh paint and a 60 day comment clock. The comparison matters because diligence decks keep confusing them, and because which lane a company can actually use depends heavily on where it sits in its regulatory lifecycle.

MCIT, the one that died

Medicare Coverage of Innovative Technology was the maximalist version. Born out of a 2019 executive order pushing Medicare to keep pace with innovation, proposed in September 2020, and finalized in the last week of the first Trump administration in January 2021, MCIT said the quiet part loudly: any FDA designated breakthrough device would get automatic national Medicare coverage starting the day of market authorization and running four full years, with eligibility for devices authorized in the prior two years. No nomination process. No evidence plan. No CMS review of whether the pivotal trial enrolled anyone over 65. FDA says yes, Medicare pays, see you in four years.

Device companies loved it for obvious reasons. It converted a coverage question into a regulatory one, and regulatory questions have knowable timelines. The problem, and the reason it never survived the change in administration, is that FDA and CMS answer genuinely different questions. FDA asks whether a device is safe and effective for its intended use, often based on trials that enroll few or zero Medicare beneficiaries. CMS asks whether the item is reasonable and necessary for the Medicare population specifically, a population that skews older, sicker, and more comorbid than the average pivotal trial cohort. MCIT bolted the second answer to the first and threw away the key. The new administration delayed the effective date twice during 2021, took comments, and repealed the rule outright in November 2021 before a single device ever received MCIT coverage. The stated rationale was straightforward: automatic coverage with no Medicare specific evidence requirement, and no practical mechanism for CMS to pull coverage on a device showing safety signals short of full FDA action, was a bridge too far. The rule died a paper death, undefeated and untested, which is why it still gets invoked at conferences like a martyred prophet.

What survived is more interesting than the corpse. The repeal notice conceded the underlying problem was real and promised a replacement that kept the speed while adding evidence guardrails. Every design choice in TCET, and honestly most of RAPID, reads as a direct response to a specific MCIT criticism. Automatic coverage became nominated coverage. No evidence requirements became evidence development plans. Unlimited eligibility became annual caps. MCIT is the ghost at every subsequent rulemaking, and CMS staff will tell you as much off the record with varying levels of eye rolling.

TCET, the one that exists, barely

Transitional Coverage for Emerging Technologies is what the repeal promise eventually produced, first as a notice with comment in June 2023 and then as a final procedural notice effective August 2024. The design is careful to the point of parody. A manufacturer self nominates roughly 18 to 24 months before its anticipated FDA decision date. CMS reviews nominations quarterly. Eligible devices must hold breakthrough designation, fall within a Medicare benefit category, not already be the subject of an existing NCD, and not be otherwise excluded from coverage by statute or regulation. In vitro diagnostics were effectively carved out at the start, with CMS punting nearly all diagnostic coverage back to the MACs on the theory that lab tests are their own specialized universe. That carve out alone removed a huge share of the breakthrough portfolio from contention, since diagnostics and algorithm driven tests are heavily represented in the designation pool.

For devices that make it in, the machinery is real but heavy. CMS and AHRQ work with the manufacturer on an evidence preview, essentially a systematic literature review that surfaces the gaps between the FDA evidence package and what Medicare wants to know. Then comes an evidence development plan that has to be approved before things move. The payoff is a commitment that CMS will aim to finalize an NCD within six months of FDA market authorization, with coverage typically granted under coverage with evidence development, meaning the company keeps generating data during a transition window generally understood to run about five years, after which CMS revisits and decides whether coverage becomes permanent, gets modified, or goes away. Compare that to the historical pattern where an NCD, if you could even get one opened, ate nine to twelve months after years of waiting in line, and TCET looks like genuine progress.

Now the uptake numbers, which are where the comedy lives. CMS said it anticipated accepting up to five TCET candidates per year, a cap it justified on staffing grounds, and which industry immediately pointed out was a rounding error against a designation pool adding well over a hundred new breakthroughs annually. Two years in, the publicly visible throughput is one device. EBR Systems’ WiSE leadless left ventricular pacing system became the first technology to enter the program, and CMS initiated the national coverage determination review in June 2026 with a projected final NCD in early 2027. That is the entire visible pipeline. One cardiac device, moving at what counts as blistering speed for an NCD and glacial speed for anything else in American commerce. Five slots a year was always going to be a lottery, and it turns out most manufacturers looked at the 18–24 month pre nomination requirement, the AHRQ literature review, the CED obligations, and the lottery odds, and quietly decided the MAC by MAC grind was less painful. Which brings the story to April 2026, when CMS essentially agreed with them.

RAPID, the newest lane

The Regulatory Alignment for Predictable and Immediate Device coverage pathway arrived in two acts. Act one was the joint CMS and FDA announcement on April 23, 2026, heavy on ambition and light on mechanics, with CMS leadership talking publicly about delivering Medicare coverage within 60 to 90 days of FDA approval and officials floating that roughly 40 devices currently qualify with maybe 20 more on the bubble. Act two was the proposed procedural notice, CMS-3487-NC, issued in early August 2026 and published in the Federal Register days later, with a 60 day comment period closing on October 13, 2026. The final notice, whenever it lands, is what makes the pathway operational.

Here is the core mechanic, and it is genuinely novel. Instead of starting the coverage conversation after FDA authorization, RAPID moves it before the pivotal trial even starts. CMS and FDA jointly engage with the manufacturer at the IDE pre submission stage, while the pivotal study can still be shaped, so that a single trial design answers both the FDA question and the Medicare question. The study must enroll Medicare beneficiaries, which sounds obvious and has historically been anything but. In exchange, CMS commits to posting a proposed NCD the same day FDA grants market authorization, running a 30 day public comment period, and finalizing national coverage as soon as 60 days after authorization for Class II devices and 90 days for Class III. RAPID NCDs also jump the queue, getting priority over everything else on the CMS wait list, which the non breakthrough world will have feelings about.

Eligibility is where the fine print bites. The pathway targets breakthrough devices in FDA’s Total Product Life Cycle Advisory Program, with presumptive Class II devices heading toward a De Novo required to be in TAP and Class III devices heading toward a PMA eligible regardless of TAP participation. The device has to be at the pre submission stage of its IDE. Devices already enrolled in an active pivotal IDE study are out, though CMS explicitly asked for comment on whether some on ramp should exist for them, so expect the comment docket to be full of manufacturers arguing their trial is special. IVDs are excluded outright, continuing the TCET tradition of telling diagnostics companies to go talk to their MAC. Software as a medical device is not categorically excluded, which is one of the more quietly consequential lines in the notice given where the breakthrough pipeline is heading. And in the same breath, CMS proposed pausing TCET intake for new candidates as of publication, while devices already inside TCET continue and the separate parallel review program survives. The polite reading is consolidation. The accurate reading is that CMS looked at a pathway with one enrollee and decided not to keep staffing the front desk.

Two things the notice conspicuously does not do. First, it says nothing about coding or payment, so a RAPID device could hold a shiny final NCD 60 days after authorization and still be waiting on a HCPCS code and a payment rate, which is like being handed a key to a car with no engine. Second, and running in the opposite direction, CMS has now moved beyond proposal and in the FY 2027 IPPS and OPPS rules is eliminating the alternative NTAP and device pass through pathways that let breakthrough devices collect add on payments without demonstrating substantial clinical improvement, beginning with FY 2028 applications. So the same agency is accelerating coverage while raising the bar on payment. Anyone modeling RAPID economics without modeling the NTAP change is doing half a diligence.

The side by side

Since a proper table would violate the formatting religion of this publication, here is the comparison in prose, structured the way a diligence memo would ask the questions. On eligibility, MCIT was the open bar: any breakthrough device, full stop, retroactive two years. TCET narrowed to breakthrough devices in a benefit category with no existing NCD, minus IVDs, and capped at about five accepted candidates annually. RAPID narrows differently: breakthrough devices caught at the IDE pre submission stage, with presumptive Class II devices required to be in TAP and heading for a De Novo and Class III devices heading for a PMA eligible with or without TAP, IVDs excluded, but with working capacity estimated at 40 to 60 devices, roughly a tenfold expansion over TCET’s cap. On the evidence ask, MCIT demanded nothing beyond FDA authorization, which is why it is dead. TCET demands an evidence preview, an approved evidence development plan, and ongoing CED data generation. RAPID demands trial design alignment up front, including Medicare beneficiary enrollment in the pivotal, effectively front loading the evidence work into the study a company was going to run anyway.

On timing, MCIT promised coverage on day zero of authorization, lasting four years. TCET aims for a final NCD within six months of authorization, with transitional CED coverage running around five years before a permanence decision. RAPID promises a proposed NCD on day zero and a final one at day 60 or 90 depending on device class, though the honest asterisk is that the clock only starts after a company has spent years inside TAP (for Class II) and its IDE study, so the first same day NCD under this program plausibly lands closer to the end of the decade than anyone’s pitch deck admits. On current status as of late August 2026: MCIT is repealed and never operated. TCET is final, operational, paused for new intake, and carrying exactly one public passenger toward a projected early 2027 NCD. RAPID is a proposed notice with comments due October 13, 2026 and no effective date until the final notice publishes. On what each does for payment: nothing, nothing, and nothing, respectively, which is the most consistent design feature across all three.

What this means for device companies and investors

For operators, the strategic question is brutally stage dependent. A company that already holds market authorization gets essentially nothing from RAPID as proposed, and with TCET intake paused, the realistic play remains the old one: MAC engagement, local coverage, registry data, and lobbying for an NCD the traditional way. A company mid pivotal is in the awkward middle, currently ineligible for RAPID and invited to say so loudly in the comment docket before October 13. The real winners are earlier stage: a breakthrough designated company that has not yet filed its IDE pre submission can now architect one trial to serve two masters, which changes protocol design decisions being made this quarter. Enroll Medicare beneficiaries in the pivotal, get into TAP if you are a presumptive Class II De Novo, engage both agencies early, and the reward is a coverage timeline that compresses from years to weeks post authorization. That is not a marginal improvement. That is a different company.

For investors, the underwriting implications are worth being precise about. In a diligence model, the pathway a target can actually access should now be a checklist item with four boxes: breakthrough designation held, TAP participation status (for Class II), IDE stage, and whether the pivotal enrolls Medicare beneficiaries. A pre IDE breakthrough company that checks all four can credibly model national Medicare coverage inside a quarter of authorization, which pulls revenue inflection forward and materially changes the amount of capital needed to bridge from approval to commercial scale. That is the bull case, and it is real. The bear case deserves equal airtime. This is a proposed notice, not a final one, and procedural notices have died before, MCIT being the canonical example of a finalized rule that still never operated. The pathway addresses coverage only, so the coding and payment clocks still run at their old speeds, and the now finalized NTAP and pass through alternative pathway repeal means the inpatient payment sweetener that breakthrough devices enjoyed is going away for FY 2028 applications and beyond, with limited grandfathering. Capacity claims of 40 to 60 devices assume CMS staffing that has not been demonstrated at anything close to that scale, given the same coverage shop that could only process five TCET candidates a year now proposes to run ten times the volume with same day deliverables. And history offers a sobering comp: parallel review, the last big structural alignment between FDA and CMS, existed for over a decade and moved a tiny handful of products, because alignment on paper does not equal throughput in practice.

The portfolio level read: expect a premium on breakthrough designated, pre pivotal assets with Medicare heavy indications, expect diagnostics companies to stay exactly as stuck as they were, and expect at least one 2027 vintage medtech deal to blow up because someone modeled RAPID timelines for a device that was already three years into its IDE. Also watch the comment docket. The fights over active IDE eligibility, SaMD treatment, and coding linkage will tell you what the final notice looks like before CMS does.

FAQ

Is MCIT still active? No. It was finalized in January 2021, delayed twice, and repealed in November 2021 without ever taking effect. No device ever received coverage under it. If a pitch deck references MCIT coverage as a go to market plan, that deck was written by someone who stopped reading the Federal Register five years ago.

How long does TCET coverage last? Coverage under TCET is granted through coverage with evidence development, with the transitional period tied to the device’s approved evidence development plan, generally understood to run about five years. After that, CMS reviews the accumulated evidence and decides whether coverage becomes permanent, gets modified, or ends. Note that new TCET intake is paused under the RAPID proposed notice, though devices already in the program continue.

What replaced MCIT? Formally, TCET replaced it in 2024 with evidence requirements and a five per year cap. Practically, RAPID is the spiritual successor, restoring the day zero coverage ambition while fixing the original sin by moving evidence alignment before the pivotal trial instead of skipping it entirely.

Does RAPID cover diagnostics? No. IVDs are excluded from the proposed pathway, as they effectively were from TCET, with coverage decisions remaining with the MACs. Software as a medical device is not categorically excluded, which matters more each year.

Does RAPID solve payment? Not even a little. The proposed notice addresses coverage only, coding and payment run on their existing cycles, and CMS has now finalized the repeal of the NTAP and OPPS alternative pathways for breakthrough devices beginning with FY 2028 applications. Fast coverage plus slow coding plus tighter add on payments is the actual 2027–2028 operating environment. Model all three

.