Friday, August 7, 2026

CMS Releases "RAPID" Plan for Rapid, Innovative NCD's

 A couple months ago, CMS announced it would nix the TCET program for rapid NCDs with Coverage with Evidence Development.  And replace it with RAPID.  However, details only appeared late Friday, August 7, in the Federal Register.

"Regulatory Alignment for Predictable and Immediate Device" RAPID coverage pathway.

Find it here:

https://www.federalregister.gov/public-inspection/2026-16368/medicare-program-regulatory-alignment-for-predictable-and-immediate-device-coverage-pathway

(This is advance-text, Fed Reg typeset version to appear August 11.)

There's also a new press release.

Despite the ironic fact that two major, early, prominent Parallel Review case studies were diagnostics - Cologuard 2014 and FMI 2018 - diagnostics (IVD) are excluded from RAPID. 

This posture of IVD exclusion may be a mistake. The output of new diagnostics LCDs at Novitas in recent years was mainly noncoverage of 9/9 oncology tests in 2025. The output of new Dx LCDs at NGS MAC (Wellpoint federal) in several years is about N of 1 - Renalytix KidneyIntel. The MolDx program is great at follow-on tests (for MRD or CGP) but it's a rare day when MolDx issues an entirely new LCD, and they follow a 2 to 3 year delay queue, easily enough to bankrupt a startup. In short, CMS may need to take a 360 view of their proposed exclusion of IVDs from rapid coverage. 

Here's a fast and early read by AI.


 

RAPID: Medicare's Latest Attempt to Solve the FDA-to-Coverage Gap

CMS has now produced another special pathway intended to shorten the sometimes painfully long interval between FDA authorization of an innovative medical device and Medicare coverage.

The newest acronym is RAPID — Regulatory Alignment for Predictable and Immediate Device Coverage. CMS and FDA first announced RAPID on April 23, 2026; on August 7 CMS released a detailed proposed procedural notice, scheduled for Federal Register publication August 11.

If the history seems familiar, it should. Medicare has been trying versions of this problem for quite a while.

There was Parallel Review, announced as a pilot in 2010 and formally implemented in 2016. FDA and CMS could meet with a manufacturer during development and later review the pivotal evidence concurrently, reducing the gap between FDA authorization and a CMS proposed NCD. Its most memorable early successes included Cologuard and, later, FoundationOne CDx. CMS itself describes Parallel Review as having two stages: early feedback on the pivotal trial followed by concurrent FDA/CMS review of the results.

Then came MCIT — Medicare Coverage of Innovative Technology, finalized during the first Trump administration in January 2021. MCIT was the bold version: FDA Breakthrough Device authorization would essentially open the door to immediate nationwide Medicare coverage, potentially lasting four years.

But MCIT never really got to govern. The incoming Biden administration first delayed and then repealed it in November 2021. The central objection was that FDA's determination of safety and effectiveness was not necessarily enough to establish Medicare's separate statutory requirement that an item be “reasonable and necessary” for Medicare beneficiaries—an older population with more comorbidities than many FDA trial populations.

Biden-era CMS eventually produced TCET — Transitional Coverage for Emerging Technologies, finalized in August 2024. TCET kept the FDA Breakthrough Device idea but restored a recognizably CMS-style evidence process: premarket engagement, an Evidence Preview, identification of evidence gaps, potentially an Evidence Development Plan, and an NCD that might employ Coverage with Evidence Development. CMS describes TCET as intended for Breakthrough Devices whose evidence may still be limited or developing for Medicare purposes.

And now TCET itself is being pushed aside.

CMS states that TCET will be paused for new candidates while CMS focuses on RAPID.

One begins to think of the late Roman Empire: Parallel Review, MCIT, TCET, RAPID—each new emperor arriving with a new acronym and a solution to the succession problem.

So What Is Different About RAPID?

RAPID actually has a fairly clear and interesting idea behind it.

The fundamental FDA/CMS problem has always been that the agencies ask somewhat different questions.

FDA asks whether the device satisfies the applicable regulatory standards for safety and effectiveness. CMS asks whether the item or service is reasonable and necessary for Medicare beneficiaries. FDA clinical trials do not necessarily contain enough older patients, patients with multiple chronic conditions, or outcomes that CMS considers decisive for Medicare coverage. FDA authorization therefore does not automatically imply Medicare coverage. CMS spends several pages emphasizing precisely this distinction.

Under the traditional sequence, a manufacturer could therefore spend years conducting a beautiful FDA program, obtain approval, walk across town to Medicare—and discover that CMS wanted somewhat different evidence.

RAPID tries to prevent that problem before the pivotal trial starts.

As CMS summarizes it in the new fact sheet, the agency will join the FDA/manufacturer process through early and frequent engagement, allowing CMS experts to identify the clinical outcomes most relevant to Medicare beneficiaries while the device is still in development.

Thus, schematically:

Old model:

FDA trial → FDA authorization → CMS review → “Where are the Medicare data?”

RAPID model:

FDA + CMS + manufacturer agree on Medicare-relevant outcomes → pivotal IDE trial → FDA authorization + virtually simultaneous CMS NCD process.

That may be the most important conceptual difference between RAPID and MCIT.

MCIT tried to eliminate the FDA-Medicare gap by treating FDA authorization as sufficient to trigger coverage. RAPID tries to eliminate the gap by making sure the FDA development program generates the evidence CMS will need.

click to enlarge


You Have to Get Into RAPID Very Early

RAPID is not a rescue program for a device that has already received FDA approval and suddenly discovers it has a Medicare problem.

Quite the opposite.

The device generally must enter RAPID at the IDE pre-submission stage. The manufacturer must plan an IDE study that enrolls Medicare beneficiaries and evaluates clinical outcomes that FDA considers appropriate and CMS agrees would demonstrate improved health outcomes for Medicare beneficiaries.

CMS's August fact sheet makes the point especially plainly: devices already market authorized—or even devices for which an IDE study is already underway—are generally too late for RAPID.

CMS does ask for comments on whether there should be a temporary transition mechanism for some devices whose IDE studies are already underway. That may be important for companies caught between TCET and RAPID, but it is not the basic design of the program.

RAPID therefore pushes Medicare reimbursement strategy remarkably far upstream.

For an eligible company, Medicare coverage planning becomes part of pivotal clinical-trial design.

That is probably RAPID's most consequential feature.

Who Is Eligible?

The pathway is deliberately narrow.

For Class II devices, RAPID generally requires an FDA Breakthrough-designated device enrolled in FDA's Total Product Life Cycle Advisory Program (TAP) (linkand proceeding toward a De Novo request.

For Class III devices, RAPID requires Breakthrough designation and a planned PMA; TAP participation is not required.

The product must also fit, or at least not obviously fail to fit, within a Medicare benefit category; it cannot already be controlled by an existing NCD; it must be separately payable; and it cannot otherwise be excluded from Medicare coverage.

RAPID is voluntary. A manufacturer can also withdraw before CMS issues the proposed NCD—for example, if the evidence disappoints or if local MAC coverage looks strategically preferable.

The Payoff: FDA Authorization and the NCD Nearly Converge

If everything works, the payoff is dramatic.

Once the IDE study is completed, FDA provides CMS with the relevant study information. If the manufacturer proceeds with RAPID and the study has satisfactorily demonstrated improvement in the agreed clinical outcome, CMS plans to post the NCD tracking sheet and proposed NCD on the same day FDA grants market authorization.

There will then be a 30-day public comment period.

CMS's goal is a final NCD approximately:

60 days after FDA authorization for Class II devices, and

90 days after FDA authorization for Class III devices.

CMS's August fact sheet translates that into unusually plain English: national Medicare coverage could therefore begin as soon as 60 days after FDA authorization.

That is a striking contrast with the ordinary NCD process, which CMS itself says generally takes nine to twelve months.

It is also more aggressive than TCET's approximately six-month post-FDA target.

Notice, however, that RAPID is not literally MCIT-style instantaneous coverage. What is simultaneous with FDA authorization is the proposed NCD. Final coverage follows roughly two or three months later.

“Immediate” in the acronym therefore deserves a small Medicare asterisk.

RAPID Is Not Necessarily the End of Evidence Development

RAPID also doesn't mean every successful device automatically gets an unconditional §1862(a)(1)(A) NCD.

CMS says the amount of demonstrated improvement in clinical outcomes and the risk profile of the device will affect whether additional evidence development is required.

A lower-risk device may arrive at FDA authorization with sufficient evidence to support conventional “reasonable and necessary” coverage.

A higher-risk device may still have evidence gaps and receive coverage through CED — Coverage with Evidence Development. In that case CMS intends to coordinate, as much as possible, its evidence requirements with FDA-required post-approval studies rather than create duplicative research programs.

So RAPID isn't really eliminating CMS evidence review. It is moving much of it earlier.

That's an important distinction.

And Now the Bad News for Diagnostics

For readers in molecular diagnostics, there is one remarkably explicit paragraph.

IVDs are excluded.

FDA's legal definition of “device” includes in vitro diagnostic products, including laboratory tests. Thus, conceptually, an FDA Breakthrough-designated IVD might seem like an obvious RAPID candidate.

CMS says no.

CMS explains that IVDs and diagnostic laboratory tests constitute a specialized area of Medicare coverage policy and that CMS has historically delegated many such decisions to specialized Medicare Administrative Contractors. CMS therefore says that most Breakthrough IVD coverage decisions should continue through those MAC pathways.

The conclusion could hardly be clearer:

“IVD products will not be accepted into the RAPID coverage pathway.”

The August CMS fact sheet repeats the exclusion almost word for word.

An IVD manufacturer isn't forbidden from pursuing an ordinary NCD. CMS notes that in the unusual case where CMS and a manufacturer agree an NCD is appropriate, the manufacturer can use the normal NCD request process.

But RAPID itself is closed to diagnostics.

There is an historical irony here. Two of the landmark products associated with the older FDA-CMS Parallel Review program were diagnostics—Cologuard and FoundationOne CDx. The newest FDA/CMS coordination pathway now expressly sends IVDs back toward the MAC system.

Four Generations of the Same Problem

The lineage can now be summarized fairly simply:

ProgramApprox. eraBasic idea
Parallel Review2010–FDA and CMS engage and review in parallel
MCIT2021FDA Breakthrough authorization essentially triggers temporary Medicare coverage
TCET2024CMS evaluates evidence gaps and develops transitional NCD/CED coverage
RAPID2026Design the pivotal FDA evidence program up front to satisfy CMS too

The programs overlap conceptually more than the succession of acronyms suggests. In fact, RAPID contains a substantial amount of Parallel Review DNA.

Parallel Review already allowed FDA and CMS to provide feedback on a proposed pivotal trial and later evaluate the resulting evidence concurrently.

What RAPID adds is a much more formalized pathway around Breakthrough designation, TAP, IDE development, Medicare-specific clinical outcomes, and a commitment to synchronize the proposed NCD with FDA market authorization.

RAPID may therefore be viewed less as an entirely new species than as an ambitious, highly structured descendant of Parallel Review.

To Sum Up

There is a sensible policy idea here.

MCIT attacked the coverage lag at the back end: FDA has approved it, so Medicare should cover it.

TCET tried to manage the gap during the transition between FDA and Medicare.

RAPID attacks the problem at the front end: before you design your pivotal study, CMS tells you what it will need. Then one evidence-generation program has a fighting chance of satisfying both agencies.

If RAPID works as advertised, the great achievement won't really be turning a nine-month NCD into a 60-day NCD.

It will be avoiding the situation in which a manufacturer reaches FDA approval after years of product development and only then discovers that the evidence needed for Medicare coverage was never collected.

That is genuinely useful regulatory alignment.

Whether enough devices can satisfy RAPID's narrow eligibility rules—and whether CMS has the manpower to provide this degree of early engagement—is another question.

And for diagnostics, the question is largely academic.

RAPID may be the latest emperor in Medicare's revolving door of innovative-technology pathways, but IVDs aren't being invited into the palace.

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Sidebar: What Is FDA’s TAP Program?

FDA’s Total Product Life Cycle Advisory Program (TAP) is a voluntary CDRH program launched as a pilot in 2022 to give selected device developers unusually early, frequent, and strategic interaction with FDA—and to help connect them with other parties important to eventual adoption and patient access. FDA describes TAP as a “medical device accelerator,” with dedicated TAP advisers helping sponsors identify and resolve development and market-access issues earlier in the product life cycle. (U.S. Food and Drug Administration)

The program is now fairly substantial: as of July 1, 2026, FDA reported 133 devices enrolled in the TAP Pilot. On that date FDA also expanded TAP across all of CDRH’s Offices of Health Technologies for eligible Breakthrough-designated and Safer Technologies Program (STeP) devices. (U.S. Food and Drug Administration)

TAP matters directly to RAPID because eligible Class II RAPID devices generally must be enrolled in TAP. In effect, RAPID plugs CMS into an FDA infrastructure that was already designed for intensive, early-stage coordination—now adding Medicare evidence and coverage requirements to that conversation. (U.S. Food and Drug Administration)


 

AI Analyzes Lab Pricing Recommendations from Medicare's Expert Panel

A prior blog conveyed the availabililty of the CMS lab pricing panel decisions - here.  This blog dives into the analysis.  (Put on your nerd hat and thick glasses!)



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Part 1. What This Project Does

Each summer, CMS convenes its Medicare Advisory Panel on Clinical Diagnostic Laboratory Tests, a federal advisory committee—often simply called the CDLT Panel—to review the roughly 100 new or reconsidered laboratory codes headed for the Medicare Clinical Laboratory Fee Schedule. 

For each code, the Panel recommends whether Medicare should set payment by crosswalking the test to an existing priced code or by gapfilling, which sends the test into a separate process for developing a new price. The Panel’s recommendations are advisory, but they provide an unusually transparent window into how experts think about laboratory pricing.

For 2026, CMS has just published the actual vote counts for 110 laboratory codes. That creates a surprisingly rich little dataset. Rather than simply asking which tests were crosswalked or gapfilled, this analysis treats the meeting like a major sports statistics exercise: How often was the Panel unanimous? How often did members abstain? Which technologies generated disagreement? Which kinds of tests were most likely to be gapfilled? And where did superficially similar tests receive quite different votes?

Very Brief Blog; CMS Releases Lab Expert Panel Pricing of New Tests

 On July 14, 2026, CMS hosted its expert advisory panel, which votes on crosswalk or gapfill for about 100 new lab codes.

CMS has now released the voting data.  Next step, CMS will release its proposed prices for public comment  in 1H September.

Website here:

https://www.cms.gov/medicare/payment/fee-schedules/clinical-laboratory-fee-schedule-clfs/clfs-advisory-panel

Click on "Panel Recommendations" and on"2026."

Direct to the 32p PDF should be:

https://www.cms.gov/files/document/clfs-advisory-recommendations-2026.pdf



AI Guest Author: On David Clark's Essays on the NHS Digital Pathology Investment

 [Chat GPT August 2026]

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British pathologist David Clark is an expert on digital pathology & real-world integrations.  Below, Chat GPT writes a detailed commentary on his four recent articles on NHS and its digital pathology investment tactics.

David Clark - Nottingham  - hematopathologist - Nottingham NHS Trust

https://www.linkedin.com/in/david-clark-61a79a23b/

He's written a series on faulty plans for NHS investments in digital pathology.

Entry point at Linked-In here:

https://www.linkedin.com/feed/update/urn:li:activity:7491025358016888833/

It matches to a four-part series he wrote at Pathology News;

https://www.pathologynews.com/the-masterbuilders-path-to-recovery/


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Reviewing David Clark's Essays on the NHS Digital Pathology Investment

The NHS digital pathology experience is not a story of failed scanners. It is a story of incomplete system design. David Clark’s four-part critique shows how capital-first procurement, weak interoperability, hybrid workflows, training gaps, and unfunded recurring costs can convert promising technology into a megaproject problem. The remedy is architectural.

This essay was written by Chat GPT and should be read as an example of the current state of AI reading, organizing, and writing - not as ground truth.

Essay as 16pp white paper PDF - here.

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  1. The NHS Did Not Buy the Wrong Technology. It May Have Bought Technology in the Wrong Order.

  2. Clark’s Part 1: The Strategy Gap

  3. Part 2: The LIMS Trap — Where the Abstract Strategy Failure Became Concrete

  4. The Hybrid Trap: When Digital Pathology Adds Work Instead of Removing It

  5. Part 3: Technology Adoption Is a Workforce Phenomenon

  6. The Sustainability Cliff: Capital Is Not a Business Model

  7. Part 4; Clark's Criteria for Successes

  8. “Design the Join”

  9. A Better Investment Model: Seven Requirements for the Next Wave

  10. An Important Irony: The NHS Is Still Investing

  11. The Larger Lesson for AI in Pathology

Conclusion: From Buying Digital Pathology to Building Digital Pathology

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EXECUTIVE SUMMARY

David Clark’s four Pathology News essays make an argument about the NHS digital pathology programme: its difficulties arose less from immature scanners or weak clinical rationale than from treating digital pathology as equipment procurement rather than redesign of a complex clinical operating system. Capital arrived before an end-state, interoperability architecture, workforce model, governance structure, or sustainable revenue model had been fully defined. The consequences included LIMS integration failures, middleware surprises, duplicated glass-and-digital workflows, inconsistent adoption, cross-Trust image-sharing barriers, and recurring storage and support costs that outlived grants.

The critique is strengthened by Bent Flyvbjerg’s work on major projects. His “Iron Law” describes projects that run over budget and time while underdelivering benefits; newer research finds IT projects unusually exposed to extreme tail risk. Digital pathology combines IT hazards—intangibility, goal ambiguity, stakeholder resistance, bespoke integration—with safety-critical clinical workflow.

The lesson is not to retreat from digital pathology. NHS experience includes successes, including highly digitised networks and routine AI use. The policy implication is to fund the next phase differently: define outcomes first, design network-level interfaces, make integration readiness a funding gateway, build recurring costs into business cases, standardise reusable components, align training and assessment, and learn from prior deployments.

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Digital Pathology Is Not a Scanner Project

What the NHS Experience Teaches About Large-Scale Digital Transformation

Thursday, August 6, 2026

Clinical Behavior in Genomics: New Paper on Reflex Tests for Genomic Biomarkers

An important new paper is just released, and open access.  See Pineualt et al., on protocols and barriers regarding reflex testing for gene panels in non small cell lung cancer (NSCLC).   

Find it here:

https://pubmed.ncbi.nlm.nih.gov/42467547/


i've linked via PubMed which gives you, at bottom, a useful list of related papers.

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AI CORNER

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What Happens After the Guideline? Achieving Access in Real-World Practice

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Summary

Pineault and colleagues examine how US health care institutions actually implement comprehensive biomarker testing for non–small cell lung cancer—not simply whether professional guidelines recommend it. Using a national cross-sectional survey of 111 health care professionals involved in NSCLC testing, the study evaluates locally standardized protocols, reflex ordering of broad multigene panels, the role of pathologists, and the regulatory and operational barriers encountered in everyday practice.

The findings are encouraging but reveal a striking implementation gap. Nearly 78% of respondents reported that their institutions had standardized comprehensive biomarker-testing protocols, and 88% of those protocols included reflexing to a multigene panel. At institutions with such protocols, most respondents said that at least 80% of newly diagnosed patients received comprehensive testing. Yet the proportion reporting that results were available before the first oncology visit—when first-line treatment is selected—fell to 47.7%. Thus, adopting a protocol does not automatically ensure that its intended clinical benefit reaches the patient at the critical decision point.

Pathologists were commonly the ordering providers, reflecting their practical position at the center of specimen selection, tumor assessment, tissue stewardship, and testing logistics. More than 90% of respondents believed that multidisciplinary, pathologist-ordered reflex testing improves care, and 93.7% supported CMS recognition of pathologists as ordering physicians, generally within guideline-based or multidisciplinary safeguards.

The study’s greatest contribution may be its treatment of regulation as something institutions must operationalize rather than merely obey. Reimbursement restrictions, prior authorization, payer denials, the Medicare 14-day rule, differing Medicare Administrative Contractor requirements, staffing shortages, and LIS limitations all shaped how—or whether—reflex testing worked. Institutions consequently developed locally adapted arrangements involving pathologist orders, oncology standing orders, multidisciplinary approval, and other hybrid workflows.

This is an important and highly promising approach to health-policy research. By studying real-world institutions, it shows how regulatory policies are translated, negotiated, accommodated, and sometimes worked around inside functioning care systems. The survey is modest, self-reported, and weighted toward pathology professionals, so it cannot establish causality or national prevalence. Nevertheless, it provides precisely the kind of grounded institutional evidence needed to understand why apparently sound policies succeed in some settings but falter in others—and how regulation might be redesigned to support effective care rather than inadvertently obstruct it.

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About LUNGevity

The study was funded by LUNGevity Foundation, a leading US lung-cancer nonprofit supporting research, patient education, advocacy, and community services. Its precision-medicine initiatives promote timely, comprehensive biomarker testing and work to remove reimbursement, prior-authorization, and regulatory barriers that prevent patients from receiving the right treatment at the right time.  



Very Brief Blog: CMS "Rapid Benefit Categories" for HCPCS Codes

Several years ago, CMS announced a process where it would codify something it was already doing - making benefit category decisions for new HCPCS code applications.   That is, CMS already for years would deny a new HCPCS applicant on the grounds it was "not a benefit category" - "Thanks, CMS."  And if it gave you a code, it usually meant, they believed it did fit some benefit category.

Such decisions are now organized in one place, and regularly updated.  

Hint: you might find the denials more interesting that the acceptances.  Only problem is, most of the denials for "no benefit category" never get a code, either, so they never survive long enogh to make it onto this list.  

For an exception, see "artificial saliva" A9154, p 8, which has no benefit category (although it did get a code!, which probably took a lot of pushing and repeat visits with CMS.)  

Breast milk bags are "contractor discretion" with a manual pump but no benefit category with an electric pump.   (Head-spinning.)

See transmittal here:

https://www.cms.gov/files/document/r13889bp.pdf



Tuesday, August 4, 2026

CMS Proposes to Pull WSI Tests Off the CLFS—Entering Topsy-Turvy Land?

In both the summer proposed hospital outpatient policies and the proposed physician payment policies, CMS proposed taking software-intensive whole-slide imaging (WSI) tests off the Clinical Laboratory Fee Schedule (CLFS).

Forget the current payment amounts for a moment. CMS proposes that, under Part B, WSI tests would be contractor-priced—eek! In the hospital outpatient setting, where contractor pricing is generally verboten, CMS would temporarily assign the WSI codes to APCs with payment rates roughly similar to what they previously received under the CLFS.



Analysis

For me, the central question is whether these tests are, or are not, CLIA laboratory tests.

If they are clinical laboratory tests of the laboratory type (not the physician pathologist type) then they are paid under the CLFS and governed by CLFS pricing rules, including the PAMA framework. See Social Security Act §1834A. Plain English, no wiggle room.

I do not think CMS can simply say: “Yes, these are clinical laboratory tests, but despite §1834A, we no longer like pricing them on the CLFS.”

But if CMS removes the codes from the CLFS on the theory that they are not CLIA laboratory tests, we enter topsy-turvy land.

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Medicare Doesn't Define Laboratory Test!

Medicare doesn't have its own definition of (clinical) laboratory test.  PAMA (SSA 1834A) added the term CDLT Clinical Diagnostic Laboratory Test, but no definition.   One assumes therefore the relevant definition is that of CLIA, which is a bulky paragraph that makes any human tissue, fluid, etc, and any analysis method, a CLIA test.  

Code Application (AMA) versus Test Category (Medicare)

One of the craziest examples is that Category III codes for digital pathology will be reviewed by CAP, and Pathology Coding Caucuse, require proof a lab offers the test, require a CLIA license, in a new proposal, even require a letter from the CLIA Lab Medical Director.

Yet, CMS has proposed that digital pathology tests are NOT laboratory tests, NOT CLIA tests, at all.  And if CMS doesn't classify the codes as CLIA tests, then laboratories can't bill them (there are national CMS claims processing edits that labs can only bill lab codes, not, say, MRI of the head).   

Date-of-Service Rules

If they are not clinical laboratory tests, then WSI tests presumably would not be subject to the laboratory date-of-service rules. See next point.

OPPS and Even Inpatient Bundling

If they are no longer subject to the strange, sometimes backward-looking laboratory date-of-service rules....then they may no longer be bundled into inpatient and outpatient hospital payments in the same way CMS takes for granted today.

Codes like 0220U, a digital pathology code, have NOT been payable in the hospital outpatient setting, because they carried status indicator (SI) Q4.  Now, they are proposed to be switched to status indicator O1, and paid $750 in the same setting.

ADLT Status

If they are clinical laboratory tests, they may be eligible for Advanced Diagnostic Laboratory Test status and ADLT pricing.

If they are not laboratory tests, they presumably are not eligible.

PAMA

If they are not clinical laboratory tests, they would not be subject to PAMA pricing and reporting rules.

Enrollment

Today, an entity performing CLIA tests obtains a CLIA certificate and enrolls in Medicare as a clinical laboratory.

But if H&E-based WSI-AI tests are not CLIA tests, can the entity performing them enroll as a clinical laboratory—or not?

As I noted in an earlier blog, CMS initially would not let HeartFlow enroll in Medicare at all. HeartFlow, now a major public company, was eventually permitted to enroll as an independent diagnostic testing facility, or IDTF.

Billing by a CLIA Laboratory

CMS is proposing that certain WSI tests should no longer be CLFS tests. That seems difficult to reconcile unless CMS also regards them as no longer being CLIA laboratory tests.

But my understanding is that a laboratory enrolled in Medicare as a clinical laboratory can bill laboratory services—not E&M visits, or foot surgery, or an MRI of the head.  These are provider-to-code hard wired edits, where the provider must be of the CLIA type or hold a CLIA certificate  to bill the CLIA codes.

If CMS no longer regards certain PLA-coded WSI services as CLIA laboratory services, CMS may be able to remove them from the CLFS. But would CMS also have to remove them from the listing of services that an enrolled CLIA laboratory is permitted to bill?   The lab would still be a CLIA lab but the WSI code it invented and got coded, would get yanked off its billable codes list.  

70/30 Rule - and Other Reference lab rules.

Labs can bill for reference lab tests that they refer out to a specialty lab, if such referrals are not more than 30% of the lab's volume.  (This is to avoid the lab becoming a "paper shell" that doesn't run a lab but only refers tests out.)  However, if digital pathology codes are not CLIA tests, then presumably they wouldn't count toward the 70/30 rule.  ...But, if they were not CLIA tests, then a CLIA lab probably is blocked from billing them.  And if the digital pathology are kept on the CLIA list at CMS so the lab where they are run can bill them, then those tests should be priced by CLFS per statute at 1834A, but CMS wants them off the CLFS and contractor priced...   topsy turvy land, again.

Another aspect, aside from 70/30 rule, when labs acquire a specimen and refer it to a special reference lab (like Mayo or ARUP), there are special claims rules, modifiers, putting the CLIA or NPI of the CLIA performing lab, etc.   None of these would apply if digital pathology is "not a lab test" in the first place.

Billing by an IDTF?

IDTFs generally are prohibited from billing CLIA laboratory services.  That's old news.

But CMS now appears to characterize these WSI services not as clinical laboratory tests, but as general diagnostic tests covered under Social Security Act §1861(s)(3).

If they are general diagnostic tests under §1861(s)(3), and CMS formally treats them that way, then perhaps they could be billed by an IDTF—even though the service involves a glass slide, tissue, and a microscope.

Level of Supervision

CMS maintains a table where it assigns "level of supervision" to all tests which are not CLIA tests.  Pathology tests are exempt from this table, because by definition they are under general supervision.  But CMS is saying that digital pathology tests are no longer CLIA tests (neither of the clin lab type nor the pathologist type), but rather, are general tests under 1861(s)(3), so they will have to be assigned levels of supervision.

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Head-spinning stuff.

There may be additional consequences that have not yet occurred to me.

 

CLIA, and Computational Pathology on H&E: The Dog that Didn't Bark?

There's a Sherlock Holmes story where a dog barked at every stranger.  Since the murder was committed on a night the dog didn't bark, Holmes concluded the murderer was someone known to the household.

Here, I'm putting together some puzzle pieces from recent CMS (and FDA) decisions.

Background Facts

In July proposed rulemaking, CMS proposed to take  existing whole slide imaging codes, priced on the CMS clinical lab fee schedule and falling under its Clin Lab policies like Date of Service rule, ADLT rule, etc.   And take those codes OFF the clinical lab fee schedule, and price them differently (temporarily on APCs in the OPPS setting, and by "contractor price" elsewhere.)

For me, the natural position was that those WSI tests - including advanced computational results from H&E - were CLIA tests, and simply had to go on the Clin Lab Fee Schedule - nothing to talk about.

For example, see a position paper from Digital Pathology Association on validation of AI "in the clinical lab" - a CLIA lab.  Here, here.  (Link 2, the paper, is open access, but you might need to enter from Link 1).

But CMS has pulled a range of WSI based codes (whether H&E or IHC) from the CLFS in its proposed rules, while skipping quite a few similar codes in the PLA system.  (See Valar comment to CMS, link in this blog.)

Back to the Non Barking Dog

So anyway, here's my point about that non-barking dog.

When FDA approves lab tess (including big sole-lab tests like FMI Foundation One), it classifies them for CLIA.

FDA explains how it classifies IVDs in CLIA levels

 https://www.fda.gov/medical-devices/ivd-regulatory-assistance/clia-categorizations

CLIA explains how this is FDA's job   

https://www.cms.gov/medicare/quality/clinical-laboratory-improvement-amendments/cartegorization

FDA clia database is here

https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfCLIA/search.cfm

If you search that database for Foundation Medicine, you'll find a number of tests. But look for Artera's tests - including their prostate test from 2025 based on H&E algorithm - and you won't find it.

So long before CMS proposed to knock H&E WSI algorithmic tests off the CLFS - which would require they "not" be CLIA tests - FDA was NOT putting them into the national  FDA-CLIA database of FDA tests that were classed by FDA as "CLIA" tests.

It's just an isolated finding but I found it intriguing.

Hiding in plain sight - like the dog that didn't bark.  There's apparently been some hesitation since 2025 whether H&E WSI tests - although for FDA "medical devices," might not also be "CLIA tests" in the CLIA database.

in contrast, for example, at the FDA-CLIA portal search "Dako," you'll get 81 hits.  Search "Abbott" and you'll max-out the system at 500 hits.



Monday, August 3, 2026

CMS Denial Rates for PLA Codes

 CMS has a terrific database where you can see all codes (services) paid for any US laboratory.  Find it here.

CMS also has a database for all CPT codes paid to Part B providers and labs, along with denial rates.  These tables are national, and are not provider specific.  But, if the code is a sole-lab PLA code, it's almost the same as provider specific.  Database here.

I ran a search for PLA codes 037U (FMI CGP Paraffin) and 0239U (FMI CGP LBx).

The table breaks the codes up into multiple lines for obscure reasons (e.g. some will go through the "Palmetto Railroad Retiree Contractor.")   See below for the fragmented lines.

But the data count in the main rows here (with around 13000 cases for 0037U and around 7000 cases for 0239U0) match up with other sourcecs for 2024.

The FMI PLA code denial rate appears to be... about 4% in those main rows.  QED.

Click to enlarge.

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A person could search the data for all codes ending in "U" and get several hundrred rows in Excel.  You could then sort for most popular PLA codes, most denied PLA code, most denied dollars per PLA code, etc.   
 Which I did here as an initial experiment.

Sunday, August 2, 2026

AI Guest Author: New 20-page AI White Paper on Medicare vs Commercial Coverage for Genomics

 It's become almost a cliche' in the past decade that for many tests, Medicare coverage will occur ahead of most commercial insurance coverage.    Or, in clinical areas like minimal residual disease (MRD) or comprehensive genomic profiling (CGP; CMS NCD 90.2), Medicare coverage will be broader.

This 15-page white paper was written entirely by Chat GPT, which was given only a few sentences of initial guidance (prompt shown on page 14).  Therefore, it should be taken as an example of the current state of AI planning, research, organization, and writing - rather than a a truth standard or as a reference article.

Find the white paper here.

Capsule Summary

Medicare has repeatedly moved first in advanced oncology genomics: nationally for FDA-linked comprehensive sequencing and locally through MolDX for tumor-informed MRD. Commercial coverage remains fragmented, with several national policies still negative and only positive outliers. Evidence, guidelines, FDA labels, and contracting—not analytic performance alone—will determine the next wave. 

Executive Summary

This white paper finds an ongoing gap between Medicare and commercial insurance in advanced oncology genomics. Almost ten years ago, 2018, CMS NCD 90.2 created national coverage for qualifying FDA-approved or cleared next-generation sequencing companion diagnostics in advanced cancer and preserved contractor discretion for additional tests. That framework was far more permissive than commercial policies of the day.  The pattern recurred in molecular residual disease: MolDX established a test-and-indication pathway enabling broad Signatera coverage --while several major commercial policies continued to classify solid-tumor MRD as unproven, investigational, or not medically necessary.  

The 2026 sample is fragmented rather than uniformly negative. UnitedHealthcare, Aetna, Cigna, Carelon-administered plans, the Federal Employee Program, and Excellus remain adverse; Blue Shield of California is unusually expansive; Centene covers selected Signatera uses; and Arkansas Blue Cross covers a narrow Merkel-cell indication. This dispersion reflects different evidentiary thresholds, especially the gap between "prognostic validity" and actual proof that test-directed management improves outcomes.  

Commercial convergence is likely to proceed no faster than indication by indication. FDA’s 2026 Signatera companion-diagnostic approval in muscle-invasive bladder cancer and guideline changes may accelerate that use first. Laboratories should fund prospective utility trials, pursue regulatory and guideline milestones, constrain testing cadence, and build payer-specific economic evidence. Early movers have a moat, part of which is data, but part of which is the high level of payer resistance. 

Linked In Deep Dive: Daniel G's Writings on Where MRD Is Going

 

Daniel G. and the Rise of the LinkedIn Topic Expert in MRD

https://www.linkedin.com/in/daniel-giner/


This blog written by Chat GPT 5.6.
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LinkedIn has developed its own class of expert: the experienced industry participant who chooses a relatively narrow field, follows it almost continuously, and publishes enough commentary that readers begin to rely on that person as an informal editor of the topic. These writers are not necessarily producing original clinical research or lengthy investment reports. Their value lies in selecting developments, putting them into a recognizable framework, and returning often enough that a following accumulates.

Daniel G. is a good example in molecular diagnostics and, increasingly, measurable or molecular residual disease—MRD. His profile reports more than 5,400 followers and describes his current work as business development and commercial partnerships in diagnostics, precision medicine, and international expansion.

Saturday, August 1, 2026

Big News: The FIND RCT Study in Colorectal Cancer: Integrating ctDNA and Imaging Management (Mo et al.)

SUMMARY:

The randomized phase III FIND trial integrated serial ctDNA methylation testing with protocol-driven CT imaging after colorectal cancer surgery. ctDNA-guided surveillance detected recurrence a median 3.9 months earlier and doubled curative-intent treatment among patients who relapsed (48.1% versus 23.6%). 

  • The study moves MRD beyond prognosis toward actionable surveillance, although mature overall-survival, economic, and independent replication data remain essential for adoption.

CITATION:

Mo S, Zhou C, Ma M, et al. Dynamic circulating tumor DNA methylation monitoring guiding postoperative surveillance in nonmetastatic colorectal cancer: a prospective, randomized, phase III FIND trial. J Clin Oncol. Published online July 29, 2026. PMID 42525894.  doi:10.1200/JCO-25-03009.

https://pubmed.ncbi.nlm.nih.gov/42525894/

The article below is written by Chat GPT 5.6. 

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The Blood Test That Tells the CT Scanner When to Wake Up

The randomized FIND trial moves ctDNA beyond prognosis and into a working surveillance algorithm—doubling the proportion of recurrent colorectal cancers treated with curative intent

Patrick Adams recently highlighted a deceptively simple question about postoperative colorectal cancer surveillance: can ctDNA tell us more precisely whom to image and when, so that recurrent disease is found while it is still manageable? His LinkedIn note is not independent evidence, but it captures the operational insight of an unusually interesting new trial rather well.

The phase III FIND trial, published July 29 in the Journal of Clinical Oncology, did not merely add another biomarker measurement to an observational registry. The investigators built a complete, protocol-driven system in which serial ctDNA results changed the timing of CT imaging, subsequent negative results could turn intensified surveillance back down, and the clinical endpoint was not simply “earlier detection.” It was whether patients whose cancer recurred could receive metastasis-directed treatment with curative intent.

That is a much more consequential test of molecular residual disease.

Linked In Deep Dive: Josh Bowerman's Articles on Genomics Industry Dynamics

Josh Bowerman Maps the Rapidly Changing World of Clinical Genomics

[This blog written by Chat GPT 5.6]

Josh Bowerman has developed a distinctive body of commentary on clinical genomics, particularly oncology diagnostics, liquid biopsy, early cancer detection, comprehensive genomic profiling, and minimal residual disease. His articles are brief, visually polished, and generally published on LinkedIn, but taken together they amount to something more substantial: an evolving map of how the precision-diagnostics industry is reorganizing itself.

Bowerman is not primarily reviewing individual scientific papers or comparing the analytical sensitivity of competing assays. His recurring questions are commercial and strategic:

Who is building what? Which parts of the cancer journey are companies trying to control? Are they developing capabilities internally or acquiring them? And, once the technology works, who can obtain reimbursement and achieve clinical adoption?

Bowerman writes from JBAndrews, an executive-search firm active in diagnostics and precision medicine. His LinkedIn profile, available here, reports approximately 29,000 followers. His position gives him an unusual source of market intelligence: conversations with companies about what expertise they are hiring, what capabilities they lack, and where they expect growth. In one discussion, he says explicitly that the firm’s view of deal activity often emerges from recruitment conversations.

These are therefore not neutral technology assessments or systematic evidence reviews. They are better understood as market cartography: concise narratives and graphics showing how a fragmented field may be consolidating.

LinkedIn Deep Dive: Jack Kohler's Work on Interpreting Clinical Trials for Commercial

 

Reading the Clinical Paper Commercially:
Jack Kohler’s Methods to Bridge from Evidence to Strategy

The essay below is written by Chat GPT 5.6 after reading Kohler's web articles.  He's focused on biopharma, where one main pivotal trial usually is hugely influential in FDA decisions as well as coverage.  In diagnostics, VERY often, at least tests in novel areas, a whole sequence of papers are required for coverage.   E.g. see the lengthy clinical trial page for Naveris NavDx for MRD in H&N cancer.  Here, here.

# # # # #

Clinical papers are written to report research. Pharmaceutical companies must ask them to do something more: clarify which patients matter most, whether a product is meaningfully differentiated, what claims the evidence can support, and whether the result can become a credible positioning and value story.

Jack Kohler has built a consulting practice around that translation. His background spans pharmaceutical sales, brand management, and international marketing, and he describes his work as helping pharma and biotech teams turn clinical evidence into “decision-ready strategy.” (LinkedIn)

His recent infographic, “How to Read a Clinical Paper Commercially,” organizes the task into nine steps:

Friday, July 31, 2026

Major News: FDA Posts Its 28pp Review of ArteraAI - Breast Cancer Computational Pathology

In May 2026, ArteraAI got FDA clearance for its computational pathology test for breast cancer.  FDA can take "weeks to months" to post its 20- to 30-page review packet - and the breast cancer review is now public.

Artera AI Breast Cancer (NEW)

See the K254114 product home page here;

https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfPMN/pmn.cfm?ID=K254115

See the FDA's 28-page 510(k) review here:

https://www.accessdata.fda.gov/cdrh_docs/reviews/K254115.pdf

FDA notes that the application includes a Predetermined Change Control Plan PCCP for updates.

See the four-page FDA letter here:

https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfPMN/pmn.cfm?ID=K254115

See the 864.3755 regulatory classification here, product classification SHW:

https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpcd/classification.cfm?id=5520

Pathology software algorithm device analyzing digital images for breast cancer prognosis