Recall that the starting point for FDA-regulated manufactuerers is what's literally on the FDA label, where HEOR usually isn't.
- Old 2018 final guidance + 2023 new law §3630 creating 502(gg) = this 2026 new draft guidance.
Ideas for or from an evolving healthcare system
Recall that the starting point for FDA-regulated manufactuerers is what's literally on the FDA label, where HEOR usually isn't.
Do payers pay for AI? Or do they assume AI-mediated savings, and deflation of prices? Is one clinical area totally different from another in terms of AI financing and strategies?
STAT just ran a three-part series on AI and reimbursement, with Medicare and other use cases. Peterson Institute just released a 15pp on AI financing in healthcare. And there are collateral sources, e.g. a PathAI webpage on the cost strucures of digital pathology.
Here's a consolidated view from Chat GPT...
This essay is also available as a PDF white paper in the cloud - here.
Summary.
##
Header: An AI-generated 20-page white paper that surveys a decade of articles about payors and genomics.
Here's another adventure in current AI thinking and writing. Chat GPT 5.6 surveyed 15 papers on payors and genomics, and for contrast, it also read 5 papers on payors and other medical industries.
The report provides a general overview and key conclusions. Trends over the decade are discussed. There's a contrast-and-compare with other medical industries - from continuous glucose meters to radiation therapy. A side bar reviews two UCSF papers (both Phillips et al...2018, 2026) on payors and genomics.
You're probably seen press releases about the recent LabCorp $14M DOJ fine related to urine tox testing.
There are some sources that go into numbing detail about the coding situations and the coding definitions and overlap. First link is DOJ press release; second link is 11p court document.
https://www.justice.gov/opa/pr/labcorp-agrees-pay-145m-resolve-false-claims-act-allegations
https://www.justice.gov/opa/media/1452616/dl
| click to enlarge |
For some questions, AI can search Google or search PubMed more efficiently than I can.
Today I asked Chat GPT to search PubMed and bring back ten papers on barriers to adoption of molecular tests in oncology. I named some categories like slow adoption of LBx for driver genes [CDx], slow adoption of Oncotype Dx or similar tests.
Pro's and Con's
The AI does the task quickly, with clean output. (I've learned that if I ask, Chat GPT can also gather the open access PDFs and give to me as a zip file. But it was very hit and miss and you have to learn to use a full 'agentic' mode (not LLM mode) on your desktop to do that consistently.) Besides 10 (or 14) papers, AI can then provide a narrative summary about the group of papers.
Downsides - But we don't know what we're missing. A true academic review might pull 200 abstracts or more and have two human readers each rate to find the most important ones. Many hours. 3 minutes per paper, 20 man-hours.
##
Here is the direct output.
###
Bruce, I selected these to maximize topic diversity: liquid biopsy, broad tumor profiling, breast prognostic testing, Lynch screening, ovarian HRD/BRCA, prostate germline testing, rural precision oncology, MCED, and a newer companion diagnostic. Only one is specifically about MCED.
INSERT:
Here is an overview essay (written by AI only after it found the 10 barriers papers and 4 extra papers about MRD barriers.)
I have seen a scattering of articles that study whether AI interpretations of H&E slides can mirror the prognostic value of molecular tests.
The linked PDF white paper is entirely machine generated.
Here were the steps:
UPDATE. I did have one day of success asking Chat GPT in "LLM" mode to download PDF papers and give me a Zip file. But it took a long time (?hour). I couldn't make it repeat this successfully on other projects.
BUT...
I understand you can do this reliably if you learn how to use full-strength agentic mode where it "takes over" your desktop browser etc. I don't know that.
##
Here's an example of AI being able to do more for you than you might guess.
1. Search Pubmed
I asked Chat GPT to find recent papers asserting that computational pathology can predict breast cancer relapse as well as Oncotype Dx. I mention I have seen several of such papers, including one in the past week.
Chat CPT came back with a number of publications, including flagging for me the most recent of the group. It wrote,
2. Downloading PubMed Papers For You
I thought, this list is good, I will now click around on all the links and find the PDF download buttons and download each open access one.
Then I thought, wait a minute.
I asked it:
AMA has a webpage for the September 17-19 Editorial Panel meeting in Minneapolis. There are limited in person seats; first come first served; but unlimited virtual participation. It's at the Hyatt Regency.
https://www.ama-assn.org/membership/events/cpt-editorial-panel-meeting
The public agenda for all codes is now available. Comment for lab codes is already closed (to allow for early subcommittee meetings).
Click on this link. Within this PDF you will find instructions to access the AMA CPT Smart App, a web portal that has the dual functions of (1) letting you write and submit new code applications, AND, (2) as a meeting approaches, request to review a packet and submit a comment.
https://www.ama-assn.org/system/files/cpt-panel-september-2026-agenda.pdf
To help you have a targeted plan to keep updated (codes are withdrawn, etc) AMA says it will update the agenda on July 10, August 14, September 4, September 11. AUGUST 10 is the last date to submit comments for the "Interested Party" function. This ensures that all public comments can be reviewed by the voting panelists.
There are 94 agenda items (some numbers may be skipped). For codes that go into a valuation process (most Category I codes go to AMA RUC), this is the last round for AMA to collect data this winter and get into CMS's public comment process summer 2027 for codebook 2028.
Big Changes for AI for Pathology Codes Only (???)
As we saw earlier in the early release of path-lab codes, tab 94 is extensive revisions to the path-lab application, with many questions on software and its validation.
See my July 2 discussion of the Path Lab AI CPT changes.
https://www.discoveriesinhealthpolicy.com/2026/07/run-dont-walk-ama-cpt-big-changes-for.html
MolDx has finalized LCD L40140, Molecular Testing for Organ Allograft Rejection, replacing the draft issued in summer 2025. The policy governs Medicare coverage for tests such as donor-derived cell-free DNA and gene-expression profiling, used either when rejection is suspected or to monitor an apparently stable transplant recipient for subclinical injury.
Header: In the last couple months, five separate and active policy events circle around digital pathology.
DP Policy Event 1: CAT III WSI Codes Not on CLFS (June 10)
DP Policy Event 2: Congr. Dunn Released "Enhance CLIA Bill" (H.R. 8890, w/ Dig Path) (June 12)
DP Policy Event 3: OPPS Rule Pushes DP Off CLFS, Onto APC System (July 2)
DP Policy Event 4: PFS Rule Knocks DP & AI Into "Contractor Pricing" (July 14)
DP Policy Event 5: CMS Releases "CLIA Reform" RFI; Singles Out DP & AI (July 16)
I won't cover them here, but one could also track the important releases of 'Revised Appendix S' (AMA CPT AI & software policy, here, humor here) and "Revisions to AMA CPT AI Lab code Applications." The latter here.
##
##
EVENT 1: Cat III Not on CLFS
Over the past two months, CMS omitted new Category III codes for Digital Pathology [Computational Pathology] from CLFS meetings June 10. (Blog).
EVENT 2: Release of HR 8890, Enhanced CLIA
Includes substantial sections on digital pathology and guardrailing-it safe from FDA. June 12. Here, here.
EVENT 3: OPPS Rule; Push Dig Path onto APC Policy System
Then, July 2, CMS published the OPPS rule, taking the position that computational pathology per-se was not a clinical lab service at all (not under CLIA) and any such codes should be pulled from the CLFS. (Blog).
In the OPPS rule, CMS proposes to take such codes off CLFS and for the hospital outpatient setting, putting them under regular APC (ambulatory payment category rules). If CMS take that category of test off the CLFS (off the list of CDLTs) they won't be eligible for ADLT, either. (That's IF, not when. And regular genomics, e.g. CGP, MRD, isn't involved).
EVENT 4: PFS Rule: Make Dig Path Tests "Contractor Priced"
In the recent PFS rule, July 14, CMS proposed to take the same 10 tests (a list with probable errors, even on its own terms) off the CLFS and kick them into "Contractor Priced" codes. (Blog.)
EVENT 5: CLIA RFI on CLIA Reform, Esp. molecular & digital
In the CLIA RFI released on July 16, the same topic is discussed at length (for 2 columns). It's topic RFI.6 & RFI.7 on page 43588. (Blog). This blog (you are reading now), looks more closely and specifically on digital/AI topics, topics RFI.6, RFI.7.
This blog, Below, is my main discussion on RFI re Dig Pathol, RFI Points 6 & 7.
##
AI CORNER for the CMS CLIA RFI
Points .6 & .7 on Dig Pathol
##
CMS and CDC are asking unusually direct questions about how CLIA should apply to artificial intelligence, digital pathology, and laboratories that perform interpretation without handling a physical specimen. Importantly, these are requests for information, not yet proposed regulatory changes.
#
The agenda for the Digital Pathology & AI Europe conference has been posted over at Linked Iin by Lauren Dennison. Dates are 9-10 December in London. See the 15 page PDF agenda. Novotel London West (just west of Kensington).
AI CORNER
# #
The 13th Digital Pathology & AI Congress: Europe will take place in London on December 9–10, 2026, bringing together more than 500 attendees and over 60 speakers from pathology laboratories, health systems, pharmaceutical companies, universities, regulators, and technology vendors. The organizers’ central message is clear: digital pathology is moving beyond the question of whether laboratories should digitize. The more urgent questions now concern how to make digital operations reliable, interoperable, scalable, and ready for routine artificial intelligence.
Three tracks
Practical Realities
Header: CMS Publishes Request for Information: Let's Update CLIA, But How?
Find it here: July 16, 2026, 91 FR 43586. Six pages. Comment 60 days, September 14.
Christine Bump summarizes highlights at Linked In, here. See 360Dx here, their article on Dunn's bill here.
A key factor of high importance to digital pathology is CMS's assertions (in OPPS and PFS rulemaking recently) that pure-play digital pathology is not a CLIA service at all, and should not be on the CLFS. CMS directly addresses this on page 43588, section 6 & 7, on "post analytic interpretation and AI."
Writing, "Facilities that only process analytical data or provide specialized data interpretation, some of which may be manufacturers of medical device software, have emerged. CMS has received inquiries on whether these types of data-only facilities require a CLIA certificate. These inquiries have in part focused on facilities that review and interpret genetic data, digital images, and perform calculations of risk factors. CMS and the CDC seek public comments on data-only facilities..."
AI CORNER
# # #
CMS and CDC have opened a broad CLIA modernization inquiry, not yet a proposed rule. The July 16 RFI asks whether the 1992-era regulations should be updated for breath tests, molecular methods, AI and data-only interpretation, remote competency reviews, cybersecurity, emergency preparedness, specimen handling, and evolving laboratory specialties. Comments are due September 14, 2026; responses may inform later notice-and-comment rulemaking.
On July 16, 2026, CMS and CDC published a six-page Request for Information on possible modernization of the Clinical Laboratory Improvement Amendments regulations. The agencies emphasize that laboratory technology has advanced substantially since the principal CLIA regulations were issued in 1992.
The document is an RFI, not a proposed rule. It creates no immediate new requirements and does not commit the agencies to issuing regulations. Instead, CMS and CDC are gathering operational experience, technical evidence, and policy recommendations that may support future notice-and-comment rulemaking. Comments on file CMS-3485-NC are due September 14, 2026.
Header: Concert Joins Lyric; by Chat GPT
Big news arrived from Nashville on July 15: Concert, known for most of its history as Concert Genetics, has been acquired by Lyric, the large healthcare payment-accuracy and “decision intelligence” company. For those who have followed Concert and its outstanding executive team over the years, the transaction looks less like an abrupt change of direction than the logical culmination of a long effort to make the extraordinarily complex world of genetic and laboratory testing understandable—and computable.
Concert was founded in 2010 as NextGxDx, initially creating tools that helped clinicians find, compare, and order genetic tests. It became Concert Genetics in 2017 and, since 2024, has generally used the shorter name Concert. Over time, the company expanded well beyond a test directory. Its infrastructure now includes proprietary laboratory-market data, clinical and coding expertise, the Concert GTU test-identification system, and patented technology for converting medical policies into machine-readable rules that can be used in ordering, coverage, coding, claims editing, and payment. Concert reports that its registry has grown to more than 175,000 laboratory-testing products and that, by 2023, its health-plan customers represented about 30 million members. (Concert)
The acquisition brings those capabilities into a much larger operating environment. Lyric grew out of the ClaimsXten payment-accuracy business and says its technology is used by nine of the ten largest U.S. health plans, supporting approximately 200 million covered lives. Its Lyric42 platform applies policy, coding, clinical information, and artificial intelligence to claims workflows, with an emphasis on decisions that are fast, auditable, and explainable. (Business Wire)
This is not a first date. Concert and Lyric began working together in 2023, initially integrating Concert’s genetic-testing capabilities with Lyric’s claims-editing platform. In 2024, they expanded the relationship into a broader Diagnostics Module covering both advanced and routine outpatient laboratory services. According to the acquisition announcement, the scope and impact of their joint solution have grown nearly tenfold since the partnership began. (Business Wire)
Concert Chief Science Officer Gillian Hooker described the company’s journey as one of scale: “taking what is possible scientifically and making it possible for more people, clearly and transparently.” She added that this next step is also about scale. That seems exactly right. Concert has spent more than a decade addressing the difficult intellectual work: identifying tests, organizing evidence, translating clinical policy into structured logic, and connecting that logic to coding and payment. Lyric supplies the industrial-scale distribution system through which those capabilities can reach a far larger share of the health-insurance market.
The strategic importance extends beyond genetics. Health plans must now manage a rapidly changing mixture of molecular diagnostics, large sequencing panels, infectious-disease testing, companion diagnostics, specialty drugs, personalized therapies, and other services for which the clinical evidence and coding rules may change faster than conventional payer systems can be updated. A policy written as a PDF and interpreted manually at disconnected points in the claims process is increasingly inadequate. Concert’s approach is to make the policy simultaneously readable by humans and executable by machines—and to place it inside the systems where ordering and payment decisions actually occur.
Concert CEO Rob Metcalf has emphasized that clinical and administrative policies should be transparent, evidence-based, and computable. Joining Lyric provides a route for putting that philosophy into real-time payer workflows on a national scale. In that sense, this is not simply the acquisition of a respected Nashville consultancy and technology company. It is another sign that precision-medicine management is moving from a specialized corner of laboratory benefits into the mainstream infrastructure of health-plan claims and payment operations.
Congratulations are due to Rob Metcalf, Gillian Hooker, and the entire Concert team. Concert’s executives have been thoughtful, visible, and constructive participants in the laboratory and genomics community for many years. Their work helped bring order to a field in which scientific innovation has often moved much faster than coverage, coding, and payment systems. Under Lyric, they will have a substantially larger platform—and a great deal more scale—on which to continue that work.
—-
Key points dictated to ChatGPT.
We recently reported the news that Anthem would soon be covering FDA approved pTau217 blood tests, with conditions, as part of dementia diagnostic work-ups in the clinic.
And today, I saw headline news at CNN that there's a new study, pTau217 is a strong marker of future 5-year risk of developing MCI or dementia in currently-healthy elders.
The CNN article said that high pTau217 matched a 38% increased risk of dementia. I thought this sounded misleading; do I care if my ten year dementia risk is 10 chances ini 100 or 13.8 chances in 100? It turns out the CNN piece was misquoting, and pTau217 is actually a much stronger predictor (from 12% to 38% absolute risk or 3X relative risk).
Here's a dialog with Chat GPT to puzzle it out.
###
Can you find this paper? There is recent evidence that p-tau171 can be a marker for elevated dementia risk in “healthy elders,” somewhat as high blood pressure is a risk factor for stroke. I had seen a five-year figure of 38% and a ten-year figure of 78%. However, relative-risk numbers can be misleading: if my underlying chance were one in ten, a 38% increase would raise it only to about 1.38 in ten. The information may have come from a recent news report or perhaps an abstract at the upcoming international Alzheimer’s meeting.
Chat GPT answers:
The paper can indeed be found, although the biomarker is p-tau217, not p-tau171. It is:
Buckley RF, Townsend DL, Birkenbihl CJ, et al. “Prognostic Value of Blood-Based P-Tau217 Levels for Progression to Cognitive Impairment.” JAMA. Published online July 14, 2026. doi:10.1001/jama.2026.12556.
The paper was published in conjunction with its presentation on July 15 at the 2026 Alzheimer’s Association International Conference in London. It pooled 2,684 people who were cognitively unimpaired at baseline across six longitudinal research cohorts. Their median age was 69.6 years, and median follow-up was 5.4 years. During follow-up, 478 participants reached the study’s composite endpoint of cognitive impairment. (JAMA Network)
My initial impression came from a CNN report by Sandee LaMotte, which said that cognitively healthy people with high p-tau217 had an “estimated 38% greater chance” of developing early signs of dementia over five years. As written, that is not what the study found. (Facebook)
The study found that people in the very-high p-tau217 group had an estimated 38% absolute probability of progressing to cognitive impairment within five years. It did not find merely that their risk was 38% higher than that of some comparison group.
That distinction is substantial. The estimated five-year risk in the low p-tau217 group was 12%, while the estimate in the very-high group was 38%. Therefore:
The absolute increase was 38% minus 12%, or 26 percentage points.
The risk ratio was 38 divided by 12, or approximately 3.2 times the risk.
Expressed as a relative increase, the very-high group’s risk was about 217% higher than the low group’s risk.
By contrast, a “38% greater chance” applied to a baseline risk of 12% would produce a risk of only about 16.6%:
12% × 1.38 = 16.6%.
Thus, the CNN wording does not merely simplify the result. It transforms a 38% absolute risk into an apparent 38% relative increase, which is a very different and much smaller effect.
There may be an identifiable source for the mix-up. The paper separately reports that each one-standard-deviation increase in p-tau217 was associated with a hazard ratio of 1.38 for progression. That means a 38% increase in the instantaneous event rate per standard-deviation increase, within the time-to-event model. It is not the same thing as saying that people with very high p-tau217 had a 38% increase in their five-year probability. The paper’s HR of 1.38 and its five-year absolute risk of 38% happen to contain the same digits, but they answer different statistical questions. (JAMA Network)
The study divided participants into four p-tau217 categories. These were not quartiles. The investigators standardized p-tau217 measurements within each cohort and chose thresholds corresponding approximately to biologically meaningful amyloid-PET Centiloid levels: 10, 25, and 60 Centiloids. Consequently, the four groups were unequal in size. (JAMA Network)
| Baseline p-tau217 category | Approximate amyloid-PET correspondence | Participants, N (%) | 5-year absolute risk | 10-year absolute risk |
|---|---|---|---|---|
| Low: <−0.5 SD | <10 Centiloids | 516 (19.2%) | 12% (95% CI, 9%–15%) | 40% (31%–49%) |
| Intermediate: −0.5 to <1.1 SD | 10–24 Centiloids | 1,087 (40.5%) | 15% (12%–17%) | 45% (37%–52%) |
| High: 1.1 to <2.5 SD | 25–60 Centiloids | 598 (22.3%) | 24% (20%–28%) | 62% (52%–69%) |
| Very high: ≥2.5 SD | >60 Centiloids | 483 (18.0%) | 38% (33%–43%) | 78% (69%–84%) |
The group sizes are important. The 38% estimate did not arise from a handful of extreme outliers: the very-high category initially included 483 participants. At the same time, the fact that 18% of this particular study population fell into the very-high category should not be interpreted as showing that 18% of ordinary cognitively healthy older Americans have such levels. These were selected Alzheimer’s research cohorts, not a representative population sample. (JAMA Network)
The table also clarifies another ambiguity in the CNN account. The formal high group had a five-year risk of 24%, twice the 12% risk in the low group. The 38% estimate belonged specifically to the very-high group. Referring simply to participants with “high levels” collapses two distinct categories.
At two years, the modeled absolute risks remained low in all four groups, ranging from approximately 1% to 4%. The sharper separation appeared over five years, and still more dramatically in the ten-year projections. (JAMA Network)
The study’s outcome was broader than “developing dementia.” Participants were counted as having progressed if they developed any one of the following:
Mild cognitive impairment;
Dementia; or
Two consecutive global Clinical Dementia Rating scores of 0.5 or greater.
Therefore, “progression to cognitive impairment” is the accurate description. CNN’s phrase “early signs of dementia” is understandable as popular shorthand, but it blurs the distinction between MCI, a low CDR score, and established dementia. The reported 38% should not be presented as a five-year probability of receiving a dementia diagnosis. (JAMA Network)
The secondary cognitive analysis told a consistent story. Over five years, modeled cognitive performance was relatively stable in the low and intermediate groups, while the high and especially the very-high groups showed greater decline on the harmonized Preclinical Alzheimer Cognitive Composite. (JAMA Network)
The 78% ten-year estimate is striking, but it is much less firmly supported than the five-year result. Only 139 participants—about 5% of the entire sample—had at least ten years of clinical follow-up, and most of the long-term information came from one cohort. (JAMA Network)
The survival figure shows how sparse the tail became. Of the 483 participants who began in the very-high group, 425 were still under observation and event-free at two years, 285 at four years, 143 at six years, 27 at eight years, and only 11 at ten years. The corresponding numbers at ten years were also small in the other groups: 19 low, 65 intermediate, and 16 high.
The 78% figure is therefore a model-based extrapolation informed by a dwindling number of long-observed participants. Its reported confidence interval—69% to 84%—does not fully communicate every source of uncertainty, including reliance on selected cohorts and the scarcity of ten-year observations.
The models also did not explicitly treat death as a competing risk because mortality information was not consistently available. Someone who died or left the study without developing cognitive impairment was censored. In an older population, failing to model death as a competing event may make long-range disease probabilities appear somewhat higher than the probability a living person would actually experience before death. (JAMA Network)
The participants were cognitively unimpaired at enrollment, but “healthy elders” can give an overly broad impression. The pooled population was assembled from six observational studies and clinical-trial cohorts. One component was the 952-person A4 prevention trial, which required participants to be amyloid-positive. Overall, 43% of the pooled study population was amyloid-positive at baseline. (JAMA Network)
That enrichment was useful scientifically because it provided enough people with substantial Alzheimer-related pathology to study subsequent progression. It also means the observed distribution of low, intermediate, high, and very-high p-tau217 should not be treated as a prevalence survey of the general older population.
The accompanying JAMA editorial noted additional limitations: the cohorts were generally highly educated and had limited racial, ethnic, and socioeconomic diversity. Medical conditions that can affect measured p-tau217 concentrations, including chronic kidney disease, were not incorporated fully into the prognostic estimates. Cognitive impairment could also arise from vascular disease, other neurodegenerative conditions, or mixed pathology rather than Alzheimer disease alone. (JAMA Network)
The blood-pressure analogy is useful in one limited respect: both measurements may help stratify the future probability of a clinically important outcome in a person who currently has no symptoms.
But biologically they are not quite equivalent. High blood pressure is itself a causal and modifiable contributor to stroke risk. Elevated p-tau217 is better viewed primarily as an indicator that an Alzheimer-related pathological process—particularly amyloid-associated tau biology—may already be advancing. It is closer to a measure of underlying disease burden or disease stage than to a stand-alone risk factor imposed upon an otherwise pathology-free brain. The study found that p-tau217 retained prognostic information even after accounting for amyloid PET, suggesting that it captures an integrated aspect of advancing Alzheimer-related pathology. (JAMA Network)
For now, the most defensible application is research: identifying cognitively normal individuals at sufficiently high near-term risk to make Alzheimer prevention trials feasible. The authors and editorialists caution that the estimates are not yet precise or generalizable enough to tell an individual cognitively healthy person, based on a commercial blood result, that his or her personal five- or ten-year risk is a particular percentage. Current guidance continues to recommend against routine p-tau217 testing of cognitively unimpaired people outside research studies or clinical trials. (JAMA Network)
The bottom line is therefore considerably more dramatic—and more nuanced—than the CNN sentence. The study did not find a mere 38% relative increase. It estimated a 38% five-year absolute risk of broadly defined cognitive impairment in the very-high p-tau217 category, compared with 12% in the low category: a 26-percentage-point difference and roughly a threefold risk ratio. That is a substantial prognostic signal. But it was derived from selected, pathology-enriched research cohorts, the endpoint was broader than dementia, and the ten-year estimate rests on comparatively sparse follow-up.
Primary paper: Buckley et al., JAMA, July 14, 2026
Accompanying editorial: Schindler SE, Wolk DA. “Predicting Risk of Cognitive Impairment With Alzheimer Disease Blood Biomarkers.” JAMA. Published online July 14, 2026. doi:10.1001/jama.2026.13322.
Header: WaPo Slams AMA Hard, Lands Punches Early
Another clue that this was hand-delivered from HHS to WaPo - even by midnight, no other media captured on Google, other than WaPo, had even mentioned the story.
The WaPo highlighted this as a goal of RFK Jr within weeks of the November 2024 election - here. (Both today's article and he 2024 one were written by Dan Diamond). (More on the journalist and the context here.)
The WaPo writes,