Thursday, July 9, 2026

MolDx Finalizes LCD: Liver Disease Risk Stratification

MolDx MACs finalize an LCD, proposed last summer, on "Biomarker Testing for Risk Stratification in Metabolic Dysfunction-Associated Steatotic Liver Disease and Metabolic Dysfunction-Associated Steatohepatitis."

See draft DL40187 here.   See final L40187 here.   

See request letter #1 9/19/2023 here.  #2 7/1/2024 here.   Posted as MA Connelly and H Imai, respectively; the latter on Siemens letterhead.

# # #

1. Request letter 1

Letter 1 is a Labcorp request, dated September 18, 2023, asking MolDX/Palmetto for a new LCD for NIS4, described as a non-invasive blood test to identify at-risk NASH in patients with features of metabolic syndrome. The letter frames the request as a Medicare Part B diagnostic clinical laboratory test and argues that access would improve treatment decisions and outcomes.

Tuesday, July 7, 2026

AI Reports as Part of Thinking? The Falling Friction of Knowledge Work

Header: AI is making analytical reports cheap enough that they become tools for thinking, not just finished products.

(Note - this essay generated by Chat GPT 5.5; fifth draft; substantial prompting.)
(This essay began in April, when Stephane Budel/Decibio showed me a 10-page multi-part Claude Opus report.)

 

When Reports Become Part of Thinking

Patterns from Index Medicus to ChatGPT Reveals the Falling Friction of Knowledge Work


I have lived through two revolutions in knowledge work. The first unfolded over several decades. The second seems to be unfolding in just a few years. Although separated by forty years, I think they are fundamentally the same story.

As an MD-PhD student in the early 1980s, performing a comprehensive medical literature search was a significant undertaking. Younger physicians and scientists may find it difficult to imagine how much effort it required.

In 1980, the standard tool for a student was Index Medicus: rows of encyclopedia-sized volumes that occupied many linear feet of library shelves, printed in extraordinarily fine type. A serious literature review meant you sat for hours in front of them.  You  searched these indexes by hand, copying references to ink and paper, and then locating the bound journals themselves, up and down the levels of the library and back and forth to a slow xerox machine.

By the mid-1980s, technology had advanced, but the process remained cumbersome. The National Library of Medicine maintained the MEDLINE database, but few investigators searched it directly. Instead, one met with a medical librarian, described the project, and the librarian formulated and executed the search. Several days later, after a charge of perhaps $50 to a research grant, a stack of paper arrived containing titles and abstracts (probably from a dot-matrix printer.) It was a new generation of service, but it was also slow, expensive, and infrequent.

Then came the Internet. 

CHAT GPT Tries to Understand All 600 PLA Codes

Here's another exercise where we give Chat GPT the ~600 current PLA codes and we ask it to find rhyme or reason in their multitudes.  The text and the analysis below are entirely machine-written with minimal instructions from me.

###

Here are AMA CPT PLA codes up to code 0659U. Some codes have been deleted, so the active file contains 583 lines rather than 659 separate items.

Study them and discuss them for my blog readers. Then assess the codes in categorized groups, using categories that seem reasonable to you. I suggest using no more than ten categories, including an “Other” category. Some codes may fit more than one category; in those cases, use a “best fit” principle.

###



Bruce, Here’s a blog-ready version based on the uploaded workbook. I also created an annotated workbook with the added category column and a summary sheet:
PLA codes categorized summary [not a live link]

(BQ: See tables in Google Cloud here.  Note that there are 2 tabs.)


A Field Guide to the PLA Code Universe:
0001U Through 0659U

The AMA’s PLA code series has become a kind of public fossil record of modern proprietary diagnostics. The file reviewed here runs through code 0659U. Although the numerical series reaches 659, the active workbook contains 583 rows and 581 unique HCPCS codes. Two rows, 0563U and 0564U, appear twice in the file. Thus, 78 code numbers in the 0001U–0659U range are absent from this active list, presumably because of deletions or gaps.

CMS Publishes Federal Register Rules for Software as a Medical Service (Incl Lab Tests)

 A few days ago, this blog flagged that CMS was proposed to take software-intensive lab tests OFF the clinical lab fee schedule (at least in the hospital outpatient setting.)  Here.   We flagged that this is not a lab-only policy but a whole new field of CMS policy for "software as a medical service" or SaMS.  Here.

 "SaMS" occurs 91 times in the outpatient rule.

On July 7, CMS published the Federal Register rulemaking for both (1) SaMS in general AND for (2) SaMS applied to software-intensive lab tests.  Find it here:

https://www.govinfo.gov/content/pkg/FR-2026-07-07/pdf/2026-13656.pdf

Comments due August 31, 2026; starting point here.

Pagination of New Rules

  • CMS overviews SaMS on page 41803.
  • Note that references to new SaMS concepts occur througout the New Tech applications; e.g. 41804 including footnote column 3.
  • The discussion of general SaMS starts on page 41918 to 41920 (plus tables 41921-41925.
  • The discussion of LABORATORY SaMS starts on 41925 and runs to 41926, plus table 41927.  
  • Discussion of new SaMS modifier O1 on page 41929, table 63.

Monday, July 6, 2026

Example of AI Company Research; What's up with Mdxhealth?

 I saw a headline that Mdxhealth received a NASDAQ minimum price warning.  July 2.  

https://mdxhealth.com/press_release/mdxhealth-announces-receipt-of-nasdaq-notification-regarding-minimum-bid-price-deficiency/

I had recently seen it had closed an infectious molecular testing line of business, perhaps related to numerous payor cutbacks in 87798 payments.

I asked Chat GPT for a quick debrief. The text is entirely machine written, including the table, with minimal up-front guidance from me.

##

Mdxhealth is a real operating prostate/urology diagnostics company, but it has a weak public-market situation. The Nasdaq notice means its share price has been below $1.00 for 30 consecutive business days, triggering a minimum-bid deficiency notice. It does not immediately delist the company; Mdxhealth has until December 28, 2026 to regain compliance by closing at $1.00+ for at least 10 consecutive business days. The company also said it may consider a reverse share split if needed. (mdxhealth)

The likely investor concern is not “they only have 87798 microbiology.” It is more like:

  1. They had a reimbursement blowup in Resolve mdx, the UTI/STI infectious-disease business. Novitas issued a roughly $10.4M recoupment decision related to historical Resolve claims, which Mdxhealth says it is contesting. (mdxhealth)

  2. They then decided to exit Resolve mdx and shut down the Plano, Texas lab, leaving restructuring/write-down costs to be recognized later. (mdxhealth)

  3. Their remaining/core business is prostate/urology oncology, not microbiology: Exo mdx, Confirm mdx, and GPS mdx are the current prostate-cancer-oriented lines highlighted on the company site. The company describes itself as focused on “prostate cancer and other urologic diseases.” (mdxhealth)

  4. Financially, they are still losing money. In Q1 2026, revenue was $27.4M, but operating loss was $7.3M, net loss $8.9M, and adjusted EBITDA was negative $4.3M. Cash was $43.2M at March 31, but pro forma for a $15M Exact Sciences earnout payment, cash would have been $28.2M. (mdxhealth)

So a revised capsule would be:

Mdxhealth is not primarily an 87798 microbiology lab. It is a prostate/urologic molecular diagnostics company that bought or built a set of prostate assays, but it also had a Resolve mdx infectious-disease business that became a reimbursement liability. The Nasdaq issue reflects share-price/capital-market distress, probably driven by losses, dilution/cash concerns, and the Resolve/Novitas overhang — not by the absence of a prostate business.

##

I asked about recent acquisitions.

##

Yes. Mdxhealth has been assembling a prostate/urology diagnostics portfolio by acquisition. The two big ones are:

YearSeller / sourceTest / businessComment
2022Exact Sciences / Genomic Health legacyOncotype DX Genomic Prostate Score / GPSMdxhealth bought Exact’s Oncotype DX GPS prostate cancer business for up to $100M, including $25M cash upfront plus stock and earnout structure. This was the old Genomic Health prostate assay, since Exact had acquired Genomic Health in 2019. (mdxhealth)
2025Bio-Techne / Exosome DiagnosticsExoDx Prostate / EPIMdxhealth acquired Exosome Diagnostics from Bio-Techne, including the ExoDx Prostate test, CLIA lab, and related assets, for total consideration of about $15M. The acquisition closed in September 2025. (mdxhealth)  Related fact: BioTechne had paid $250M for Exosome in 2018.
2015NovioGendixSelectMDxOlder acquisition: Mdxhealth acquired NovioGendix, giving it the urine-based SelectMDx prostate cancer liquid-biopsy test. (mdxhealth)

So your memory is right: GPS came from Exact Sciences/Genomic Health, and ExoDx came from Bio-Techne/Exosome Diagnostics. Alongside legacy ConfirmMDx, that gives them a prostate-testing stack: pre-biopsy risk assessment, post-negative-biopsy risk assessment, and localized prostate cancer prognosis/treatment guidance.

The confusing part is that Resolve mdx, the UTI/STI infectious-disease business using codes like 87798, became the recent reimbursement problem and was discontinued. But that was not the whole company. The surviving strategic story is more like: a financially stressed prostate molecular-diagnostics roll-up that also had a failed/discontinued UTI line.

AMA Posts PLA Applications for July-August Cycle

 AMA has posted applications (for public comment) for the July-August application cycle.  

Find them here:

https://www.ama-assn.org/system/files/aug-2026-pla-public-agenda.pdf

Comment via the indicated portal, by deadline July 20.  (I'm not sure the deadline but I'd suggest noon central.)

Palmetto MolDx Shows Up in National News (DCIS)

Palmetto MolDx and its pending decision on DCIS test coverage has made national news on NBC.  The news includes a detailed article as well as video stories. This article quotes Linkd-In, quotes an NBC video, and abstracts points from a long NBC article.


See an article on Linked In by Dan Forche, CEO at PreludeDX.  Prelude makes the "DCISionRT' test to help make decisions about RT (radiotherapy) in DCIS patients.

He links to a firewalled NBC article by Gretchen Morgenstern. Headlining:

"Millions of women may lose Medicare coverage for a breast cancer test hailed by doctors. A private company advising the agency that oversees Medicare has recommended against reimbursing for the biomarker tests, sparking a backlash from cancer specialists."

See the firewalled article here:

And there's a five minute video version:

https://www.nbcnews.com/video/millions-may-lose-medicare-coverage-for-breast-cancer-test-hailed-by-doctors-265914437537

Or at YouTube:

The  5-minute video transcript is here: 

Thursday, July 2, 2026

Payors, Pathology, and MBA Economics: A New 20p AI White Paper

Entry point:

The June 2026 issue of CAP TODAY features an article on pathology business economics by Dr Thomas Mezzetti.  

He cites a 2025 AMA report on health insurance consolidation, and 2024 CAP report on adverse impacts of private payors.  

What happened next:

I asked Chat GPT to read these AMA and CAP reports, and discuss them.  I then asked Chat GPT to frame the high "friction" with payors (prior auth, denials, etc) as a special subtype of a general business phenomenon calld "transaction costs."  (The field of transaction costs has seen 2 Nobel prizes, many books, and hundreds of articles). This is Sidebar 1.  Next, I asked why the universal phenomenon of "transaction costs" becoms so toxic in the form of "payor friction."  Chat GPT explains why, as Sidebar 2.

The resulting analysis, including "Sidebar 1" and "Sidebar 2," are listed below.   They are also available as a 20-page new white paper which also includes a "Sidebar 3" and "Sidebar 4."  In 3&4, I uploaded Chat GPT with some academic articles about transaction costs, to give it more facts to reason with.

Find the 20-page publication here:  white paper.


 

CAP’s 2024 payors white paper and AMA’s 2025 health insurance competition report describe two levels of the same problem. 

CAP shows how insurer interference reaches into pathology: narrow networks, steering, prior authorization, coding edits, take-it-or-leave-it contracts, and disruption of locally integrated diagnostic care. AMA supplies the market-structure explanation: most commercial and Medicare Advantage markets are highly concentrated, giving insurers monopsony power over physicians and hospitals. 

Together, the papers show that payer power is not merely a reimbursement issue but a governance issue. Insurers increasingly control the “rules layer” of health care: networks, documentation, medical necessity, claims edits, appeals, and payment timing. Physicians are weakened by fragmentation; pathologists are especially exposed because their work is essential but often invisible and easily mischaracterized as commodity testing.

This white paper then builds beyond summary to offer an original industry-strategy argument. Payer “friction” is often taken for granted as the familiar background noise of health care administration — denials, prior authorization, coding edits, appeals, and related burdens. Viewed through the Nobel Prize-winning work of Ronald Coase and Oliver Williamson, however, this friction can be understood as a manifestation of transaction costs that, under asymmetric market power, may become instruments of control.

###

The 2027 OPPS Proposed Rule: CMS Wrestles Actively with Software as a Medical Service (SaMS)

 Header:  The OPPS proposed rule for 2027 is released.  After a couple years of patchwork solutions, CMS adopts broad interim measues for software-dominant services.  CMS also promised a more worked-out plan for next year.

##

Find the proposed rule here:

https://www.federalregister.gov/public-inspection/2026-13656/medicare-program-hospital-outpatient-prospective-payment-and-ambulatory-surgical-center-payment

##

CMS Takes the Next Step on Paying for Medical Software:

From RFI to Rulemaking

In July 2025, CMS asked the public how Medicare should think about reimbursement for software-based medical services. It did so in both major Medicare payment worlds: the Physician Fee Schedule, where the issue is practice expense and Part B professional services, and OPPS, where the issue is hospital outpatient payment. In the PFS proposal, CMS specifically asked for comment on “Software as a Service,” noting that software algorithms and AI do not fit comfortably into older practice-expense categories built around clinical labor, supplies, and equipment.

Run, Don’t Walk: AMA CPT Big Changes for Software-Dependent Services

Run, Don’t Walk: AMA CPT Big Changes for Software-Dependent Services

I wrote a long blog on Appendix S a few days ago, here's the concise version I used as a mini-post on Linked In.
###

AMA has published the 2027 version of “Appendix S,” its greatly-revised policies for software-intensive services. 
  • But there’s more! AMA is also rolling out BIG changes and never-before-seen requirements in the CPT new code process.
  • Apply quickly to understand and track these changes before the 9/2026 CPT meeting in Minneapolis.

See the AMA CPT AI press release:
https://lnkd.in/gufqGaNj

See the new 2027 Appendix S for AI:
https://lnkd.in/gZ-55ggj

Go to AMA CPT “Smart App”, being sure you click at top for “interested Party Portal.” (May require email registration.)
https://lnkd.in/gx-YVr8P

Now, click on Tab 94 for IP (Interested party) access.

This is the lab version of the CPT application, but I believe the general-code version opens for comment by July 13.

See "green" text: There are A LOT of changes proposed for evaluating and documenting AI or other software during the CPT application process – including a lot of new applicant work and new committee review responsibilities.

I expect by mid-July CMS will release the same changes for the "general purpose" code change process.  AMA CPT may also soon release information on the new CMAA algorithmic services code category - that will be either now July-August or this winter December-January.

CMS Drops a Bomb on top of AI Lab Policy (OPPS Rule)

HEADER: CMS Proposes Big Shift for Software-intensive Lab Services

 See pages 457-462 of the new Hospital Outpatient rulemaking for CY2027:

https://www.federalregister.gov/public-inspection/2026-13656/medicare-program-hospital-outpatient-prospective-payment-and-ambulatory-surgical-center-payment

Update: The July publication in Fed Reg is here:

https://www.govinfo.gov/content/pkg/FR-2026-07-07/pdf/2026-13656.pdf


###

What was Wet Lab and Dry Lab is now... Wet Lab and Not-A-Lab?  ?!?

###


News in Brief

[ChatGPT]

CMS has proposed a major CY2027 OPPS policy shift for “software as a medical service” analyses performed on prior laboratory test data. In recent years, lab AI and lab-plus-algorithm services have often been channeled through MAAA, PLA, and CLFS coding/payment pathways. The new OPPS proposal partially reverses that direction. 

CMS argues that once the original laboratory work is complete, downstream algorithmic analysis of stored data—such as genomic, transcriptomic, or digital pathology data—may no longer be a clinical diagnostic laboratory test at all.

CMS proposes to move 10 such HCPCS codes out of the CLFS and into OPPS New Technology APCs, with a new status indicator “O1” for separately paid software-as-a-medical-service items. The agency emphasizes that these analyses may be performed by non-CLIA software entities, creating a new Medicare boundary between the laboratory test and later AI/software interpretation.

[I'm not sure that they can be performed by non-CLIA entities, but I'll leave that to CLIA law experts.]


Deeper Dive

CMS’s CY2027 OPPS proposed rule includes a compact but potentially far-reaching section on what it calls “SaMS analyses performed on laboratory tests.” SaMS stands for software as a medical service. The target is not ordinary hospital software, and not simply AI used inside a lab workflow. Rather, CMS is focused on algorithmic analyses performed downstream of a prior laboratory test, especially where the raw or processed data already exist and the later service is essentially computational.

CMS gives the example of genomic sequencing. The sequencing itself may be performed once by a CLIA-certified laboratory. But after that, the same underlying sequence data can be reanalyzed many times by different algorithms to produce diagnostic, prognostic, risk, or treatment-related information. CMS’s key point is that this later algorithmic step may not require a CLIA laboratory at all. A non-CLIA software entity with the relevant program could perform the computation. That distinction drives the policy proposal.

This is why the proposal feels like a flip-flop from the recent coding and payment trajectory for lab AI. Over the past several years, the ecosystem has treated many lab-plus-algorithm products as laboratory services. AMA created MAAA codes for multi-analyte assays with algorithmic analysis. PLA codes have also been used for proprietary lab and algorithmic services. CMS has then often placed these items on the Clinical Laboratory Fee Schedule, using crosswalk or gapfill logic. In practical terms, the system has been willing to treat “lab data plus algorithm” as a lab test.

Now CMS is drawing a sharper line. The agency says it does not believe these secondary algorithmic analyses should be considered clinical diagnostic laboratory tests or priced under the CLFS when they do not require CLIA-regulated laboratory performance. CMS instead characterizes them as “other diagnostic tests” under Medicare law, not “diagnostic laboratory tests.” That is a significant conceptual move.

CMS also flags payment-policy concerns

  • The CLFS generally lacks beneficiary cost-sharing and is not budget-neutral in the same way OPPS is. 
  • CMS also says it often receives limited transparent cost information for algorithmic components because companies consider the details proprietary. 
  • Historically, CMS may have relied on visible lab methods in code descriptors—NGS, RT-PCR, methylation, and so on—but CMS now says that comparison is not appropriate when the service at issue is entirely computer-based.

For CY2027, CMS proposes to assign 10 existing HCPCS codes to OPPS New Technology APCs, choosing APC bands that approximate current CY2026 CLFS payment levels. These include oncology and digital pathology AI services, transcriptomic or genomic algorithmic analyses, tumor-response prediction, recurrence scoring, MSI/HRD assessment, and comparator exome analysis. The proposal also creates a new status indicator, “O1,” meaning software as a medical service, paid separately under OPPS.

The larger issue is not just these 10 codes. CMS also proposes that future SaMS analyses performed on lab-test data should go to New Technology APCs under OPPS rather than the CLFS. If finalized, this could reshape the business model for lab-adjacent AI, blur the old PLA/MAAA assumptions, and force companies to think much harder about whether their product is a laboratory test, a software diagnostic, or both.

##

##

SIDEBAR: The Road to Today...

The CMS OPPS announcement was inevitable once AMA CPT last winter began issuing lab-AI codes as Category III codes. CMS handles every Category III code in its OPPS rulemaking, so the AMA CPT maneuver back in February,  loaded the gun for this OPPS proposal now in July.

SIDEBAR: Odd Code List Table

CMS lists 9 PLA codes plus CPT code 81416 (comparator exome).  I would think they'd leave off wet lab exome 81416, but could have included 81417 (exome re-analysis dry lab) and 81427 (genome re-analysis dry lab.)  0418U is "out" (found on the table, immuno + algorithm) but 0295U isn't (immuno + algorithm), etc.  

SIDEBAR: Re-examining Genomes

Timely to this discussion: New high-bandwidth approaches to reviewing genomes/exomes at future dates.  See See Welland et al here (24 June Nat Med), see briefing here, coverage at Genomeweb here.

SIDEBAR: Typo  493.21, 493.2

CMS refers erroneously to "CFR 493.21," which does not exist.  What CMS is saying there - in awful syntax - is that it thinks there are things that are performed on lab tests, which are software rather than CLIA lab services (as define at CLIA 493.2).  These "things" will be called, by CMS, SaMS or Software as a Medical Service.

 There's no claim by CMS that SaMS is a CLIA term, at 493.2, 493.21 (sic), or anywhere else. 


What was Wet Lab and Dry Lab is now... Wet Lab and Not-A-Lab?

Changing Codes Table 62. Two parts.  Click to enlarge.




Tuesday, June 30, 2026

Lighthouse Lab Services / July 22 / Webinar on Qui Tam Developments

Back on April 23, I posted an AI-driven analysis of a new qui tam court case involving, "MD Labs."

Lighthouse Lab Services will host a webinar on the topic on July 22, with some of the original attorneys involved.  (Some of them also spoke at Executive War College a month back.)

Register here:

https://www.linkedin.com/events/7477359203842482176/



Monday, June 29, 2026

A New Go-To Essay on the Value of CDx (from Hannah Mamuszka)

Hannah Mamuszka, a cofounder of consultancy Alva10, has released a Go-To Essay on the Value of CDx, particularly in a world where drugs are increasingly expensive.

This caught my attention in part because I was able to co-author an article this spring about how diagnostics get more and more cost-effective as drug costs rise (Kansal et al., 2026).  

Mamuszka discusses a wide range of emerging drug/test examples, and discusses some marketplace disincentives to better HEOR. 


Find Mamuszka's essay at Substack here:

https://substack.com/home/post/p-196116530


Here’s a ~200-word summary / Chat GPT:

Hannah Mamuszka argues that the national debate over drug prices misses half the problem: many drugs are prescribed to patients who will never respond to them. Modern drug development often targets specific biological pathways, yet prescribing still frequently proceeds by trial and error. TNF inhibitors, for example, may work well for patients whose disease is TNF-driven, but response rates are often only around 30–40%. Similar issues occur across oncology, autoimmune disease, cardiology, psychiatry, and other fields.

The remedy, she argues, is broader use of diagnostics that predict either drug response or serious toxicity. Pharmacogenomic tests can identify patients at risk from drugs such as fluoropyrimidines, thiopurines, abacavir, clopidogrel, and antidepressants. Response-prediction tests can determine whether a patient’s disease biology matches a drug’s mechanism, as already accepted in many areas of oncology.

The obstacle is not scientific feasibility, but market design. Pharma benefits from broad drug markets; PBMs may favor drugs with higher rebates; insurers often resist paying for tests. But employers and patients may increasingly see the value of diagnostics that prevent months of ineffective, costly, or harmful treatment. The core message: precision diagnostics are not a luxury; they are a way to stop paying for predictable failure.

Saturday, June 27, 2026

Humor: AI News Article About My Appendix S Blog

Header: All About a New Blog about Appendix S


June 27, 2026 (Los Angeles)

By: Chat GPT 5.5

In a new post at Discoveries in Health Policy, medical innovation and reimbursement expert Bruce Quinn uses an unusual but effective format: he asks two advanced AI systems to analyze the AMA’s revised 2027 CPT Appendix S, then compares their conclusions. The result is a layered review of one of the more important technical-policy documents now shaping how artificial intelligence may be described in medical coding.

The central finding is that AMA’s revised Appendix S is a real improvement over the prior version. The newer taxonomy moves away from vague language about “work performed by the machine” and instead focuses on software outputs, clinical meaningfulness, and the role those outputs play in care. The familiar three categories remain: assistive, augmentative, and autonomous. But the 2027 version gives these categories sharper practical meaning.

Both AI reviews identify the same unresolved problem. Appendix S is titled as a taxonomy for artificial intelligence, yet it expressly declines to define “AI.” That may be defensible, since CPT generally codes medical services rather than underlying technologies. But it creates an odd threshold issue: if “AI” is undefined, when exactly must an applicant use the AI appendix?

In an interview, Quinn provided this example. An applicant feels his service is not AI, and doesn't refer to Appendix S.  At review, several panelists feel the service is AI, and can't proceed without conformity to Appendix S.  But now 3 or 4 panelist voice their agreement with the applicant, and say the service falls outside of Appendix S.  More panelists join each side of the debate, offering diverse rationales for either position.  How is this paradox to be resolved, with no AMA definition of AI?

The stronger critique concerns decision logic. The revised Appendix S is written in prose and table form, but it does not provide a flow chart or formal classification rules. Quinn’s post emphasizes that this matters because ambiguous prose can hide contradictions. A logic tree would have forced the AMA to write an equally logical appendix - and decide whether classification turns on the type of software output, the physician’s role, or the action that follows.

The Claude analysis adds a particularly useful point: Appendix S may be blending two axes—output type and physician involvement—while treating them as one. That could create edge cases and contradictions for developers, payers, and CPT applicants.

Overall, the post is a thoughtful, technically informed critique: Appendix S is improving, but it still reads more like a negotiated taxonomy than a fully tested classification machine.


___

See also: Is an ICD an AI?

See also:  AMA press release on New Appendix S:

https://www.ama-assn.org/practice-management/cpt/cpt-editorial-panel-strengthens-ai-taxonomy-keep-pace-tech

Appendix S from A to Z. Two AI's Review New Appendix S for 2027

 Two AI's Review the AMA's New Artificial Intelligence Coding Rules "Appendix S 2027"

See AMA"s press release about early-release of a new Appendix S on AMA CPT AI Policy.

https://www.ama-assn.org/practice-management/cpt/cpt-editorial-panel-strengthens-ai-taxonomy-keep-pace-tech

As of June 27, I believe the 2027 version of Appendix S is here:

https://www.ama-assn.org/practice-management/cpt/cpt-appendix-s-taxonomy-artificial-intelligence-medical-services-procedures

And the 2025-and-earlier version still online here;

https://www.ama-assn.org/system/files/cpt-appendix-s.pdf

The rest of this blog is a comparison of New and Old "Appendix S," first by Chat GPT then by Claude Opus.


###

CHAT GPT 5.5 followed by CLAUDE OPUS 4.8

###

AMA’s 2027 Appendix S improves the AI taxonomy by focusing on software outputs, clinical meaningfulness, and the assistive/augmentative/autonomous distinction. But it still oddly refuses to define “AI,” and it lacks formal decision rules or a flow chart. Without logic-tree testing, the prose may hide ambiguities, contradictions, and edge-case classification problems for future CPT applicants and reviewers.