Wednesday, October 14, 2026

Handy Reference: AMA, ASCO, CAP Positions on the Awful 14-Day Rule

The 14-day rule or Date of Service rule is generally unpopular with oncologists and cancer patients and societies.   Here are some recent (2024) positions from ASCO, AMA, CAP.

The topic is found on page 22 of a 40 page summary document from AMA.

The topic is also found on pages 136-137 of the longer meeting handbook.

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2024 AMA Governing Council Report (40pp)

https://www.ama-assn.org/system/files/i24-omss-report-a.pdf

See page 22 of 40 (aka Item 18).


RESOLVED, that our American Medical Association actively lobby the federal government to readdress and change laboratory date of service rules under Medicare, e.g. the Medicare 14-Day Laboratory Date of Service Rule (Medicare 14-Day Rule), such that complex laboratory services performed on pathologic specimens collected from an inpatient hospital procedure be paid separately from inpatient bundled payments, consistent with Outpatient rules. (Directive to Take Action). 

Note this is for inpatients, as the outpatient rule as fixed in 2017.

Note the main sponsor was, ASCO.

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2024 Minutes of Reference Committee B (142pp)


See pages 136-137 (as item 225).

Opening:


2024 CAP Policy Update   11-14-2024


Elimination of Medicare 14-Day Rule

The CAP supported a resolution asking the AMA to actively lobby the federal government to readdress and change laboratory date of service rules under Medicare, eg the Medicare 14-Day Laboratory Date of Service Rule, such that complex laboratory services performed on pathologic specimens collected from an inpatient hospital procedure be paid separately from inpatient bundled payments, consistent with outpatient rules.

The CAP appreciates the improvements to Medicare’s laboratory DOS policy to date. However, these improvements did not address hospital inpatients and payment for some tests is still problematic. Regardless of the place of service, a revised DOS policy that allows the performing laboratory to bill directly for molecular pathology tests and ADLTs, rather than receiving payment from the hospital, would reduce administrative/billing complexity for hospitals, clinical laboratories, treating physicians and Medicare beneficiaries, and promote timely access to patient testing.

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Full text of Minutes, Committee B, Item 225 (seen above) p 136-137

Whereas, our American Medical Association adopted D-330.903 at I-17, which asks our AMA “actively lobby the federal government to change laboratory Date of Service rules under Medicare such that complex diagnostic laboratory services performed on pathologic specimens collected from a hospital procedure be paid separately from inpatient and outpatient bundled payments”; and

Whereas, AMA advocacy on the CY 2018 Medicare Outpatient Prospective Payment System Rule was successful in getting complex molecular testing unbundled from outpatient diagnostic procedures – such as outpatient interventional radiology biopsies; and

Whereas, the Medicare 14-Day Laboratory Date of Service Rule (Medicare 14-Day Rule) provides billing requirements for diagnostic tests ordered for Medicare patients and determines whether the clinical laboratory performing the tests will directly bill Medicare or bill the hospital where the specimen was collected; and

Whereas, the Medicare 14-Day Rule was not changed for specimens collected during an inpatient encounter, with complex molecular tests ordered within 14 days of hospital discharge continuing to be bundled into inpatient Medicare payments; and

Whereas, performing complex molecular tests on inpatient samples parallel the criteria established for unbundling testing of outpatient samples: including it being medically appropriate to have been collected during the hospital inpatient encounter, the results of the test not guiding treatment during the hospital inpatient encounter, and the test being reasonable and medically necessary for the treatment of an illness; and

Whereas, the real-world effect of an inpatient Medicare 14-Day Rule is to routinely delay the initiation, until 14 days after discharge, of complex molecular tests on pathologic samples collected during an acute hospitalization, such as cytology from an inpatient thoracentesis for a new diagnosis of lung cancer; and

Whereas, diagnostic delay of pivotal molecular data due to the inpatient Medicare 14-Day Rule causes harm to patients, such as forcing an initial round of an inferior cytotoxic chemotherapy on newly diagnosed lung cancer patients while awaiting candidacy for a more efficacious targeted agent; therefore be it

RESOLVED, that our American Medical Association actively lobby the federal government to readdress and change laboratory date of service rules under Medicare, e.g. the Medicare 14-Day Laboratory Date of Service Rule (Medicare 14-Day Rule), such that complex laboratory services performed on pathologic specimens collected from an inpatient hospital procedure be paid separately from inpatient bundled payments, consistent with Outpatient rules. (Directive to Take Action).

 

Fiscal Note: Modest – between $1,000 - $5,000 

Received: 9/24/2024 

 

REFERENCES 

1.   American Medical Association. Follow-Up on Implementation of Resolutions and Report Recommendations, AMA House of 

Delegates Interim Meeting - November 8-11, 2017. https://www.ama-assn.org/system/files/2018-11/i17-followup-status-
report_0.pdf   

2.   Centers for Medicare & Medicaid Services. Laboratory Date of Service Policy. https://www.cms.gov/medicare/payment/fee- schedules/clinical-laboratory-fee-schedule-clfs/date-service-policy    

3.   Foundation Medicine. 14-Day Rule Billing Requirements for Foundation Medicine Tests. 
https://www.foundationmedicine.com/sites/default/files/media/documents/2024-
08/14%20Day%20Medicaid%20Rule_One%20Pager_LaboratoryDateOfService_June%202024_US-PF-2200092_R4.pdf   

 

RELEVANT AMA POLICY 

Elimination of Laboratory 14-Day Rules Under Medicare D-330.903 

Our AMA will actively lobby the federal government to change laboratory Date of Service rules under 
Medicare such that complex diagnostic laboratory services performed on pathologic specimens collected  from a hospital procedure be paid separately from inpatient and outpatient bundled payments



Tuesday, October 13, 2026

Agilent to acquire Proscia; Business Strategies in Digital Pathology

 In headline news today, Agilent (market cap $50B) will acquire Proscia in a deal for $240M in cash.  See news below.

I've had a number of blogs recently on strategies in digital pathology.   Here's a lookback to a white paper I wrote in May 2026 comparing the digital pathology business strategies of Philips and Roche.   It comprises two deep-dive reports by AI, one by Claude and one by Chat GPT.  Find it here:

https://www.discoveriesinhealthpolicy.com/2026/05/can-ai-write-deep-strategic-business.html

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Guest Author: Chat GPT looks into the deal for us.

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Agilent’s $240 Million Proscia Deal:
Buying a Larger Role in Digital Pathology

Agilent’s planned acquisition of Proscia illustrates a broader contest in cancer diagnostics: who will supply the software connecting laboratory instruments, tissue images, and artificial intelligence? On October 13, 2026, Agilent announced an agreement to buy the digital pathology company for $240 million in cash, plus up to $30 million in performance milestones. Closing is expected early in Agilent’s fiscal 2027. Announcement here.

Agilent is a global supplier of laboratory instruments, reagents, software, and services, with fiscal 2025 revenue of $6.95 billion. Its pathology business includes Dako, the cancer diagnostics company acquired in 2012, and Biocare Medical, whose acquisition closed in June 2026. These businesses supply staining instruments and reagents that help laboratories identify biological markers in tissue. Proscia would extend that presence further into the digital work performed after slides are prepared.  Agilent has already had a cooperative alliance with Proscia.

Philadelphia-based Proscia develops and supplies "Concentriq," a software platform for managing, viewing, and analyzing digitized pathology images. Scanners create the images; Concentriq connects them with laboratory systems, pathologists, and AI applications. According to Agilent, by means of Concentriq software, Proscia serves more than 4,000 laboratories, hospitals, and clinics, plus 16 of the 20 largest pharmaceutical companies. Its trailing annual revenue exceeded $18 million. The companies have already worked together under a distribution agreement dating to 2022.  That distribution channel is now tightened into an acquisition. 

The strategic logic is straightforward. Owning software used throughout a laboratory’s daily work could deepen Agilent’s customer relationships, generate recurring revenue, and create additional opportunities in pharmaceutical research and companion diagnostics. A platform connecting tissue preparation with image interpretation could also make it easier to develop and deploy quantitative biomarker tests. These are business opportunities, however, rather than demonstrated financial benefits of the acquisition.

The price reflects substantial expectations. Using $18 million as a reference, the upfront payment represents approximately 13.3 times annual sales; the actual multiple is lower because reported revenue exceeds that figure. Agilent describes Proscia as a growing, high-margin software business but provides no numerical growth, margin, or earnings targets in the announcement. Buyers are therefore being asked to assess the strategic potential with limited financial detail.

For Leica Biosystems, part of Danaher, the implications include both competition and cooperation. Proscia’s August 2026 FDA clearance included compatibility with Leica’s Aperio GT 450 DX scanner. Agilent could consequently gain software revenue from laboratories using Leica hardware. That makes preserving interoperability commercially important: supporting competing instruments can expand the software’s market. Roche likewise supports third-party algorithms through its Digital Pathology Open Environment, demonstrating that these competitive boundaries already overlap.

Tempus offers another comparison. The precision-medicine and AI company acquired Paige in August 2025, emphasizing its pathology images, technical expertise, and AI capabilities. Strategically, Tempus approached pathology from data and computational medicine; Agilent approaches it from laboratory infrastructure and diagnostics. Both transactions suggest that pathology software is becoming an important component of larger healthcare businesses.

For independent AI developers, larger platforms could offer broader distribution while gaining greater influence over commercial terms and customer access. (Compare: Cerner/Epic in EHRs).  

 For laboratories, the practical questions remain concrete: Will integration become easier? Will pathologists save time? Will new capabilities justify their cost? Agilent’s investment strengthens its ability to compete for that business; execution will determine the return.

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What's Interesting or Surprising about Agilent-Proscia?

  1. Agilent is paying for a strategic position well ahead of current revenue. Proscia generates just over $18 million annually; the $240 million upfront price implies roughly 13 times sales, using $18 million as the reference. That revenue is only about 0.3% of Agilent’s annual revenue. The investment’s importance lies in what Proscia could enable across Agilent’s business. www.agilent.com

  2. The central asset is the software pathologists work in—not simply an AI algorithm. Concentriq connects images, laboratory systems, people, and analytical applications. Strategically, owning that daily workspace could give Agilent influence over how numerous AI products reach customers. Its distribution relationship with Proscia since 2022 also means this follows several years of commercial experience together. www.agilent.com

  3. Agilent could benefit when a laboratory buys a competitor’s scanner. Proscia’s FDA-cleared platform supports Leica’s Aperio GT 450 DX. That creates an unusual competitive relationship: Leica supplies the scanning hardware, while Agilent could supply the software used with its images. Preserving compatibility with rival equipment therefore has direct commercial value. www.globenewswire.com

  4. The pharmaceutical footprint is striking for such a small company. Proscia serves 16 of the top 20 pharmaceutical companies, according to the announcement. That gives Agilent an established software presence in drug-development organizations—potentially valuable for biomarker research and companion diagnostics. However, customer reach alone does not reveal contract size or depth of adoption. www.agilent.com

  5. The deal follows a much larger move by Roche into the same territory. Roche announced its PathAI acquisition in May for $750 million upfront, potentially $1.05 billion. Alongside Tempus–Paige, these transactions suggest a shift toward pathology software being owned by larger diagnostics and data businesses. An important strategic question is how those platforms will balance their parent companies’ priorities with the openness customers and independent AI developers value. www.roche.com


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Review of Deals


The Broader Picture: Eight Major Deals and Financings in Digital Pathology

Agilent’s purchase of Proscia joins a substantial wave of acquisitions, investment, and consolidation. Eight notable transactions from 2025–2026 illustrate how laboratory manufacturers, software companies, and investors are positioning themselves:

  • Agilent–Proscia: $240 million, plus up to $30 million in milestones. Announced October 13, 2026. Agilent agreed to acquire Proscia, the company that makes Concentriq, adding digital pathology software to its tissue-diagnostics portfolio. Announcement.

  • Roche–PathAI: $750 million upfront, potentially $1.05 billion. Announced May 7, 2026. Roche agreed to acquire PathAI, including its AISight image-management software, AI capabilities, and pharmaceutical research services. This would deepen Roche’s presence across laboratory workflow and computational diagnostics. Announcement.

  • Agilent–Biocare Medical: $950 million. Announced March 2026 and completed in June. This is an adjacent tissue-pathology acquisition: Biocare supplies staining instruments, antibodies, and reagents. Together, Biocare and Proscia would expand Agilent’s presence from slide preparation through digital review. Announcement; completion.

  • Grundium–Visiopharm: price undisclosed. Announced May 21, 2026. Finnish scanner manufacturer Grundium acquired Danish pathology AI and image-analysis company Visiopharm, combining slide digitization with quantitative tissue analysis and biomarker applications. Announcement.

  • Tempus–Paige: $81.25 million, predominantly in stock, plus assumed cloud commitments. Announced August 22, 2025. Tempus acquired Paige’s pathology AI technology and expertise, alongside a dataset of nearly seven million digitized slides with associated information. Announcement.

  • Evident–Pramana: price undisclosed. Completed August 27, 2025. Evident, the former Olympus microscopy business, acquired Pramana’s autonomous slide-scanning technology, strengthening its capabilities in automated image acquisition and quality control. Announcement.

  • Waiv, formerly Owkin Dx: $35 million Series A. Final closing announced April 24, 2026. Investors backed development and commercialization of AI-based oncology tests, including applications extracting biomarker and prognostic information from pathology images. Announcement.

  • Aiforia: €20 million venture-debt agreement. Announced July 31, 2026. European Investment Bank financing supports the Finnish pathology AI company’s product development and commercial expansion. Funding is available in tranches subject to milestones. Announcement.

The Latest Paige Development: Channel through Leica Aperio

On September 24, 2026, Leica Biosystems announced the addition of Tempus’s Paige PanCancer Detect and Paige Prostate products to its Aperio AI Store. PanCancer Detect identifies suspicious areas across more than 40 cancer types; the prostate suite supports detection, grading, quantification, and assessment of perineural invasion. The applications operate within Leica’s Aperio HALO AP software workflow, developed with Indica Labs. Leica announcement.

This is a useful example of cooperation across corporate boundaries: Tempus owns Paige, while Leica provides another distribution channel. But the announcement explicitly labels these offerings research use only, not for diagnostic or clinical use. It therefore illustrates both progress toward integrated pathology AI and the remaining distance to broadly deployable, FDA-authorized diagnostic and report-drafting systems.


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Review of Funding Events

These two funding deals bring the previous list to ten, and both fall within the past 12 months:

  • Waiv, formerly Owkin Dx — April 24, 2026: $35 million Series A financing. Initial investors OTB Ventures and Alpha Intelligence Capital were joined by CRB Health Tech and others. Waiv develops AI tests that extract biomarker and prognostic information from pathology images, including breast cancer risk assessment and colorectal cancer MSI screening. Funding supports development and commercial expansion. The $35 million is the completed round’s total, including its extension. Company announcement. waiv.com

  • Aiforia — July 31, 2026: €20 million venture-debt financing agreement with the European Investment Bank. The Finnish pathology AI company secured financing for image-analysis product development and international commercial expansion. This is debt financing, available in three tranches subject to revenue and other milestones, rather than a conventional VC equity round. EIB announcement. eib.org

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I've had multiple articles and white papers in recent months arguing that FDA-authorized (not locally RUO) draft reports will lead to explosive growth in digital pathology.   Apply this lens to Agilent.
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Quinn's Lens:
Agilent–Proscia and the Coming Market for AI-Drafted Pathology Reports

My bias is that FDA-authorized systems that analyze slides and prepare draft reports before the pathologist opens the case will blow the roof off digital pathology’s growth—and that this opportunity remains underappreciated. The compelling product is a substantially completed first pass: findings, measurements, supporting images, and a report ready for physician review. Agilent’s acquisition of Proscia deserves attention through that lens.

Radiology offers an early indication of the potential. DeepHealth’s FDA-cleared breast ultrasound application analyzes images and generates reports for physician review. The company reports a 37% reduction in interpretation time in its FDA-submitted reader study—close to 40%. That is a result for a defined examination and study setting, rather than a reduction in the radiologist’s entire workday, but its commercial significance is considerable. DeepHealth announcement.

FDA is also investing in the methods needed to evaluate these products. A $1.29 million research contract awarded to Cognita Imaging will test approaches to evaluating AI-generated radiology reports across approximately one million examinations, with radiologists reviewing important discrepancies. This is regulatory-science research, not authorization of a product, but it addresses an essential bottleneck: how to assess the quality of an entire generated report at scale. Contract announcement.

Where does Agilent fit? Its proposed $240 million purchase of Proscia, plus potential milestones, combines a large diagnostics manufacturer with software positioned inside the pathologist’s workflow. Agilent brings laboratory relationships, tissue-diagnostics products, and experience commercializing regulated tests. Proscia brings the infrastructure connecting slides, case information, analytical applications, and the physician’s workstation. The strategic inference is that this combination could support development and distribution of a report-drafting product. Acquisition announcement.

Proscia’s recent product descriptions make that possibility concrete. Its fifth-generation Concentriq architecture connects images with clinical context, runs relevant analyses automatically, and prepares work for the expert. Its launch announcement describes assembling reportable findings for pathologist confirmation. Those capabilities are relevant building blocks for a case that arrives already analyzed and partially documented. Proscia’s architecture explanation.

The regulatory gap is equally revealing. Proscia explicitly distinguishes these research-use-only capabilities from Concentriq AP-Dx, its separate FDA-cleared product for primary diagnosis. Clearance of the viewer does not authorize every AI application operating within it. The public materials reviewed do not establish an FDA-authorized comprehensive draft-report system, and Agilent’s announcement makes no specific commitment to deliver one. Product-status disclosures.

This is where pathology’s dependence on RUO-based, locally assembled and validated solutions can impose a crippling scaling penalty on itself.   Dependence on RUO: it's not for nothing that we read of 1400 FDA radiology apps and 5 pathology ones (all else RUO.)

  • Each implementation can become another development project. A manufacturer-supported, FDA-authorized product could concentrate much of the evidence generation, maintenance, and change management centrally. Local implementation checks would remain—CAP still emphasizes validation of digital diagnostic workflows—but hospitals could adopt a defined product with established performance claims. CAP guidance.

The decisive commercial test would be net physician time saved while maintaining diagnostic quality, including time spent checking and correcting drafts. A convincing result could make digital adoption easier to justify from operating economics, even before considering separate AI reimbursement.

Agilent has acquired an opportunity to pursue that result. The milestone worth watching is a product label, clinical study, and everyday workflow demonstrating that a pathologist can open a prepared case and finish it substantially faster.

The Strange World of PAMA Neuro Test Pricing

Header.   For 24 neuro codes, most were PLA codes with no PAMA data.   For codes with PAMA data (e.g.  5,000 payments for generic ABeta 1-40 at various prices), median prices rose significantly (from $118 to $175).   Interestingly, raw PAMA data shows that dozens of labs often got over $200, even over $300, for these codes despite later CLFS prices of $118.

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I asked Chat GPT to look at CMS's current clinical lab fee schedule and pull out full text codes for dementia-related codes (A-Beta, Tau 217, etc.)   It found 24 rows of data.

I then asked Chat GPT to search the CMS PAMA Preliminary Median file and wherever it found a median (some are blank), to insert that in the table.  I then had it make ratios of "PAMA Median over Current CLFS" and plot the ratios (where possible) on a vetical bar chart.   Note the bar chart has bins 1 to 24, and the table in Excel also has ordinal rows 1 to 24 (right column G).  

Find the Excel data in Google Sheets here. Note there are several tabs.

This shows the full table but won't be legible (see Google Sheets)  "Down" price in pink box; "up" prices in green box. Again, quite a few are PLA codes with no PAMA data so those rows are ineligible for an up/down color.


not legible, see google sheets


Whereas many prices fall under PAMA, here in Neuro World, only one of 24 neuro codes fell and not by too  much (0035U prion, from $540 to $432, row 1.)  

Six of the codes rose between 1.2X and 1.8X, including 0443U, 82233, 82234, 83884,  84393, 84394.  Most of these rising prices were generic CPT codes like Beta amyloid 1-40 and Beta amyloid 1-42.  These were reported by dozens of TINS (101 TINS in the case of 84393 Tau phospho eg 217. 

Often, PLA codes had no reported PAMA data (blanks in the bar chart).     


I had Chat GPT go to the "raw PAMA data" (each reported code, price to the penny, and number of services) and make a bar chart of the price distribution for 82233 and 82234, which are Abeta 1-40, and 1-42.   These had CLFS prices of $118 (hard-won, since CMS attempted to price first at $18).   Prices go UP from $118 to $175 for each code (which had about 20 reporting labs). 
  
The CLFS price $118 is not a peak, and a lot of prices came in over $200 dollars.  But this makes sense because these codes were in gapfill (no national price) during the PAMA survey period of 1H2025.

Note that CMS calculates medians, so it doesn't matter how far to the left or right the data fall, only what is the 50th percentile price.   You could push the 82233 spike at $260 to $360 or $460 and it wouldn't affect the median of $175.   

It's interesting the distribution below is so diffuse and non-Gaussian. 



Another tidbit - the codes, generally for Alzheimer testing, WERE getting paid.  But the data represent for each, about 5,000 services, not many considering there may be over 10M dementia patients.   The 5000 services are a circa $1m market.

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Nerd note.  How-to.  For 82233, I went to raw PAMA data and pulled the rows for 82233, about 500 rows, into its own Excel.  I uploaded that simple excel to Chat GPT with this instruction:
  • "Please bin these PAMA prices and then make a bar chart where the number of ser vices reported at a price is the bar height.    We have done this before.   Bin the prices in $10 increments from $0 to $300.   The height of each bar will be the aggregated number of services for that bin.'


Monday, October 12, 2026

Using Radiology Business "AI" Section to Understand Trends in 2025-2026

 I pulled Radiology Business's own listing of 24 recent AI articles - what does it amount to?  Which way and why, are we running?

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Yes. Your document contains 24 articles: 20 from Radiology Business and four from Cardiovascular Business. I accessed the full text of 23. The BCRF venture-fund article repeatedly returned an access error, so I supplemented its available excerpts with BCRF’s original announcement.

Together, these September–October 2026 articles offer a useful picture of an industry entering commercial maturity. This is a qualitative industry synthesis, rather than a statistical meta-analysis: the collection mixes research reports, company announcements, executive interviews, and policy commentary.

My central interpretation is that radiology AI is becoming a competition over who can turn information into a reliable, economically sustainable clinical service. Algorithm performance remains necessary, but distribution, workflow, evidence, payment, and responsibility for follow-up increasingly determine commercial success.

Rapid Changes Expected for Breast Cancer Therapies; ADCs and More

 From Nature Med, Nat Rev Clin Oncol, and NEJM.

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These papers support a substantial opportunity for digital pathology manufacturers—but the opportunity is to predict benefit from a particular ADC in a particular clinical setting, not simply to measure its target more precisely. TROP2 computational pathology is an especially important example because subcellular localization may contain information that conventional expression scoring misses. However, the papers also explain why many successful ADCs will not require a target-expression companion diagnostic.

For a manufacturer anticipating FDA CDx approvals, the strongest strategy is to establish a reliable platform for drug-specific diagnostic claims, while developing the ability to incorporate spatial biology, payload sensitivity, and treatment history. The likely future is a portfolio of validated applications sharing infrastructure, rather than one universal “ADC response score.”

The three articles are reviews or perspectives, so the appropriate synthesis is a critical narrative review rather than a pooled statistical meta-analysis. The assessment below separates established clinical uses, investigational biomarkers, and commercial forecasts.

The three papers address complementary questions.

  1. Hurvitz explains the clinical demand: an expanding treatment menu is making selection and sequencing harder.

Katie Palmer's Radiology Articles at STAT: An 8-Article Review and Meta-Analysis

We previously used Chat GPT to assess a set of 5 "AI Reimbursement" articles from Katie Palmer at Stat Plus.  Here, we expand the approach to a larger set of 8 of her business strategy articles.

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The attachment contains eight substantive articles. Read together, they support a comprehensive review of radiology’s AI frontier—and of the commercial, clinical, and policy choices likely to confront digital pathology next. 2026 STAT 1013 Bigger Katie pal…

Radiology’s AI transformation is becoming a transformation of the diagnostic business itself. Across eight STAT articles published between December 2025 and October 2026, Katie Palmer follows developments that initially appear separate: report-generating foundation models, practice acquisitions, opportunistic screening, hospital prediction systems, Medicare payment changes, and consumer purchases of cancer-risk assessments. Together, they reveal an industry reorganizing around the ability to extract more information from existing clinical data—and to control the infrastructure through which that information reaches patients.

The familiar question, “Can AI interpret an image?” remains important. But Palmer’s reporting increasingly directs attention to another question: Who can turn that interpretation into a useful, sustainable clinical service?

Part 2 of 2: AI Is Amazed by the Novitas-FCSO "MAC LAB DOS" Educational Article

In Part 1, we learned that CMS had asked MACs to  produce a composite standard article that educates on the bizarre Lab Date of Service Rule (Lab DOS).  

The AI's did not care much for the MAC article, and tried drafting better ones on their own.

Here in Part 2, we learn Novitas-FCSO wrote its own article, and the AI reacted much more favorably.  See the results below. We see the reaction first, and then we see how CLAUDE wanted to collaborate with Novitas in fixing its own article.

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Verdict

The article for Novitas is a different kind of document from the Wellpoint consensus piece, and a much better one. Compared with Claude V2, it's a near peer that sets out to do a different job. V2 is an explanatory essay: it tells billing staff why the date matters and walks them through the reasoning. Hers is a contractor reference page, built from definitions, the regulation's conditions, and a lookup table. On structure and legal accuracy they clearly beats Wellpoint and is level with V2 on most points. They also gets three things right that V2 misses. But they have one real error in her table and two gaps that V2 doesn't have.

Part 1 of 2: MAC DOS Article: Two AIs Compete to Do Better (Than MACs)

Part 1 of 2:  The MAC DOS Article: Two AIs Compete to Do Better (Than MACs)

After hearing complaints that the Lab DOS rule should have uniform explanations and enforcement at all MACs, CMS asked the several MACs to produce a new education article on DOS.  (Novitas-FCSO wrote its own.)

Below, I show the MAC example (from Wellpoint).   

Then Chat GPT, and CLAUDE, produce their own articles, which took a minute or two.

Then Chat GPT, and CLAUDE, "critiqued' their own work and compared to Wellpoint.

Finally, Claude produced a second version of the article, hopefully taking the best of each prior attempt.

IN PART TWO: We pivot to a big surprise from Novitas.

Read this blog via its links:

PAMA and Codes for Exome, Genome, and "Rapid Genome"

 

PAMA 2027: Genome Prices Fall Below Exome—and Rapid Genome Codes Have Missing Data

CMS’s preliminary PAMA results point toward a notable reversal in genomic testing reimbursement: standard genome sequencing has a lower private-payor median than exome sequencing.

The broader genome assay currently receives higher Medicare payment. Under the new medians, genome sequencing would ultimately receive substantially less. However, Medicare’s annual reduction limit delays the payment crossover: genome remains more expensive in 2027, with the genome-exome price reversal  projected to begin in 2028.

Rapid and ultra-rapid genome sequencing present a different situation. Several established proprietary codes have current Medicare prices, but no private-payor medians in the preliminary workbook. A newly announced rapid genome code, effective January 2027, adds another pricing question. (It will enter pricing meetings in June 2027).

Article by Chat GPT.

Standard exome and genome: different reductions, reversed targets

The central comparison involves 81415, exome sequence analysis, and 81425, genome sequence analysis.

Mammography AI Sold Straight to Consumers! (Parallels in Labs?)

Everywell will be the agent for seeling Clairity Breast mammography software results to consumers, according to a press release.   

In the future, will patients be able to upload a pathology needle biopsy DICOM and VISA card and get AI assistance?  To be continued.

I'll clip the press release below.


https://radiologybusiness.com/topics/artificial-intelligence/health-and-wellness-company-begins-selling-mammography-ai-directly-consumers-249

Health and wellness company begins selling mammography AI
directly to consumers for $249

  • Marty Stempniak | October 09, 2026 | Radiology Business | Artificial Intelligence
  • A health and wellness company has begun selling a key mammography artificial intelligence solution directly to consumers. 

Austin, Texas-based Everlywell recently announced the nationwide rollout and commercial availability of Clairity Breast to its users. Founded in 2015, Everlywell sells lab testing kits and digital diagnostic solutions to patients, “transforming care” for some 60 million people. 

The company said it is now offering Clairity Breast for $249 a pop, allowing women to upload their mammogram to the platform. Authorized by the Food and Drug Administration in 2025, the solution predicts patients’ five-year risk of developing breast cancer based on a routine screening. 

PAMA and PAP Smears: Strange Goings-On


PAMA 2027: When More Cytology Work Brings Less Payment

Article by : Chat GPT

CMS’s preliminary laboratory pricing data for 2027 offer an unexpected lesson in cervical cytology reimbursement. Adding manual review to an automated Pap screening service could result in lower payment. Two conventional manual-screening codes, distinguished principally by reporting terminology, have dramatically different private-payor medians. Meanwhile, an unusual statutory payment floor prevents several low medians from becoming Medicare fees.

The findings illustrate why laboratory prices deserve examination both individually and in relation to neighboring codes.

Automated screening: the price relationship reverses!

CPT 88174 describes automated screening of a cervical or vaginal specimen prepared using an automated thin-layer method. 88175 adds manual rescreening or review. Both operate under physician supervision.

The current Medicare rates follow an intuitive relationship: the service incorporating additional manual work receives slightly more payment. The preliminary 2027 medians reverse that relationship.

CodeService, abbreviated2026 Medicare ratePreliminary 2027 medianChange from 2026
88174Automated screening$25.37$27.43+8.1%
88175Automated screening plus manual rescreening or review$26.61$24.86−6.6%

The additional manual review currently receives a $1.24 premium. Under the new medians, the more extensive service would receive $2.57 less.

This establishes a payment inversion, rather than demonstrating that either service becomes unprofitable. The data do not measure laboratory costs or margins. Nevertheless, the prospect of receiving less payment for the service with additional manual work is striking.  And 88175 is more commonly used than 88174.

These figures come from CMS’s preliminary weighted-median workbook, released September 21, 2026. They are preliminary medians, rather than final Medicare payment determinations. However, (1) both exceed the current Pap payment minimum of about $18, and (2) the decrease for 88175 is below the PAMA 15% annual reduction limit. So if CMS retains the medians, the reversal appears likely to carry into payment.

The two medians represent very different populations

The reporting data reveal a substantial imbalance.

Private-payor data before additional QC8817488175
Reporting entities, measured by TIN19480
Reporting laboratory NPIs20730
Reported test volume20,9563,711,248

The reported volume for 88175 is approximately 177 times greater. These are private-payor tests submitted for PAMA pricing. They are not Medicare claim counts, Medicare expenditures, or estimates of all Pap testing nationwide.

The difference does not establish that either median is wrong. It does show that the two prices arise from substantially different reporting populations. Laboratories, payer contracts, negotiated discounts, and volume distributions could differ between those populations. The summary tables cannot establish which factors produced the reversal.

PAMA calculates a volume-weighted median independently for each code. That process can produce a valid median for each submitted distribution without preserving the expected price relationship between related services. A private-payor median also does not establish the resources required to perform the service.

CMS Quality Control does not resolve the inversion

CMS published medians calculated before and after additional "quality-control exclusions."  These are meant to remove duplicate reports from the same TIN/NPI and erase bizarrely high values (100X price).  The change in PAMA median is usually 0 or a few pennies.  Neither median changes: 88174 remains $27.43, and 88175 remains $24.86.

For 88175, the reporting-TIN count falls from 480 to 479 after QC, but its median again stays the same. The reversal therefore survives the additional data cleaning.

A related screening code, G0145, illustrates how small the QC effect can be. Its median changes from $22.84 to $22.79, a five-cent difference downward. Compared with its 2026 Medicare rate of $26.49, the adjusted median is $3.70 lower, or approximately 14%.

Manual screening introduces further surprises!

The manual-screening codes broaden the story beyond a single automated pair.

CodeService, abbreviated2026 Medicare ratePreliminary 2027 medianChange from 2026
88142Liquid-based preparation, manual screening$20.26$20.260%
88143Liquid-based preparation, manual screening and rescreening$23.04$30.00+30.2%
88150Conventional smear, manual screening$18.54$29.55+59.4%
88164Conventional smear, manual screening, Bethesda reporting$18.54$10.72−42.2%

These percentages compare preliminary medians with current Medicare rates. They are not necessarily the payment changes Medicare will implement.  Note that $10.72 is below the $18.54 legal floor so $18.54 would be used.  (See below)

Holding the liquid-based preparation method constant provides another revealing comparison. Manual screening and rescreening, 88143, currently receives less than automated screening with manual review, 88175: $23.04 versus $26.61. Their preliminary medians reverse that relationship to $30.00 versus $24.86.

The reporting populations differ here as well. The 88143 median rests on 2,880 reported tests from 15 TINs, compared with 3.7 million tests from 480 TINs for 88175.

Bethesda reporting: a large price drop for comparable screening work

The conventional-smear comparison is particularly curious. 88150 and 88164 currently receive the same Medicare payment—$18.54—yet their new PAMA medians differ by $18.83.

Both describe manual screening. The distinguishing feature is principally the reporting system. Bethesda standardizes terminology and specimen-adequacy reporting; it does not substitute a fundamentally cheaper screening technology. Separate Bethesda reporting codes are longstanding: AMA’s discussion of the 1999 CPT changes identifies the introduction of codes 88164–88167.

On the unadjusted medians alone (see below!), Bethesda reporting would have been associated with approximately 64% less payment than the neighboring manual-screening code.

That comparison comes with an important population qualification. The $29.55 median for 88150 rests on just 96 reported private-payor tests from nine TINs. The $10.72 median for 88164 rests on 942 tests from 39 TINs.

QC changes neither median.

The statutory minimum limits the disparity—but does not eliminate it

Pap smear laboratory tests have an unusual protection under Social Security Act §1833(h)(7). Congress established a $14.60 national minimum payment in 2000, with annual adjustments. The provision expressly applies notwithstanding §1834A, the PAMA pricing statute. Consequently, the minimum survives private-payor-based pricing.

The 2026 minimum is $18.54, following a 1.9% increase. CMS’s annual payment instructions explicitly include all the screening codes discussed above. The protection spans conventional and liquid-based preparations, manual and automated screening, and Bethesda reporting. Payment remains limited by the actual billed charge.

For 88174 and 88175, the floor appears unlikely to change the outcome because both medians exceed it comfortably. But for 88164, the statutory flow is decisive: the $10.72 median cannot simply become the Medicare fee. Since the code already pays at the floor, its sharply lower median need not produce an actual payment reduction.

Other codes illustrate the same protection. 88148, automated screening with manual rescreening of conventional smears, has a preliminary median of $5.28. P3000, screening Pap smears by a technician under physician supervision, has a median of $7.94. Both currently pay $18.54 and appear on CMS’s minimum-payment list.

The floor prevents the most extreme Bethesda outcome, but leaves a substantial disparity. Using the current minimum as a reference, $18.54 is approximately 37% below $29.55. The eventual difference would depend on the updated 2027 minimum and final pricing decisions. Comparable manual screening services could therefore acquire markedly different payments largely associated with the reporting distinction, even after statutory protection is applied.

What's Next?

CMS expects to publish final 2027 rates in November. The preliminary cytology results deserve awareness across the code family: additional manual review can receive less payment, closely related reporting variants can diverge sharply, and small reporting populations can generate large apparent increases. The statutory floor protects against some reductions, while leaving the unexpected relationships between other prices intact.

Source workbook for the numerical comparisons:

https://www.cms.gov/medicare/payment/fee-schedules/clinical-laboratory-fee-schedule/clfs-pama-reporting-resources

https://www.cms.gov/files/zip/cy-2027-preliminary-weighted-median-2027-clfs-rate-calculations-raw-vs-trimmed-rates.zip