Legislation: Where to Find It: Delay Lab Pricing 30 Days. Spend $50B for Rural Health Technology.

 Too pieces of recent legislation and where to find them.

HR 5731 and Section 6209 PAMA

The bill that ended the Fall 2025 government shutdown was HR 5731.   Look to Section 6206 to find a 30-day delay in the next implementation of PAMA lab pricing cuts.  Find many Medicare payment rules by searching "1834" and find PAMA changes by searching "1834A."

https://www.congress.gov/bill/119th-congress/house-bill/5371/text

click to enlarge

For comparison, 6206 tweaks ambulance payments and section 6208 extends telehealth flexibility, the first to January 30 and the second to January 31.

Coverage at Genomeweb.

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RURAL HEALTH TECHNOLOGY HR 1

This was the "Big Beautiful Bill" and it includes a big beautiful $50 billion dollars for rural health technologies.

https://www.congress.gov/bill/119th-congress/house-bill/1

https://www.congress.gov/bill/119th-congress/house-bill/1/text

Government Summary

1. (Sec. 71401) This section provides $10 billion per fiscal year for FY2026-FY2030 for a program that supports the provision of health care in rural areas. 
2. Under the program, states may apply for financial allotments to improve the access and quality of care of services in rural areas, such as through enhanced technology, strategic partnerships, and workforce training. States must submit detailed rural health transformation plans and certify that no funds will be used to finance the non-federal share of Medicaid or CHIP. The CMS must approve or deny applications by December 31, 2025; states that receive approval do not need to reapply each year. States are not required to contribute any matching funds with respect to program allotments.
3. The CMS must award allotments so that 50% of funds are awarded equally among all approved states. The remaining 50% of funds must be awarded based on certain considerations, including the proportion of rural health facilities in the state compared to the number of such facilities nationwide.
4. The section additionally provides $200 million for FY2025 for the CMS to implement the program.

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AI Summary (Chat GPT 5)

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Below is a structured ~500-word paragraph-style summary of Section 71401 (Rural Health Transformation Program), integrating the statutory foundations with the implications for med-tech and health-IT suppliers, and concluding with what CMS is likely doing operationally in the first six months and into CY2026.

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Section 71401 of the 2025 budget reconciliation law establishes the Rural Health Transformation Program, a $50 billion, five-year mandatory spending initiative aimed at restructuring and modernizing rural health care delivery in all 50 states. 

Between FY2026 and FY2030, CMS will allocate $10 billion per year to states that submit approved “rural health transformation plans.” These plans must improve access to rural hospitals and providers; enhance health outcomes; integrate new and emerging technologies; promote regional partnerships and economies of scale; strengthen rural clinical workforce supply; and present credible strategies for long-term hospital solvency. 

States may use the funds for at least three of a defined set of “health-related activities,” including evidence-based chronic disease interventions, limited provider payments, consumer-facing technology solutions, the adoption of advanced technologies such as remote monitoring, robotics, AI, and other innovations; workforce recruitment; major information technology upgrades; cybersecurity improvements; and reconfiguration of service lines across the full continuum of rural care. 

Only a small fraction of each state's allotment (10 percent for administrative costs, 15 percent for provider subsidies) may go to overhead or direct financial support, ensuring that the majority of funds flow into structural modernization rather than temporary relief.

The implications for medical technology, diagnostics, and health IT suppliers are significant, even though the statute avoids naming specific product categories. The law repeatedly emphasizes “new and emerging technologies,” “technology-driven solutions,” “technology-enabled solutions,” “software and hardware,” “information technology advances,” and “advanced technologies, including remote monitoring, robotics, artificial intelligence.” 

This creates a statutory foundation for a wide range of equipment and digital platforms, from connected diagnostic devices and point-of-care instruments to telehealth infrastructure, imaging and pathology informatics, remote monitoring systems, cybersecurity architecture, and cloud-based workflow systems. 

For med-tech suppliers, the opportunity lies not in selling individual devices but in positioning integrated solutions that help states satisfy the transformation plan requirements: improving quality, stabilizing rural access, reorganizing service lines, and modernizing workforce-limited settings. For health-IT suppliers, the strongest hooks are in the explicit authorization for software, hardware, interoperability, and cybersecurity upgrades—essentially giving states legal authority and federal dollars to modernize outdated rural hospital infrastructure, strengthen data systems, and deploy digital tools that enable new care models.

The View from CMS

In the first six months after passage (July–December 2025), CMS is likely occupied with program design, application review, and operational scaffolding. Statutory deadlines required states to submit applications by the end of 2025, meaning CMS staff were working intensively to publish guidance, answer technical questions, process fifty state applications, and build the internal analytics necessary to score transformation plans. 

CMS also needed to design the allocation formula that splits funds evenly across states and distributes the remainder based on rural population, facility mix, and other factors. 

Internally, CMS likely staffed or expanded a cross-agency team, activated its $200 million implementation budget, coordinated with OGC for legal interpretation, and began constructing mandatory reporting templates, oversight frameworks, and technical-assistance resources for states.

Looking into CY2026, CMS will shift from startup activity to execution: approving applications, issuing allotments, conducting early monitoring, and guiding states as they begin procurement and program rollout. CY2026 will be the year when states translate their plans into concrete vendor partnerships for IT modernization, diagnostic upgrades, workforce support technologies, telehealth expansion, and advanced digital tools. 

CMS will simultaneously face a growing oversight burden—tracking expenditure, ensuring compliance with allowable uses, and responding to inevitable questions from Congress, GAO, and state stakeholders about whether the $50 billion is producing measurable improvements in rural access and stability.

Siemens' Remarkable Comments to CMS on Software Reimbursement - the New "Must-Read?"

 For several years CMS has struggled with changing, vague, or counterproductive policies for how topay for software-dominant services.   This year, the Senate introduce S.1399, which (if passed) would force CMS to develop coherent software reimbursement policies, at least in the OPPS setting.   Last July, CMS inserted a Request for Information into both the PFS and OPPS rules.  Numerous parties responded (you can find all rulemaking comments online), but CMS has only responded to the extent of saying, "Thanks for getting back to us, we'll be reading that" to stakeholders.

In this blog I'll focus on the responses from Siemens to both the PFS and OPPS rules.  To help you, I'll put a zip file in the cloud four documents, the two RFIs and the two Siemens letters.

https://drive.google.com/file/d/1kKdDr14gczk-ATk8MrT3ovoL5WqirZUa/view?usp=sharing

I've read both letters but I can't write a better summary than Chat GPT 5 does, below.  Worth reading.

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AI CORNER

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Overview of Siemens Comments to RFI’s on SaaS

 Siemens Healthineers’ comments to CMS on the July 2025 PFS and OPPS RFIs reflect a highly coordinated, sophisticated strategy to shape the reimbursement landscape for artificial intelligence, software-driven clinical analytics, and broader digital health technologies.

Across both rulemaking venues, Siemens proposes a conceptual shift away from CMS’s narrow framing of “Software-as-a-Service (SaaS)” toward a broader and more inclusive category they call Algorithm-Based Healthcare Services (ABHS). This new term deliberately captures not only cloud-based software tools but also AI and machine-learning applications embedded[1] in imaging equipment, delivered via web or workstation, or provided by third-party analytic vendors. By urging CMS to adopt ABHS as the central regulatory category, Siemens is effectively attempting to define the vocabulary—and therefore the policy architecture—through which Medicare will evaluate and pay for clinical AI. In regulatory affairs, naming the category often determines how the category will be regulated, and Siemens is moving early to ensure that the definitions mirror its own wide-ranging digital portfolio.

In both letters, Siemens argues that AI-driven analytic services must receive separate, explicit payment, rather than being folded into packaged payments for imaging or other underlying procedures. They underline that packaging AI into base procedure codes would immediately suppress adoption and undercut the value proposition of these technologies.[2]  To prevent this, Siemens requests that CMS codify formal regulatory text guaranteeing separate payment for ABHS—even providing draft language for 42 CFR 419.2 in the OPPS comment letter. This is a significant move: Siemens is no longer asking CMS to “consider” separate payment, but is proposing the actual legal language that would lock separate payment into federal regulation. These comments also push CMS to explicitly shield ABHS add-on codes from OPPS packaging rules—an attempt to close every possible loophole through which CMS might inadvertently or intentionally eliminate separate payment in future rulemaking.

Another major pillar of Siemens’ strategy is the request that CMS automatically place all new ABHS CPT codes into New Technology APCs for a minimum of five years, using manufacturer-supplied cost data rather than unreliable early Medicare claims. Siemens argues that early claims for new AI services are frequently distorted by incorrect revenue code assignments, slow hospital adoption, and lack of clear billing pathways. By providing a five-year protected runway—parallel to the lifespan of Category III codes—CMS would ensure stable and predictable reimbursement while allowing enough time for claims data to mature. This approach mirrors the policy logic behind transitional pass-through payments and NTAP in the inpatient setting. Siemens also requests that these ABHS codes be exempt from the Universal Low-Volume APC policy, which otherwise risks downward payment bias for emerging technologies.

Siemens devotes substantial attention to the unique cost structure of AI technologies, emphasizing that ABHS products involve ongoing subscription or licensing fees, cloud computing costs, cybersecurity infrastructure, integration with EHRs, and ongoing staff training. These are not capital costs, and they do not resemble the equipment depreciation and clinical labor inputs that CMS traditionally uses to calculate reimbursement. Consequently, Siemens argues that CMS must modernize its resource-based methodology or risk chronically undervaluing digital health technologies. They also highlight that AI often generates additional clinical outputs, which increase cognitive workload for physicians rather than replacing it. Clinicians must review expanded information, validate algorithmic findings, integrate AI-derived insights into care planning, document the use of AI, and communicate results to patients. Siemens leverages this point to argue for meaningful work RVUs under the PFS, counteracting any CMS assumption that AI reduces professional effort.

Interwoven throughout these comments is Siemens’ broader strategic posture as both a policy thought leader and a legislative partner. Siemens explicitly supports Senate Bill 1399, the Health Tech Investment Act, which directs CMS to create clear reimbursement pathways for AI. Even though the bill is unfunded, Siemens recognizes that it carries substantial agenda-setting force; it can push CMS to create the structural payment models Siemens wants. By aligning itself with S.1399 and proposing fully formed regulatory text, Siemens positions itself not merely as a stakeholder responding to CMS, but as an architect offering CMS a ready-made blueprint for national AI reimbursement. Siemens also calls for CMS to convene a national public forum on ABHS, which would cement Siemens’ role as a central voice in federal policymaking and create a venue where Siemens can influence the conceptual and technical underpinnings of AI reimbursement.

Ultimately, Siemens’ comments reveal a comprehensive, proactive attempt to define how Medicare will recognize, categorize, and reimburse AI-enabled clinical services. Their strategy seeks harmonization across PFS and OPPS, codification of separate payment, early placement into New Technology APCs, explicit valuation of physician work, and modernization of cost inputs. Through legislative alignment, regulatory drafting, and conceptual reframing of AI as a clinical analytic service rather than as a software add-on, Siemens attempts to shape a durable federal policy framework that supports innovation while aligning closely with the structure and economics of its own product portfolio.

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[1] I believe SaaS implies “cloud” and skips “embedded.”

[2] For published thinking on Ai reimbursement policy, see Warshawsky and others. https://www.discoveriesinhealthpolicy.com/2025/11/center-for-medicare-innovation.html

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See my earlier blog about Artera and PathAI comments specific to digital pathology,

https://www.discoveriesinhealthpolicy.com/2025/10/pathai-proposes-new-coding-system-for.html

And general blog about the OPPS and PFS comment cycle,

https://www.discoveriesinhealthpolicy.com/2025/10/very-brief-blog-see-search-comments-on.html

Prasad & Makary: Radical New Ideas for Drug Approvals; Do They Matter to Diagnostics??

 On November 12, 2025, NEJM published an important new essay by Vinay Prasad MD and Martin Makary MD, the head of drug approvals and the commissioner of the FDA.

The essay, titled, "FDA's New Plausible Mechanism Pathway," states that new therapies "challenge traditional models of drug and biologic development" at FDA, and require new thinking.  The article is getting a fair bit of attention.

Let's ask, are there ideas in the Prasad-Makary assay that apply to genomics and other diagnostic tests?  If so, what are the points of application, and where is there a mismatch?

https://www.nejm.org/doi/pdf/10.1056/NEJMsb2512695

See coverage at Fierce Biotech, Politico Pro, Biopharma Dive, and Stat+.

See also an excellent 7-page review at Linked In by AgencyIQ about Makary’s vision for "continuous trials."  Here. 

ACLA Scores Short-Term Win in PAMA Pricing!

With the budget that reopened the government on November 13, 2026, ACLA scored a short term win in delaying PAMA cuts.  I'll quote them below.

https://www.acla.com/acla-applauds-enactment-of-short-term-pama-relief-in-spending-package-and-urges-advancement-of-results-act/

Washington, D.C. – The American Clinical Laboratory Association (ACLA) applauds the enactment of a short-term delay to payment cuts to the Medicare Clinical Laboratory Fee Schedule (CLFS) and data reporting requirements under the 2014 Protecting Access to Medicare Act (PAMA), included in the federal government funding package. 

The provision delays these harmful policies through January 30, 2026. 

Without this latest extension, laboratories would have faced a fourth round of cuts—up to 15 percent reductions on roughly 800 tests—along with burdensome reporting mandates beginning in [January 1] 2026.

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“Now, Congress has a vital opportunity to prioritize enacting meaningful, permanent reform through the Reforming and Enhancing Sustainable Updates to Laboratory Testing Services (RESULTS) Act (H.R. 5269 / S. 2761).” [the President of ACLA] added. “ACLA is committed to working with lawmakers and key health care committees to advance the RESULTS Act and protect patient access to critical laboratory testing services nationwide.”

The RESULTS Act would modernize the CLFS rate-setting process by leveraging comprehensive, representative commercial market data while significantly reducing administrative burdens on laboratories and the Centers for Medicare & Medicaid Services.

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See an October 30, 2025, two-page letter to both House and Senate.

https://www.acla.com/wp-content/uploads/2025/10/2025-RESULTS-Act_Provider-Letter-10.30.25.pdf

Trump Administration: Far Less Rulemaking 2025 vs 2024

Did the Trump Administration do far less rulemaking in their first year than Biden in year four?

Last year, the Physician Fee Schedule final rule appeared at 89 FR 97710.

This year, the same final rule appeared at only 90 FR 49266 - about half as many pages along in the Federal Register.

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Their are some balancing factors.  The Biden rule appeared December 9, 2024, the Trump rule November 5, 2025.  The Trump administration was shut down during October.   Still, these don't account for the 50% difference in sheer regulatory volume between page 49266 and page 97710.

For-Example AI Essay: CLIA Registration but not a License [REVISED]

[REVISED]

Someone was talking to me about a lab having "CLIA Registration but not a License."

The question is a source of immediate confusion because the CLIA agency does not seem to use the term "license" but rather has three types of registration status (CoR, CoC, CoA as further below).  While I've seen AMA PLA instructions that use the term [CLIA License].

Here is a key passage from a CLIA agency government PDF:

https://www.cms.gov/files/document/laboratory-quick-start-guide-cms-clia-certification-november-2024.pdf

Here's what I came up with after several emails with colleagues and after reading more CLIA documents like the link above.

It appears the CLIA agency avoids the term "License" - for example the word LICENSE does not appear in this detailed four page PDF:
https://www.cms.gov/files/document/laboratory-quick-start-guide-cms-clia-certification-november-2024.pdf

But if you look at AMA CPT PLA instructions, they do use the term "CLIA license."

https://www.ama-assn.org/system/files/cpt-pla-codes-tutorials.pdf

What you do have is:

STAGE A

Applied online for certificate.    At this short initial stage, you get a clia number as a tracking number but it is not active.  This stage does not have a formal name.

STAGE B

CLIA issues CERTIFICATE OF REGISTRATION or CoR.   

This is based on a paperwork review at the CLIA agency.  For example, your director and other senior staff have appropirate credentials. 

You hope to get this CoR a month or two after the day you applied.   This is good for up to two years AND IT DOES ALLOW complex testing assuming you applied for complex testing and demonstrated on paper you have the right people.

STAGE C1

You get INSPECTION and upgraded to a CERTIFICATE OF COMPLIANCE or CoC (from CLIA) or

OR

STAGE C2

You get INSPECTION and upgraded to a CERTIFICATE OF ACCREDITATION or COA (from CAP or Joint Commission).

Relationship to PLA application at AMA CPT:

https://www.ama-assn.org/system/files/cpt-pla-codes-tutorials.pdf

When readers read that AMA PLA application instructions require a "CLIA license," readers may be uncertain if this means any of the three certificates (CoR Registration - CMS CLIA paperwork review passed, lab is active) (CoC Compliance - site visit by CLIA passed) (CoA Accredidation - site visit by CAP passed).   Or is there any chance PLA "means" only the two certificates issued post-inspection (CoC, CoA).

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AI CORNER [REVISED]

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 What “CLIA Registration” Really Means — Untangling a Common Point of Confusion

In CLIA discussions, few phrases create more misunderstanding than “registered but not licensed.” The confusion stems from the fact that “registration” has both an informal meaning in everyday conversation and a formal meaning within the CLIA regulatory framework. 

The formal term: Certificate of Registration (CoR)

Under CLIA, a Certificate of Registration (CoR) is not just a placeholder or a pre-approval. It is a valid CLIA certificate issued to new laboratories applying for either a Certificate of Compliance (CoC, from CLIA itself) or a Certificate of Accreditation (CoA, i.e. accreditation by CAP).   

 The Certificate of Registration is issued when the application has passed a paperwork review, but not yet a physical inspection.

The CoR is temporary—valid for up to two years—but during this period it fully authorizes the laboratory to perform moderate- and high-complexity testing, as well as waived testing.  (See the quotation that opened this essay).

The purpose of the CoR is to allow a new laboratory to begin operating while awaiting its first full inspection. After that inspection, the CoR is replaced by a CoC or CoA. Until that transition occurs, the CoR serves as the operative license, and no additional CLIA certification is required for the lab to run non-waived tests.

The informal usage: “We’re registered with CLIA”

Outside of regulatory documents, companies often use “registered with CLIA” loosely to mean that they have submitted an application, received a CLIA number, and appear in CMS’s database. 

This status—essentially a pending application that has been filed but not reviewed—does not authorize any moderate- or high-complexity patient testing. A CLIA number alone is not a certificate.

Thus, the informal phrase “registered but not licensed” probably refers to this pre-certificate stage, not to a laboratory holding an actual Certificate of Registration.

Why the distinction matters

The formal CoR and the informal “registration” reflect two entirely different regulatory statuses:

Status	Formal CLIA Term?	Does it authorize moderate/high-complexity testing?
Application submitted, CLIA number assigned	No	No
Certificate of Registration (CoR) issued	Yes	Yes
Certificate of Compliance (CoC) [CLIA]	Yes	Yes
Certificate of Accreditation (CoA) [CAP]	Yes	Yes

Understanding these distinctions prevents the common error of assuming that a “registered” laboratory cannot legally perform testing. In CLIA’s vocabulary, a Certificate of Registration is itself the legal authority to operate until inspection.

The bottom line

A CLIA Certificate of Registration is a genuine, valid CLIA certificate that authorizes all levels of testing for up to two years while a new laboratory awaits inspection. The lab's paperwork has been reviewed, and passed, but the inspection is still in the future.  Confusion only arises when “registration” is used informally to describe the pre-certificate stage. Clarifying this difference ensures accurate communication, particularly in regulatory, operational, and consulting contexts where the precise meaning of CLIA terms has real consequences.

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You said:

Could you give an example with ABC LAB? which is a new lab. Make it concise but use dates as examples to make it seem more concrete.

ChatGPT said:

Here is a concise, concrete example you can drop into your blog:

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Example: ABC Lab and the Difference Between “Registration” and a Certificate of Registration

Imagine ABC Lab, a brand-new molecular diagnostics lab.

January 5, 2026

• ABC Lab submits its CLIA application. CMS assigns a CLIA number the same week.
• At this point, ABC Lab is informally “registered” in the database—but it cannot perform any moderate- or high-complexity patient testing.

February 1, 2026

• CMS issues ABC Lab a Certificate of Registration (CoR).
• This is a real CLIA certificate, valid for up to two years, and it immediately authorizes ABC Lab to begin performing moderate- and high-complexity testing while awaiting its initial inspection.

It means the applicatoin has passed an initial review - for example, that high-complexity staff have appropriate training per the application on January 5.

September 2026
The state agency performs ABC Lab’s first full CLIA inspection.

October 2026
After passing inspection, ABC Lab’s CoR is replaced with a Certificate of Compliance, which becomes the long-term certificate for the lab.

This example shows the key distinction:

• A CLIA number alone (January) does not authorize testing.

• A Certificate of Registration (February) does authorize testing until inspection.

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I can also format this as a shaded call-out box, sidebar, or timeline graphic if you want it to visually stand out in your blog.

You said:

what happens between January 5 and Feb 1? They just read the lab's name and address at CLIA?  

ChatGPT said:

Between January 5 (application submitted) and February 1 (Certificate of Registration issued), it looks like “nothing is happening”—but in reality CMS and the state CLIA agency are doing several non-trivial administrative checks behind the scenes. None of it is glamorous, but none of it is simply “reading the name and address,” either.

Here is what actually occurs during that gap.

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What Happens Between Application and Issuance of the Certificate of Registration

1. CMS validates the application data (CLIA-116)

They review that ABC Lab has provided:

• Correct lab type (e.g., independent, hospital-based, physician office, etc.)

• Accurate address and contact information

• Appropriate test menu (claimed complexity)

• Proposed clinical specialties/subspecialties

• Correct payment category (fees vary by complexity and test volume)

This includes checking for mismatches—e.g., a lab claiming high-complexity molecular testing but listing personnel who only qualify for moderate complexity.

2. Verification of the Laboratory Director’s credentials

This is the most time-consuming part.

CMS/state reviewers confirm that the proposed director:

• Meets CLIA high-complexity director requirements (PhD + board certification, pathology MD, etc.)

• Has appropriate documentation (licenses, ABMGG/ABMM/ABP certification, or equivalent)

• Has no gaps, mismatches, or missing credentialing documents

If anything is incomplete, CMS requests additional materials—this alone can stretch the timeline.

3. Personnel review for key positions

For moderate- or high-complexity labs, CMS may also check:

• Technical supervisor qualifications

• Clinical consultant qualifications

• General supervisor qualifications

For some states, this must be manually approved.

4. Fee processing and confirmation

CLIA will not issue a certificate until:

• The invoice is generated

• The lab pays the fee

• The payment is confirmed by the accounting contractor

This can add 1–2 weeks depending on timing.

5. Enrollment in Proficiency Testing (PT)

CMS verifies that the lab has:

• Selected an approved PT provider (e.g., CAP, API, AAB)

• Enrolled in applicable PT programs for the tests they plan to run

A lab cannot claim certain specialties on its CoR without demonstrating PT enrollment.

6. Assignment to the state survey agency or accreditation body

CMS flags the new lab for:

• State inspection (if pursuing a Certificate of Compliance), or

• Accreditation review (if applying under CAP, COLA, etc.)

This step places the lab in the queue for its upcoming inspection, and the CoR cannot be issued until this routing is configured.

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So is it trivial paperwork?

Not really.
It’s bureaucratic and unexciting, but it is real work that must be manually verified.

Most delays occur because of:

• Missing director credential documents

• Incomplete PT enrollment

• Fee processing delays

• Manual review by state agency staff

• Seasonal backlogs (e.g., January is notoriously slow)

Once all these pieces are checked and validated, CMS issues the Certificate of Registration (CoR), which allows the lab to begin moderate- and high-complexity testing.

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AMA Opens Registration for Palm Springs CPT Meeting (February 5-7, 2026, Grand Hyatt)

AMA has opened registration for the February 5-7, 2026, CPT Editorial Panel meeting in Palm Springs, CA.   The location is the Indian Wells Grand Hyatt.   In-person attendance is capped at 500 people.  (Overflow by Zoom.)

Average temperatures in February are 75 day, 50 night.

https://www.ama-assn.org/member-benefits/events/cpt-editorial-panel-meeting

Pathology CPT applications will be posted by AMA on November 15, and any comments must be submitted by December 1.  

Agendas for other medical topics will be posted by AMA on December 5.

AI Chat GPT 5 Explores the Rules for CAP's Distributive Testing CLIA Model

I've heard for a number of years that CAP allows "distributive testing" of parts of one  complex test when two labs formally collaborate.  

• For example, a CLIA lab in Chicago might do sequencing and a CLIA lab in St Louis might do bioinformatics.  (They are mutually responsible for quality assurance, etc.)

I've also heard, informally, that distributive testing might raise eyebrows with the AMA PLA code committee.  I've never seen that myself.

I asked Chat GPT 5 to research this and get back to me.   Note, I am not an expert in this area, so I would use this information below only as a launch pad for my own research, I'd need to check the links carefully, etc.  Note that the results include a website that uses the term "dry lab" to refer to a bioinformatics lab.

Quiz:

• Would I take the AI essay below as fact, like a textbook?  
• NO!
• Would the organized and hotlinked info below speed me up to use this and its links as a starting point?  
• Yes.

John Oliver Does Not Like Medicare Advantage

 John Oliver turns his attention to Medicare Advantage in a recent episode.

I know what I think, so I asked Chat GPT 5 what it thought of the episode.

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AI CORNER

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Setting the stage

In an October 2025 episode of Last Week Tonight, John Oliver focused on Medicare Advantage (MA)—the privately administered alternative to traditional Medicare. The segment critiques how MA is marketed and how it operates, especially with respect to taxpayer costs, beneficiary experience, and provider burdens. The framing resonates with professionals across health systems, hospitals, and molecular laboratories who routinely navigate payor friction, narrow readings of LCDs, and time-consuming prior authorization requirements.

Hot News: AMA Moving PLA Applications to the Main CPT Application Portal

Here's an exciting email from AMA CPT, arriving on November 12, 2025.  Effective in December, PLA code applications will be handled through the main CPT application portal, called "CPT Smart App."  Previously, PLA applications went through an abbreviated special portal of their own.

If you need to make a copy of your prior PLA submissions on the old portal, it will remain "up" as an archive til January 12.   

Here's the mass emailing from AMA CPT.  Note that there is also a worthwhile FAQ (for example, stating that the diminuitive list of PLA questions will stay the same).

Amal Thommil / DeciBio / Updates Us on Reimbursement for MRD

 Amal Thommil, Senior Research Associate at DeciBio, regularly updates us on coverage for minimal residual disease testing.  Each updates expands either tumor type (like "breast cancer") or application (like "checkpoint therapy monitoring.")   Each time, we see the centrality of coverage determinations at the CMS MolDx program, which sets coverage for both fee for service Medicare and Medicare Advantage.

Here's his most recent chart:

https://www.linkedin.com/feed/update/urn:li:activity:7393750080786395136/

click to enlarge

Center for Medicare Innovation: Warshawsky at AEI Proposes Reforms

Tag line: Can the long-maligned CMMI redeem itself under Trump? Warshawsky argues that only mandatory models and smart use of AI can finally deliver real savings.

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The Center for Innovation (CMMI) at CMS has been kicked around ever since it was created by the Affordable Care Act in 2010.   It has the authority to waive any section of Medicare law for the purpose of running a demonstration or model - and there is no explicit limit on how big or how long such a demonstration can be.   

The current head of CMMI is Abe Sutton, who worked at McKinsey, had some accomplishments in the Trump I administration, and snuck in a law degree at Harvard during the four Biden years.

I track articles on how to improve CMMI, and I may be a little jaded on the topic.  But this week, I found one that turned out to be quite interesting and insightful.  The author is Mark Warshawsky of the American Enterprise Institute.

Find the whole AEI article here:

https://www.aei.org/articles/another-obamacare-failure-will-trump-fix-the-center-for-medicare-and-medicaid-innovation/

I disagree with one general point of his - "eliminate reimbursement of AI."  His point is, he wants hospitals directed to use of AI to reduce health system costs, rather than focus on AI they would get paid for.   But creation of some products and I.P. in AI will surely require investment and funding. He quotes and tracks back to a 2022 article on paying for AI, by Parikh and Heimchen, which has been cited 90 times.

Basically, I think he could retitle CMMI as CMPE, "The Center for Medicare Productivity and Efficiency."

Below, a short AI summary.  

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AI CORNER

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Has Artificial Intelligence Arrived at Clinical Hematology? The Case of AML.

Artificial intelligence has arrived at the hematology clinic?

A new review in JAMA Oncology (Ansarian et al., 2025) surveys how AI systems are being woven into the management of acute myeloid leukemia (AML)—from image-based diagnosis to genomic risk modeling. 

The numbers are striking—up to AUROC 0.97 for AML detection and >99% accuracy for transcriptome classification.  But the authors also indicate that these tools are beginning to mimic clinical reasoning, by linking bone-marrow morphology with genetic signatures such as NPM1 status. 

The authors also highlight the growing role of federated learning, which lets hospitals train shared models without sharing patient data—an advance that could democratize access to high-performance AI even in resource-limited settings. Below is the abstract of Ansarian et al, positioning AML as a proving ground for AI in the cancer clinic.

### ABSTRACT

Acute myeloid leukemia (AML) is a severe hematologic cancer with complex genetic heterogeneity necessitating personalized treatment approaches. Artificial intelligence (AI) technologies may revolutionize risk stratification, diagnosis enhancement, and treatment planning in addressing critical gaps in AML management, particularly in low-resource health care environments.

Observations  This narrative review synthesizes existing AI applications in 3 primary areas of AML management. 

1. Machine learning algorithms integrating clinical, cytogenetic, and molecular data demonstrate greater prognostic accuracy than conventional European LeukemiaNet (ELN) guidelines. 
2. Deep learning approaches to image analysis yield excellent results for AML subtype identification from bone marrow smears (area under the receiver operating characteristic curve [AUROC]: 0.97) and genetic variant prediction (eg, NPM1 status [AUROC: 0.92]). 
3. AI-driven genomic analysis reveals novel prognostic signatures and therapeutic targets through advanced pattern recognition, with high-dimensional machine learning achieving greater than 99% accuracy in AML classification from transcriptomic data. 

Federated learning approaches enable multi-institutional collaboration with 96.5% accuracy in leukemia classification on heterogeneous datasets.

Conclusions and Relevance  AI technologies hold potential to improve AML treatment through enhanced risk stratification, early detection capabilities, and individualized treatment optimization.

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AI CORNER
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Chat GPT 5 writes,

• The review makes a persuasive case that AI could one day unify genomic, morphologic, and clinical data into a single risk framework for AML—but it also reveals how far the field still has to go.

Most cited studies remain retrospective, often trained on small or single-institution datasets, with limited external validation and uncertain generalizability across patient populations. Reported accuracies above 95% may partly reflect closed research settings rather than real-world complexity, where staining variation, scanner differences, and incomplete data routinely confound algorithms. Even the most “explainable” models still need prospective trials, workflow integration, and regulatory clarity before they can influence treatment decisions.

The technology’s direction is unmistakable—but don't overlook the gap between high-performance prototypes and practical, reproducible clinical tools. In that sense, this review captures a turning point for today: AI in leukemia care is not yet routine medicine—but it is no longer mere speculation either.

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See a DRAFT article where AI compares ANSARIAN (above) directly to a new paper on multi-modality in oncology by DELLAMONICA - here.

Podcast: MedTech Talk. Valuation bubble; Reimbursement challenges.

Recently I ran across the podcast, MEDTECH TALK, and I'll mention a few that caught my attention.  (I'm citing a couple from 2023, 2024, but the channel has podcasts right to October 2025).

Find the home page here:

https://medtechmvp.com/media/medtech-talk-podcast

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Hear about the career path and priorities of Liz Kwo MD MBA, who is now Chief Commercial Officer of Everly Health.   July 2024.  Find it here. #189.

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There was a huge valuation bubble in biotech, genomics, etc, during 2020/2021.   In this podcast, recorded in July 2023, a panel looks back on the very recent bubble, and predicts the next year.   Find it here. #179.

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Justin Klein, an MD JD who went straight into venture capital, discusses his career and priorities, also from 2023.  The focus is "the Medtech Ecosystem," how important it is.  There's a substantial section about "reimbursement" as being an opaque unpredictable barrier, a weak link in that ecosystem.  (Around minute 20.-30)  Find it here.  #182.  (See similar reimbursement points at Linked In here.)

• See an extract (summary + transcript) from the Klein interview re: reimbursement:
• https://bqwebpage.blogspot.com/2025/11/jordan-klein-md-phd-medtech-talk.html

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Valuation bubble.  Biodesix (genomic testing) IPO at $250, peak $480, rapid decline over 90% to $30 and under ($6 today).   Many diverse genomic companies had 2020/2021 valuation spikes, even if they had no connection to Covid testing or therapies.  Invitae rapidly went from $15 to $50 to $15 to 0.

CAP's Newest Podcast - CIPI Council on Informatics and Pathology innovation

 CAP launches a new podcast, CIPI CONNECTIONS.
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CIPI Cup

One of the several Councils of the College of American Pathologists (CAP) is CIPI - The College on Informatics and Pathology Innovation.   Home page here.  They have five committees:

• Artificial Intelligence
• Cancer
• Digital and Computational Pathology
• Informatics 
• Pathology Electronic Reporting (PERT0

The CIPI podcast is subtitled, 'Insights, Updates, and the People Behind the Innovation."

Find a podcast hosting page here;

https://podcast.ausha.co/cipi-connections/insights-updates-and-the-people-behind-the-innovation

Find the "debut episode" August 8, 13 minutes.  The link, above, also offers a transcript. Here's the tag line:

• Welcome to the debut episode of CIPI Connections, the official podcast of the College of American Pathologists' Council on Informatics and Pathology Innovation (CIPI). Co-hosts Dr. Giovanni Lujan and Dr. M.E. de Baca introduce the podcast’s mission and discuss Dr. de Baca’s inspiring journey from ophthalmology in Germany to leading innovation in pathology. Learn how CIPI and its five committees are shaping the future of digital pathology, AI, cancer reporting, and more—and what listeners can expect from future episodes.

See also a listing of "CAP Podcasts" which includes CIPI Connections and a new series under the banner, "Horror Stories in Pathology Informatics."

Here's an entry point from the CAP / Publications / Podcasts index page:

https://www.cap.org/member-resources/podcasts

https://www.cap.org/member-resources/podcasts/cipi-connections-pathology-meets-ai-translating-ai-frameworks-into-practice

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AI CORNER

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Here are AI summaries of two recent podcasts.

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CIPI Connections Podcast 1 — “Pathology Meets Artificial Intelligence”

This episode of CIPI Connections from the College of American Pathologists explores how existing laboratory validation frameworks can guide the safe implementation of artificial intelligence in pathology. Hosted by Dr. M.E. de Baca, the discussion features Drs. Matthew Hanna, Nick Spies, and Larissa Furtado from the CAP AI Committee, who examine parallels between AI model validation and familiar laboratory processes such as immunostain verification and molecular assay quality control. They emphasize that AI should be treated as another diagnostic test, requiring analytical and clinical validation, documentation, and continuous performance monitoring. The speakers identify gaps in current CAP checklists—particularly around data quality, explainability, and model updating—and highlight the emerging role of AI implementation specialists to ensure safe, effective deployment. Their consensus: existing laboratory rigor provides a strong foundation for AI adoption, but evolving guidance and education will be essential to maintain patient safety and trust as laboratories integrate machine learning tools into clinical workflows.

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CIPI Connections Podcast 2 — “Horror Stories in Pathology Informatics: Unflagged and Overlooked”

In this inaugural episode of the Horror Stories in Pathology Informatics series, Drs. Alexis Carter and Omar Baba dissect a real-world case involving a missed low cortisol result that went unflagged in an electronic health record, delaying diagnosis of adrenal insufficiency. The case—stripped of identifiers but based on actual events—illustrates how informatics design decisions can compromise patient safety. Because cortisol has time-dependent reference ranges, the lab displayed both ranges in a free-text comment, preventing the system from automatically flagging the abnormal value. The physicians discuss how structured data fields, discrete order codes for morning and afternoon tests, or “ask-on-order-entry” prompts could have prevented the oversight. They also caution against overreliance on visual flags as shortcuts for reviewing lab results, emphasizing the need for clinician education, structured data standards, and interdepartmental communication. The episode concludes with practical takeaways: build structured informatics solutions wherever possible, ensure reference ranges are machine-readable, and reinforce the clinician’s responsibility to review all results—not just those flagged as abnormal.

CMS Releases PFS Final Rule Despite Shut-Down. OPPS Final Rule Pending.

Each fall, CMS normally releasing the final PFS rule and final OPPS rule on November 1, giving them 60 days to take effect (January 1).   CMS got the CY2026 PFS rule out the door on Friday October 31.  The OPPS rule isn't out yet.

See the PFS press release here - "CMS Modernizes Payment Accuracy."  

The main headline is a 2.5% cut in reimbursement for surgical and similar services that CMS believes have "become more efficient."  Stakeholders argued the opposite, that patients had become more complex (a greater and greater percent are over 70).  See MedPage Today here.

• This cut continues an effort, which finally bloomed after years of debate, of shifting some dollars from specialists to primary care.  A couple years ago CMS introduced a G-code which adds about $16 to primary care visits, a perturbation that decreased RVUs for non-E&M visits.  In an effort to increase the number of Infectious Disease doctors, CMS also introduced some special coding for them a couple years ago.

See the PFS Fact Sheet here, which is more detailed and granular than the press release.

CMS notes that much of its practice expense information dates to 2008, but declines to accept a 2014 update from an AMA survery.

CMS may expand its method of using Medicare hospital outpatient rates as a proxy for office-setting rates.   Otherwise, CMS uses an extremely detailed accounting method with pennies and dollars for supplies, capital equipment, staff time, physician time, overhead, and other factors.  

While a telemedicine "cliff" is still in the air, as COVID legislation expires, CMS continues to tweak with rules for virtual services which do exist, such as "virtual direct supervision" rather than "present in the office suite" supervision, for some incident-to services.

Responses to public comments solicited for "software as a service" (in general) at page 447ff, merely remarkng that "comments were appreciated."

The Fed Reg publication will be Wednesday November 5.  90FR49266.  Even in print, it's still 1216 pages.

https://www.govinfo.gov/content/pkg/FR-2025-11-05/pdf/2025-19787.pdf

  A typescript copy is available here (2375pp!)

PLA Codes at Novitas: Vastly Less Controlled than at MolDx

The Novitas MAC seems to go through one payment disaster after another, with notoriously high and bizarre-looking payments for 81408 (rare gene, full sequence) and adjacent codes in 2019-2021.  The OIG's report cited a "billion dollars" in misspending.   Now, in 2023, 2024, the Novitas cash seems to be directed to some otherwise rare gene panels (e.g. for mitochondrial disorders, or for inherited diseases of childhood like cystic fibrosis), and also for code 87798, a microbiology code that is uncontrolled at Novitas.  (See also blog.)

Rare Gene Panels (81419, 81430, 81433, etc); 87798 

The typical labs billing for these in the US are in Texas or Florida, and they recently obtained NPI numbers as LLCs.   The same codes (81408; the rare-gene panels; 87798) are very rarely billed to Medicare by labs like LabCorp, GeneDx, Ambry, Quest, etc.  

In each case, billing in Texas and Florida (but not elsewere) exploded such as multiples of 100X over a couple years.

Novitas and PLA Codes - Striking Lack of Controls Compared to MolDx

I looked at 2023 billing to Medicare Part B for all "U" codes - the PLA codes.  Total billing was $519M.  The distribution was 64% MolDx, 14% Novitas, and 22% NGS MAC.  

However, had NGS MAC not been paying for FMI codes which are under an NCD (0037U, 0239U), NGS MAC PLA payments would drop to just $36M or 7% of national.

In each case, the PLA codes were highly concentrated, with 90% to 97% of PLA payments to the top 10 providers in each MAC system.  (And, as shown below, most PLA payments went to the top 3-4 codes).

• We noticed something strange when we looked up each PLA code in the Medicare Coverage Database.  
• All of the top 10 PLA codes at MolDx fall under NCDs or LCDs.  
• In the Novitas MAC, I could identify only 2 of 10 PLA codes that fell under an LCD or NCD, using the same Medicare Coverage Database.

In both Novitas and NGS MAC, many of the payments (not under LCDs) were for 0240U, 0241U, microbiology codes.  Although MolDx had 64% of all PLA payments, none of the top 10 at MolDx were microbiology codes.

Caveats

• This is first-pass work; I haven't double checked everything or had anyone replicate it.  
• We compare 2023 payments to current 2025 policies.  
• I entered CPT codes one by one in the Medicare Coverage Database and took the result.

Click to enlarge. MAC index = 1, MolDx, 2, NOV/FCSO, 3, NGS MAC.

click to enlarge

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The CMS cloud database is here.  It has all 2023 Part B claims.  You can filter for codes ending in "U" = PLA codes.