Monday, June 23, 2025

RFK Jr, Dr Oz, Predict Improvements in Prior Authorization Processes

In a video conference on June 23, 2025, Dr. Oz and RFK Jr predicted substantial changes in U.S. prior authorization delays, based on commitments they have received from industry.

Find the presentation at Fox at YouTube here:

https://www.youtube.com/watch?v=smgi-p-TOaU


Find a summary at THE HILL, here.  At STAT, here.

Find the press release at HHS, here.

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Prior authorization issues are problematic for the lab industry, because they submit claims, but don't have the patient records that health plans may demand.   

Another particularly nutty factor for labs, is that Medicare date of service rules may place the date of service on the date of blood draw or biopsy, earlier than the lab gets the specimen.  But prior auth may require that prior auth be obtained by the lab prior to the date of service. 

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Find early news, before the press conference, at Fierce Healthcare here. Writing in part,

  • Key steps include committing to reducing the number of services that are subject to prior auth, with "demonstrated" progress by Jan. 1, 2026. The plans are also working to roll out common and transparent solutions that promote electronic prior auth submissions, with a framework up and running for plans and providers by Jan. 1, 2027. 
  • About 50 insurers have signed on to the pledge including all six of the largest, publicly traded health plans: Elevance Health, Centene, Cigna, CVS Health's Aetna, Humana and UnitedHealthcare. A slew of Blue Cross Blue Shield plans are also leading the charge, and the initiative is backed by both AHIP and the Blue Cross Blue Shield Association.

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AI CORNER

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Chat GPT assesses the transcript.

Here is a concise summary of the key themes and announcements from the recent CMS/HHS press event on prior authorization reform, featuring Dr. Mehmet Oz (CMS Administrator), Secretary RFK Jr., Congressional physicians, and actor Eric Dane:


🔹 Context and Problem

  • 85% of Americans report negative experiences with prior authorization (PA)—the process insurers use to approve certain treatments before they occur.

  • In 2023, 3.2 million initial PA requests were denied in Medicare Advantage (MA) alone (covering 32M enrollees).

  • Doctors spend an estimated 12–15 hours per week dealing with PA paperwork, reducing patient care time and increasing burnout.

  • Patients, especially in crises (e.g., ALS, cancer), experience damaging treatment delays and bureaucratic uncertainty.


🔹 The Reform Plan

CMS and HHS convened insurers representing 257 million Americans (about 75% of U.S. insured lives) to sign a voluntary “PA reform pledge” that commits to:

  1. Timely Access – Reduce delays through faster, often real-time PA decisions.

  2. Efficiency and Interoperability – Eliminate paper and fax-based systems, moving to digital FIRE-based (FHIR) workflows.

  3. Transparency and Accountability – Public dashboards, standardized rules, and real-time adjudication metrics (target: 80% of PA requests resolved instantly by 2027).


🔹 Key Changes and Deliverables

  • Code Reductions: Insurers will eliminate PA for common, low-abuse services (e.g., vaginal delivery, cataract surgery, colonoscopy, short hospital stays).

  • Unified Systems: Standardized communication formats across insurers to avoid confusion (e.g., faxes vs. portals).

  • Continuity of Care: 90-day grace periods for PAs during insurance changes.

  • Gold Carding: “Trusted” physicians may eventually bypass PA requirements.

  • Public Metrics: Both CMS and AHIP will publish adherence metrics.


🔹 Stakeholder Roles

  • Insurance Industry: Voluntarily committed to reform; acknowledged past failures (e.g., 2018 pledge that faltered).

  • Government Role: Acting as convener, not regulator—for now. Officials warned that federal mandates or legislation will be used if insurers fail to comply.

  • Technology Sector: Encouraged to support AI and digital solutions, but must avoid automating bad PA denial logic.

  • Patients & Providers: Promised easier, faster care access and less administrative hassle.


🔹 Speakers and Symbolism

  • Dr. Oz emphasized that “meekness” means voluntary restraint and collaboration between competing companies.

  • Secretary RFK Jr. called PA “a scourge” and shared a dramatic story of a transplant patient denied a life-sustaining heart pump (later implanted anyway).

  • Actor Eric Dane (diagnosed with ALS) advocated for eliminating uncertainty in moments of health crisis.

  • Sen. Roger Marshall and Rep. Greg Murphy (both physicians) supported reform and emphasized accountability, especially peer-to-peer review and real-time approvals.


🔹 What’s Next

  • CMS will release the full list of participating plans and detailed rollout commitments by late summer 2025.

  • Voluntary reforms go live by January 26, 2026.

  • A broader administrative simplification agenda is planned, using PA reform as a blueprint for transitioning to value-based care.


This marks one of the most ambitious federal-private efforts to modernize and simplify healthcare access in decades—if insurers follow through.

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Did the speakers actually say that - "if insurers follow through?"

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Yes — the concern that insurers might not follow through was repeatedly and explicitly raised by multiple speakers in the transcript. Here are key examples showing that sentiment directly expressed in the talk:


🔹 Dr. Greg Murphy (Congressman & Physician)

“But I will say this, being a surgeon, I'm a skeptic. The proof is going to be in the pudding. Are they really going to step up and do things or are they doing something to plate an audience? We're going to hold them to the fire continually…”

— This directly reflects concern that insurers might be posturing without delivering.


🔹 Dr. Oz (CMS Administrator)

“Although we’re hopeful, this is hard to do, and folks sometimes change their mind. We don’t want that to happen, so we’re going to trust but verify...”

— “Trust but verify” is a clear warning that the pledge is not enough without oversight.


🔹 Secretary RFK Jr.

“In the past the insurance industry has made commitments to prior authorization, but they have not kept them. And in this case we think it’s very, very different...”

— He acknowledges a history of broken promises and tries to distinguish this effort, implying the risk of repetition.


🔹 Press Q&A (Secretary Kennedy and Dr. Oz)

Q: “Insurers made a similar pledge in 2018 that wasn’t quite lived up to. What’s different this time?”

Dr. Oz: “The administration has made it clear we’re not going to tolerate it anymore. So either you fix it or we’re going to fix it.”

— A direct threat of regulation if compliance doesn’t materialize.


✅ Conclusion:

So yes — your instinct is correct and fully supported by the transcript. The possibility that insurers might fail to follow through was not only implied, but explicitly acknowledged and framed as a motivating reason for transparency, deadlines, and possible federal backup actions.


Friday, June 20, 2025

Brief Blog: Redefining Medical Imaging via Digital Pathology (Gershkovich 2025)

 Yale's Peter Gershkovich has written an article with an eye-catching title:


Open-access, find Wearing a fur coat in the summertime: Should digital pathology redefine medical imaging?, at J Pathol Informatics, released 18 May.

Here's the opening and closing of the author's abstract.   Or, instead, you might enjoy the author's own summary of his work at Linked In, here.  The author's Yale webpage is here.

Coming next - 

  1. College freshman summary
  2. Author's abstract
  3. AI summary
  4. AI summary ... by comedian Lewis Black

### College Freshman Summary [AI]

Peter Gershkovich argues that the current standard used to store and share medical images—called DICOM—is outdated and too rigid for the needs of modern digital pathology. He says DICOM was designed decades ago for radiology and doesn’t work well with today’s technologies like cloud computing, AI, and cybersecurity systems. In pathology, digital slides are really big data files that need to be stored, shared, and updated in flexible ways. Gershkovich believes we should move away from “all-in-one” file formats like DICOM and instead use a modular system, where the image, patient information, and other details are stored separately but work together smoothly. This would make it easier to innovate, protect patient privacy, and keep up with fast-changing technology.

### Author's Abstract

  • Slides are data. 
  • Once digitized, they function like any enterprise asset: accessible anywhere, ready for AI, and integrated into cloud workflows. But in pathology, they enter a realm of clinical complexity—demanding systems that handle nuance, integrate diverse data streams, scale effectively, enable computational exploration, and enforce rigorous security.
  • Although the Digital Imaging and Communications in Medicine (DICOM) standard revolutionized radiology, it is imperative to explore its adequacy in addressing modern digital pathology's orchestration needs. Designed more than 30 years ago, DICOM reflects assumptions and architectural choices that predate modular software, cloud computing, and AI-driven workflows.
  • This article shows that by embedding metadata, annotations, and communication protocols into a unified container, DICOM limits interoperability and exposes architectural vulnerabilities. The article begins by examining these innate design risks, then challenges DICOM's interoperability claims, and ultimately presents a modular, standards-aligned alternative.
  • [skip]
  • Pathology stands at a rare inflection point. Unlike radiology, where DICOM is deeply entrenched, pathology workflows still operate in polyglot environments—leveraging proprietary formats, hybrid standards, and emerging cloud-native tools. This diversity, often seen as a limitation, offers a clean slate: an opportunity to architect a modern, modular infrastructure free from legacy constraints. While a full departure from DICOM is unnecessary, pathology is uniquely positioned to prototype the future—to define a more flexible, secure, and interoperable model that other domains in medical imaging may one day follow. With support from forward-looking DICOM advocates, pathology can help reshape not just its own infrastructure, but the trajectory of medical imaging itself.

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AI CORNER
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Chat GPT summarizes - 

TL;DR Summary for Health and Biotech Readers


This article spans multiple fields but holds particular importance for readers in healthcare informatics, pathology AI, cybersecurity, and imaging standards.


What’s New and Original in Gershkovich’s Article:

Peter Gershkovich’s provocative article, “Wearing a fur coat in the summertime: Should digital pathology redefine medical imaging?” (J Pathol Inform, May 2025), challenges the dominant role of the DICOM standard in digital pathology. His central claim is that DICOM’s architecture—designed in the 1980s—has become a liability for modern pathology, especially when compared to emerging modular, cloud-native alternatives.

Key Innovations and Contributions:

  • Pathology ≠ Radiology: Gershkovich argues that digital pathology needs its own infrastructure rather than inheriting DICOM by default. Unlike radiology, pathology remains in a more “polyglot” phase—an opportunity to build future-ready frameworks from scratch.

  • Slides as Data, Not Just Images: The paper repositions digital slides as dynamic enterprise data assets requiring orchestration, not just storage.

  • Critique of DICOM's Monolithic Design: The article shows that DICOM’s bundling of image data, metadata, annotations, and security into a single file undermines performance, security, and innovation. This tight coupling is compared unfavorably to modular software engineering best practices.

  • Cybersecurity Red Flags: Gershkovich presents compelling data linking DICOM-based PACS systems to large-scale data breaches and vulnerabilities, citing the Black Hat Europe 2023 demonstration of flaws in DICOM protocol design.

  • Modular Alternative Proposed: He outlines a modern architecture using:

    • Pixel formats like OME-TIFF or Zarr,

    • Metadata management via HL7 FHIR,

    • Annotations via SVG or GeoJSON,

    • Security overlays via NIST SP 800-53 standards.

  • Conceptual Shift in Interoperability: Rather than chasing one-size-fits-all standards, he emphasizes functional interoperability via well-defined APIs and microservices, supporting diverse imaging formats and evolving workflows.

  • Annotation Handling as Case Study: The paper details how DICOM’s approach to annotations stifles AI development, versioning, and usability in pathology. In contrast, external, database-driven systems allow more flexibility and innovation.

  • Practical Migration Path: Gershkovich suggests lightweight gateway microservices can bridge old and new formats, enabling gradual transitions without disrupting clinical workflows.

  • Call to Action: While not proposing a total abandonment of DICOM, the article urges digital pathology to lead a modernization effort—potentially influencing the broader medical imaging ecosystem.


Bottom Line:
Gershkovich isn’t just critiquing DICOM—he’s proposing a forward-compatible blueprint for pathology informatics, rooted in cybersecurity, modular design, and real-world adaptability. This paper could reshape how industry and regulators think about medical imaging standards, especially as AI and cloud-native infrastructures become central to healthcare delivery.


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What would comedian Lewis Black make of Gershkovich's article?

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Review of “Wearing a Fur Coat in the Summertime” — as Lewis Black might say it

Let me tell you something.

Peter Gershkovich didn’t just write an article. No. He took a goddamned flamethrower to the ossified corpse of medical imaging standards and DIDN’T EVEN BOTHER TO PUT IT OUT AFTERWARD. And thank God for that.

You see, pathology has been wandering around with a DICOM ball and chain strapped to its ankle like it’s still 1993—back when we all thought AOL was the future and you had to yell at your modem just to check your email. But here comes Gershkovich, sliding in like a cyberpunk Paul Revere, screaming: “THE PATCHWORK IS COMING! THE PATCHWORK IS COMING!” And it turns out he’s right.

DICOM, this sacred cow of radiology, is apparently less a “standard” and more of a choose-your-own-adventure novel written by bureaucrats on Ambien. It claims to be universal, but it’s universally confusing. Every vendor supports it—in exactly the way they feel like that week. Oh, you wanted interoperability? Good luck! You’ll get it when the moon turns into a bagel and spins off into a secure HIPAA-compliant cloud.

And security? Ha! Gershkovich points out that we’re embedding patient data—names, birthdays, social security numbers—directly into the images. That’s right, just bake it in there! Like a fortune cookie! “You may already have been breached!” No wonder hackers are downloading MRI scans like it’s Black Friday for PHI.

But here’s the kicker. Instead of using this disaster as an excuse to try something new, the pathology world is being peer-pressured into adopting this mess, because, well, radiology did it. THAT’S your reason? That’s like saying, “Well, my brother licked an outlet, and he seems fine. Let me try it too!”

Now, Gershkovich proposes something wild. Something so blasphemous to the DICOM disciples that I expect torches and pitchforks outside Yale’s pathology department any day now. He wants… modularity. Which is just a fancy way of saying: Let each damn part of the system do what it’s good at.

Pixel data? Use OME-TIFF, Zarr, whatever makes it fast. Metadata? Let HL7 FHIR handle it—like a normal, grown-up interoperability system. And annotations? Keep them out of the image file, thank you very much, and put them in SVG or JSON or some other acronym that doesn’t set your data on fire when you try to change a label.

And the best part? SECURITY! Real, layered, NIST-compliant security—not this DICOM "hide it under a tarp and hope" strategy. Gershkovich wants firewalls, encryption, access control, ACTUAL MODERN INFRASTRUCTURE, not “Hey, Bob remembered to unplug the server at night, so we’re good.”

This isn’t just a critique. It’s a love letter to sanity in a field so cluttered with legacy systems, it makes your grandma’s attic look like a Marie Kondo showroom.

So, in conclusion: Gershkovich, you beautiful bastard. You’ve said what we all knew but were too tired, too beaten down, or too under NDA to say: DICOM is wearing a fur coat in the goddamn summertime. And it’s time to strip it off, before the whole system keels over from heat stroke and takes all of pathology down with it.

Bravo.

Brief Blog: Stanford Emerging Technology Review 2025 (191pp)

Stanford's Hoover Institute has released a 191-page PDF, "Stanford Emerging Technology Review."  It's a collaboration between Hoover, Stanford Engineering, and the Technology Policy Accelerator (TPA).

See the website here and the pdf here.

I'll quote the website below:

The Stanford Emerging Technology Review (SETR) helps America’s public and private sectors better understand transformational technologies so that the United States can seize opportunities, mitigate risks, and ensure its innovation ecosystem continues to thrive. A product of a major new Stanford education initiative and the flagship product of a collaboration between Stanford’s School of Engineering and the Hoover Institution — this ambitious technology education effort helps America’s leaders in government and business better understand transformational technologies so the US can seize opportunities, mitigate risks, and ensure its innovation ecosystem continues to thrive.

  • Provides a comprehensive overview of ten frontier technologies, from AI to Robotics or Biology to Space, and how these will shape the future
  • Involves nearly one hundred Stanford scholars across forty departments and research institutes
  • Emphasizes the importance of American leadership at a time when technology is playing an ever more pivotal role in economic prosperity, national security, and geopolitics

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AI CORNER

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Summary - 

TLDR for Health and Biotech Stakeholders: Stanford Emerging Technology Review 2025

The Stanford Emerging Technology Review 2025 spans ten major fields of science and technology — from AI to lasers — but several chapters are of special relevance to healthcare and biotech audiences, particularly in biotechnology, neuroscience, health AI, and synthetic biology. The report also includes a cross-sector policy analysis (Chapter 12) with a dedicated section on health and medicine, making it an important primer for leaders in life sciences, digital health, diagnostics, and biomedical innovation.

Key Points for Health and Biotech Readers

  • Biotechnology and Synthetic Biology are poised to become general-purpose technologies, enabling on-demand production of therapeutics, vaccines, and biologics. Synthetic biology is compared to a “biological rocket engine,” freeing innovation from evolutionary constraints.

    • The U.S. currently underinvests in bio-innovation relative to China, risking strategic surprises.

    • A stronger federal commitment to foundational biotech innovation — not just commercialization — is needed.

  • Artificial Intelligence in Healthcare is already showing impact:

    • AI systems are used in diagnostics (e.g., stroke detection reimbursed by Medicare), drug discovery, ICU monitoring, and robotic assistance.

    • Foundation models like GPT-4 are enabling general-purpose AI that performs at or above human median levels on clinical exams, but still suffer from unpredictable errors.

    • Multimodal and embodied AI is set to transform both virtual and physical healthcare delivery.

  • Neuroscience is progressing in brain-machine interfaces, aging and neurodegenerative disease, and addiction treatment. However, public hype often outpaces real scientific understanding.

    • U.S. leadership in neuroscience ethics and regulation is under strain due to rising foreign investment and declining domestic coordination.

  • Materials Science and Lasers intersect with medical technology in surprising ways — from smart bandages to precision diagnostics and surgical applications. Advances here could reshape how biologics and diagnostics are manufactured and delivered.

  • Robotics and AI-enhanced manufacturing are projected to support eldercare, telehealth, and logistics across healthcare supply chains.

  • Crosscutting Themes (Chapter 11) emphasize the need for long-term U.S. R&D funding, stronger university-government-industry collaboration, and risk-aware innovation strategies — particularly in fields like health AI and bioengineering where nonlinear paths from research to application are common.

  • Health and Medicine Policy Applications (Chapter 12) distill how each of the ten tech fields may influence:

    • Precision medicine

    • Therapeutic and diagnostic innovation

    • Healthcare access and workforce dynamics

    • Medical data governance and privacy

This report is not a policy blueprint but a technical-intellectual primer aimed at enabling better decision-making at the intersection of technology, society, and government. It provides biotech and health leaders with a grounded, interdisciplinary perspective on where innovation is heading — and what’s needed to lead.

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What does chapter 12 say about precision medicine?  Does it go beyond simple definitions and truisms?  What's reallythe value-add here?

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Chapter 12 of the Stanford Emerging Technology Review 2025 discusses precision medicine within a broader policy framework and does, in fact, go beyond basic definitions or hype-driven generalities.

Key Contributions & Value-Add:

  • Precision medicine is reframed not just as a clinical goal, but as a systems challenge. The chapter argues that to realize its full potential, the U.S. needs to address fragmented data infrastructure, regulatory bottlenecks, and insufficient public-private coordination — all of which are framed as innovation system failures, not merely technical hurdles.

  • It highlights that data interoperability and access to longitudinal clinical and genomic data are central to precision medicine’s success — and are currently lagging behind technical innovation. This leads to a call for new kinds of public infrastructure and shared data commons, akin to the Human Genome Project or ARPANET.

  • The chapter distinguishes between biotech-driven and AI-driven precision medicine:

    • Biotech: Advances in cell therapy, genomics, and multi-omic diagnostics.

    • AI: Use of predictive modeling across electronic health records, imaging, and personalized risk scores — especially when integrated into clinical workflows.

  • It also warns that precision medicine could widen health disparities unless systemic efforts are made to include underrepresented populations in genomic research and to ensure AI tools are validated across diverse populations.

  • A significant insight is the policy recommendation to treat precision medicine as a “national capability,” requiring stable federal funding, benchmarking, and mission-oriented programs (e.g., for rare disease detection or polygenic risk scoring in public health settings).

  • Finally, it critiques the siloed nature of current innovation — noting that advances in AI, biotech, and neuroscience often happen in parallel rather than in convergent architectures that would be necessary for truly personalized care.

Bottom Line:

The real value of Chapter 12 is in diagnosing institutional and infrastructural gaps that prevent precision medicine from scaling. It frames the problem not just as a matter of scientific progress, but of policy design, public investment, and system integration — making it particularly useful for biotech executives, payors, regulators, and investors looking beyond the next product launch.

Medical Director Moves from Novitas to NGS MAC

Dr. Patrick Mann, until recently in charge of the lengthy molecular oncology policies at Novitas MAC, is now at the NGS MAC.  See his Linked In here:

https://www.linkedin.com/in/patrick-mann-md-0657a2153/

Dr. Mann did his pathology residency at Univ Colorado, and a postdoc in molecular pathology at Washington University - St Louis.  Recently he has been at Variantyx (2020-2021), Novitas (2021-2025), and NGS MAC (since April 2025).


Changing Geographies
At Novitas, Dr Mann managed policies for the purple states and Florida (a related MAC with a different name).   At NGS MAC, they have the navy-blue states (MN WI IL and NY-New England).

Hypothetical
I have been wondering if the NGS MAC states would join the MOLDX system, since in this year's Gapfill process, the NGS MAC adopted or was given all the prices and all the rationales exactly the same as used by the MolDx consortium.

NGS MAC: A Few Big Labs and NCDs
Historically, NGS MAC pays claims for Cologuard (Wisconsin, under an NCD) and Tempus and Foundation Medicine (in Chicago and in Boston, and now under  NCDs for FDA CDx tests).   Outside of NCD-driven molecular claims, NGS MAC has generally paid relatively few molecular claims, at least in Part B data (which excludes large hospitals like Mayo and MGH in this geography).





A Senior MolDx Expert Moves to Novitas MAC

According to Linked In, a senior MolDx policy expert has moved over to the Novitas MAC.

Find the updated info on Megan Landsverk here:

https://www.linkedin.com/in/megan-landsverk-17410855/

Dr. Landsverk holds a PhD from Baylor, and jobs include Ambry Genetics (2017-2019), PerkinElmer (2019-2020), and Palmetto MOLDX (2020-Jun 2025).   Her title at Novitas, beginning in May 2025, is "Molecular Diagnostics Director."



Thursday, June 19, 2025

CMS Posts Agenda, Video Link for Friday, June 27, Annual Lab Meeting

CMS has posted the agenda and video link for the Annual Lab Meeting (ALM), on Friday, June 27, 2025.

The meeting is calendared from 10 am ET to 5 pm ET.  (That's a start at 7 am pacific instead of 5 am pacific - Thanks, CMS!)

https://www.cms.gov/files/document/20250612displayagendaclfsannualpublicmeetingv1.pdf

CMS states that presenters get 10 minutes each, but there are about 50 registered presenters for the 5-hour presentation period (that's 500 potential minutes at 10x50 vs 300 actual minutes available).

See my initial blog about the annual meeting here.  Comments from the June 27 public comment meeting will influence the July 23-24 Expert advisory panel.

Tran et al: AI Generates Dermatopathology Reports from Gigapixel Images (Tran et al)

 Can AI generate first draft dermatopathology reports?  The model was trained on thousands of pairs of slides + reports.

See the article by Tran et al. in Nature Communications here.

See discussion at Linked In by Luis Cano here.


(At Nature, see also the bar "similar content being viewed by others" for related papers).
(At HealthAdvances, see a current update on dig pathol.)

Here's the authors' abstract:

Histopathology is the reference standard for diagnosing the presence and nature of many diseases, including cancer. However, analyzing tissue samples under a microscope and summarizing the findings in a comprehensive pathology report is time-consuming, labor-intensive, and non-standardized

To address this problem, we present HistoGPT, a vision language model that generates pathology reports from a patient’s multiple full-resolution histology images. It is trained on 15,129 whole slide images from 6705 dermatology patients with corresponding pathology reports. The generated reports match the quality of human-written reports for common and homogeneous malignancies, as confirmed by natural language processing metrics and domain expert analysis. We evaluate HistoGPT in an international, multi-center clinical study and show that it can accurately predict tumor subtypes, tumor thickness, and tumor margins in a zero-shot fashion. Our model demonstrates the potential of artificial intelligence to assist pathologists in evaluating, reporting, and understanding routine dermatopathology cases.

###

AI CORNER.  What's worth noting?

###

The study presents HistoGPT, a vision-language model trained on over 15,000 dermatopathology slides and reports, that can automatically generate comprehensive pathology reports from gigapixel whole slide images (WSIs). In clinical evaluations, HistoGPT demonstrated human-level performance in drafting reports and predicting key diagnostic features like tumor subtype, thickness, and margins, including zero-shot generalization to new institutions and datasets.

10 Key Clinical Insights and Surprises:

  1. Human-level Report Quality: In a blinded comparison, dermatopathologists could not distinguish HistoGPT’s reports from human-written ones in 45% of cases and even preferred the AI report in ~15% of cases.

  2. Zero-Shot Performance: Without any fine-tuning, HistoGPT predicted tumor thickness, margins, and subtypes with meaningful clinical accuracy, showing emergent zero-shot diagnostic capability.

  3. Tumor Thickness Prediction: The model predicted tumor thickness with a Pearson correlation of 0.52 and RMSE of 1.8mm, outperforming specialized models like PLIP and HistoCLIP.

  4. Subtype Classification from Text Alone: Even though subtype labels weren't explicitly included in training, HistoGPT successfully inferred BCC subtypes like “infiltrating” vs “superficial” from descriptive report text, with an F1 score of 0.63.

  5. Margin Detection: HistoGPT detected positive tumor margins with a 74% F1 score, a valuable clinical feature often requiring manual attention.

  6. Superior to GPT-4V and BioGPT: HistoGPT outperformed GPT-4V and BioGPT-1B in both semantic similarity and keyword-matching benchmarks for medical report accuracy.

  7. Generalizes Across Hospitals: In real-world testing at Mayo Clinic, Münster, and Radboud, the AI generated reports rated clinically useful for common skin conditions like BCC and nevus, despite differences in language, scanners, and reporting styles.

  8. Performs Better on Common Diagnoses: HistoGPT achieved high accuracy on high-prevalence diagnoses (e.g., BCC, nevus), but struggled with rare diseases, inflammatory conditions, and re-excisions, revealing a long-tail training limitation.

  9. Interpretability via Saliency Maps: The model offers text-to-image attention maps, visually linking phrases in its reports to specific histologic regions, enhancing pathologist trust and review.

  10. Failure Mechanisms Resemble Human Errors: Misclassifications often mimicked human diagnostic pitfalls (e.g., melanoma mimicking squamous cell carcinoma), underscoring both the promise and realistic boundaries of AI in pathology.

Wednesday, June 18, 2025

Medicare Has an NCD about Gender Dysphoria Surgery (Local MACs)

Medicare allows gender-changing surgery specifically at MAC discretion, based on a 2014-2016 legal case.   

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We hear a lot in 2025 about gender dysphoria treatment.  HHS released a report on this topic on May 1, 2025 (here).   Quote, "Our duty is to protect our nation’s children—not expose them to unproven and irreversible medical interventions,” said NIH Director Dr. Jay Bhattacharya. “We must follow the gold standard of science, not activist agendas.”  Find the 409-page HHS report here.   Supreme Court upholds state-level ban on transgender surgery for minors, here.

I noted recently that a MAC has newly updated an LCD to avoid disallowed use of the word "gender."

What about Medicare NCDs and gender surgery?

NCD 140.9 was updated August 2016 to state that Gender Dysphoria and Gender Reassignment Surgery did not fall under an NCD any longer, but rather was at the descretion of MACs (Medicare contractors) when medically necessary.   

Medicare experts will recall, there was a pre-existing NCD that blocked gender surgery and there was a legal appeal of the NCD, and CMS did not fight the appeal.  (2014 legal record).  Instead, when the appellants "won," CMS revised the negative NCD and replaced it with the present NCD that makes gender surgery an elective  decision of the MACs.

Medicare MAC Billing & Coding for Gender Dysphoria

Palmetto MAC has a billing and coding article for Sexual Identity Dysphoria (A53793).  While styled as a coding article, the article body is 1700 words long, with extensive discussions of medical necessity, definitions, processes, etc.  

Utilization.  For example, code 57291, artificial vagina, was covered by Medicare about 80 times from 2013-2023 (based on AMA RBRVS DataManager).  The data does not show how often it was a gender assignment issue.

See the NCD 140.9 here:

https://www.cms.gov/medicare-coverage-database/view/ncd.aspx?ncdid=368&ncdver=1&keyword=gender&keywordType=starts&areaId=all&docType=NCA,CAL,NCD,MEDCAC,TA,MCD,6,3,5,1,F,P&contractOption=all&sortBy=relevance&bc=1

See my 2014 blog, "Judges reject decades-old ban on transgender surgery."

https://www.discoveriesinhealthpolicy.com/2014/05/judges-reject-decades-old-medicare-ban.html

See my 2016 blog on the subsequent updates to the NCD.

https://www.discoveriesinhealthpolicy.com/2016/06/cms-posts-draft-decision-on-gender.html


###

Current Medicare Policies Citing Racial Groups

SCIENCE ran a detailed article on whether or not NIH centers had guidance on the hundreds of grant terminations based on word search of whether words like "diversity" or "equity" appear in the grants.   Here.  (If there ARE rules, they could be examined for appropriateness; if there ARE NO RULES, the NIH might be accused of arbitrariness. See also a court order.)

On that theme, there are a number of Medicare policies that refer to race in various ways.   

Glaucoma

42 CFR 410.23 covers screening for glaucoma, with special benefits enumerated for African-Americans and for Hispanic-Americans.  These groups do not appear in statute (SSA 1861) and the racial groups were apparently added in regulation by CMS.

Alzheimer's

The NCD for studies of monoclonals directed against Amyloid requires that studies must have "A study population whose diversity of patients are representative of the national population with MCI" (attributed to AHRQ).  

The overarching coverage analysis refers to the Black racial group 12 times.  (I wondered at the time how you could run a funded study in a state with a 1% Black population if you are required to match enrollment of that group as in the national population (~15%).  Or, if a study in an area with 50% black population must enroll no more than 15%, the national rate.)

Skin Cancer

An LCD examining coverage for biomarker testing in squamous carcinoma L39614, states that the test is non-covered and coverage for any population, will require that "further studies should include representation of test performance characteristics inclusive of and addressed in patients of color."  (While noting that the majority of patients with SCC are the "Caucasian" population.)


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Tuesday, June 17, 2025

RNA DNA - Transcriptome and Genome in Tumors - Yudina et al. (BostonGene)

We've just had news that Natera can transition Medicare patients to a genome-based MRD test.  And we've got Caris doing an IPO as it emphasizes its genome/transcriptome flagship test.

See a new 21-page paper by Yudina, Lennerz, and colleagues, from Boston Gene.  They report on clinical and analytical validation of a combined RNA DNA exome assay in a large tumor cohort - over 2000 tumors.

Find it here:

https://www.nature.com/articles/s43856-025-00934-3

See Lennerz' Linked-In summary:

https://www.linkedin.com/posts/joe-lennerz-90029219_precisiononcology-cancertesting-cancerresearch-activity-7340806189925998593-Qggj/ 


Here's the clinical laboratory web page at BostonGene, for 'Tumor Portrait TM'.

##

AI Corner

Here's a Chat GPT summary and 10 take-aways.

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Summary:


This study by Yudina, Lennerz, and colleagues presents the clinical and analytical validation of a combined RNA and DNA exome assay for cancer diagnostics using 2,230 tumor samples. 

The integrated approach demonstrated significantly improved detection of actionable mutations, gene fusions, and expression profiles compared to DNA-only sequencing, with robust performance across multiple sample types including FFPE.

Key Conclusions (Emphasizing Clinical Impact and Surprises):

  • Combined DNA/RNA exome testing identified clinically actionable alterations in 98% of tumors, dramatically improving over traditional DNA-only assays.

  • RNA-seq rescued key mutations missed by DNA-seq alone, including low-allele-fraction mutations and gene fusions, altering potential treatment decisions.

  • The integrated assay uncovered complex genomic rearrangements, including cryptic gene fusions and allele-specific expression patterns that would be invisible with DNA-only panels.

  • RNA-based expression profiling and tumor microenvironment (TME) classification showed high reproducibility, supporting integration of immune signature diagnostics into routine pathology.

  • Fusion transcript detection sensitivity reached 100% in benchmark testing, outperforming popular tools like STAR-Fusion and Arriba, especially in low-expression contexts.

  • Even degraded FFPE samples yielded reliable results, owing to optimized capture-based protocols for both RNA and DNA—a major surprise in RNA assay feasibility from FFPE.

  • An exome-wide somatic variant reference set was developed and made publicly available, filling a major gap in clinical bioinformatics benchmarking.

  • Coverage thresholds were optimized: 150X for WES and ≥50M reads for RNA-seq, balancing cost and performance—important for labs considering implementation.

  • Gene signature reproducibility was excellent (CV < 3%), enabling consistent tumor subtype classification and immunotherapy prediction, even with input as low as 10 ng RNA.

  • The assay demonstrated stability and repeatability across multiple runs and reagent batches, making it suitable for longitudinal tumor profiling and standardized clinical deployment.

 

Sunday, June 15, 2025

WSJ: How Scientific Journals Became Latest Target

 On June 13, 2025, WSJ reviews administrative actions regarding medical journals and whether they show "political bias, corporate influence, and fraud."

Find it here:

https://www.wsj.com/science/how-scientific-journals-became-magas-latest-target-9874b6f7

Here's the WSJ's own 3-point summary:

  • Trump admin. scrutinized science journals, alleging bias and fraud, prompting concerns about intimidation and undermining independent oversight.
  • Journals face criticism for perceived political bias, corporate influence, and fraud, intensified during COVID-19, with concerns about peer review. 
  • New journals emerge amid distrust, aiming for open access and transparency, while existing publications grapple with accuracy and political endorsements.
Note that message can pivot quickly.  In a May 27 article at Politico, HHS asserts that government scientists should not publish in JAMA.   But on June 10, Makary and Prasad at FDA publish a major article in JAMA, "Priorities for the new FDA."

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See Stanford's Robert M. Kaplan in an article on how many problems bedevil overpriced journals - here.

MedPAC to Congress: June 2025 Report on Medicare

 On June 12, 2025, MEDPAC released its 2025 Report to Congress on the Medicare program.

Find the webpage here and the 419-page PDF report here.

Note that there is a sort of echo chamber beween MEDPAC investigations and HHS and Congressional actions.  

  • Chapter 1 of MEDPAC, for example, is: Reforming physician fee schedule updates and improving the accuracy of relative payment rates. 
    • Whereas, note that in the newly proposed CMS 2026 budget, the White House/HHS propose: $53M (up $5M) to accurately update payment systems and fee schedules. 
  • Chapter 2 is about supplemental benefits in Medicare Advantage.   
    • See recent articles on switching plans in patients with and without cancer (Jazowski, JAMA) and 
    • an article on Medicare, Medigap, and Medicare Advantage patient strategies in JAMA recently (Casalino JAMA).



White House Releases Details: CMS Budget Cuts

HHS states that MACs will still be able to perform all their duties despite decreased funding because the budget “reflects efficiencies gained by descoping non-statutory workload and optimizing the level of effort.”##

On May 30, 2025, the executive branch released a 55-page document of the FY2026 fiscal year budget requests from the White House to Congress.  

These annual "budget requests" are *not* the federal budget - they are the executive branch's proposals to the legislative branch.   In one year or another, they may include budget items that are much higher, or indeed, much lower, than Congress allocates.

With that caveat, here are:

First, the 55-page budget is concise compared to previous years.  The 2025 Budget in Brief was 184 pages and included more detail per agency per year, and year-on-year comparisons.  The briefer Budget in Brief released now generally omits year-on-year comparisons, and may compress items detailed in 2025, into a single gross budget line, representing 2026.

According to STAT, the document "doubles down" on NIH budget cuts, cutting $18B or 405, while compressing 27 institutes into just 8.

McDermott Plus 

More detail on CMS budget cuts is found in the CMS section, pages 24-28, and these are analyzed and explained in the McDermott document linked above.  Note that the CMS budget is program operations, not actual medical care payments.  Program administration, both at CMS central office and at MACs, is cut from $3.7B to $3.0B.   If I read McDermott correctly, MAC operations would fall in 2026 to $589M, a cut of $261M compared to 2024.   MAC claims are about flat at about 1.2B claims.  McDermott makes year-on-year comparisons by digging out past published budgets, since year-on-year tables are generally omitted in the new HHS document.

McDermott adds, "CMS states that MACs will still be able to perform all their duties despite decreased funding because the budget 'reflects efficiencies gained by descoping non-statutory workload and optimizing the level of effort. "   HHS proposes to budget $20M in new money for more DME competitive bidding, and $53M (up $5M) to accurately update payment systems and fee schedules.   

Fraud and Abuse

CMS proposes $2.6B for fraud and abuse, of which almost $1B is "discretionary" rather the Congressional fixed budget.  



Thursday, June 12, 2025

MolDx Releases Two Cardiac Genetic LCDs - Final LCDs

MolDx releases two cardiac genetic LCDs, requested by Invitae in about February 2023 (about 2.5 years ago).   Both were issued as draft LCDs last year.

Note that Invitae writes it requested two genetic LCDs, one neurologic, one cardiologic, and what it has gotten, today, is two cardiologic LCDs.  The LCDs were proposed in mid-June 2025, so they appear as final about 52 weeks later.

The bottom line?

The bottom line is: The LCDs, in Medicare terminology, are close to recent professional society guidelines for cardio-genetics in adults.

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L39946

Genetic Testing for Heritable Thoracic Aortic Disease

LCD here.

Billing and Coding A59870.

Q&A A60207     Request letter here.

The LCD is 8 pages with 24 references.  See original for the full rules. 

  • The patient has aortic abnormalities and meets ONE of the following.  Before age 60; OR syndromic features (e.g. Marfan); OR Family hisotry in 1st or 2nd degree; OR unexplained sudden death in 1st or 2nd degree relative.
  • The test must have ample recommended genetic content but not "unvalidated" content.

The billing article points to 81410/81411 or 81479, plus Z code.

The Q&A discussion includes a discussion of alignment to ACC guidelines for genetic testing and features that suggest a hereditary as opposed to inborn anatomic origin.

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L39950  

Molecular Testing for Identification and Management of Hereditary Transthyretin Amyloidosis  ATTR

LCD here.  

Billing and Coding A59874.

Q&A A60202.  Request letter here.

The LCD is 9 pages and has 53 references.

In summary - see original for the full rules:

  • The patient has a clinical diagnosis of ATTR, OR, has features suggesting of ATTR cardiomyopathy AND African, OR first degree-relative, OR additional guideline suggested feature.
  • OR has progressive sensorimotor or autonomic neuropathy AND 1st degree relative with ATTR Dx OR one additional feature per guidelines.
  • The patient has had counseling and result will inform treatment decisions.  The test has minimum genetic content and does not included unvalidated genes.

The Billing Article simply says "use appropriate CPT code" (!!! thanks) and Z code.

The Q&A notes that a draft exclusion of "test that includes genetic content considered harmful" was revised to 'test does not include content that is not properly validated" etc.


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AI Corner

I asked for re-write of the coverage criteria, for clarity.  At link.

https://brucedocumentblog.blogspot.com/2025/06/moldx-cardio-genetic-lcds-june-2025.html

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AI CORNER

For your curiousity only, here are Chat GPT summarizes of the LCDs.  Do not make any decisions except by reference to the original LCD text, not this AI summary.

Here is a summary of the two complementary MolDX Local Coverage Determinations (LCDs), L39950 and L39946, both effective July 27, 2025, for Medicare beneficiaries with cardiac conditions requiring genetic testing. 

These LCDs mark a significant expansion in Medicare coverage for cardiogenetic diagnostics.


1. L39950: Molecular Testing for Hereditary Transthyretin Amyloidosis (hATTR)

LCD Title: MolDX: Molecular Testing for Identification and Management of Hereditary Transthyretin Amyloidosis
Jurisdiction: Noridian MAC J-F (13 states, incl. WA, AZ, UT)

Covered Indications

Genetic testing is covered when the patient:

  • Has a clinical diagnosis or cardiac features suggestive of ATTR-CM, and

    • Is of African ancestry, or

    • Has a first-degree relative with hATTR, or

    • Displays features consistent with expert consensus or guidelines (e.g., neuropathy, autonomic failure)

  • Has sensorimotor/autonomic neuropathy plus relevant family history or clinical indicators

  • Has been counseled on test implications

  • Will use the result to inform treatment decisions

  • Receives a test with validated genes (minimum content includes TTR and possibly others)

  • Uses a test that has passed MolDX Technical Assessment

Clinical Rationale

  • hATTR is a treatable, underdiagnosed cause of cardiomyopathy and polyneuropathy.

  • The most common U.S. pathogenic variant, TTR p.Val142Ile, is highly prevalent (~3.4%) in African ancestry populations and primarily cardiac in expression.

  • Gene sequencing improves diagnostic accuracy, especially as clinical features overlap with other conditions (e.g., diabetic neuropathy, hypertensive heart disease).

  • The test supports earlier diagnosis and therapy (e.g., tafamidis, RNAi drugs like patisiran and vutrisiran).


2. L39946: Genetic Testing for Heritable Thoracic Aortic Disease (HTAD)

LCD Title: MolDX: Genetic Testing for Heritable Thoracic Aortic Disease
Jurisdiction: Noridian MAC J-F (same 13 states)

Covered Indications

Genetic testing is covered when:

  • The patient has aortic root/ascending aorta dilation, aneurysm, or dissection, and

    • Presents before age 60, or

    • Has syndromic features (e.g., Marfan, Loeys-Dietz, vascular Ehlers-Danlos), or

    • Has a family history of thoracic aortic disease, aneurysms, or sudden death

  • Counseling is provided

  • The test:

    • Covers the minimum validated gene set, including FBN1, TGFBR1/2, SMAD3, COL3A1, ACTA2, etc.

    • Excludes non-validated or unclear variants

    • Has completed MolDX Technical Assessment

    • Does not violate repeat germline testing policies (L38353)

Clinical Rationale

  • HTAD accounts for ~20% of thoracic aortic aneurysms (TAA).

  • Guidelines from the ACC/AHA (2022) and ClinGen strongly recommend genetic evaluation for younger TAA cases or syndromic/familial presentations.

  • Identifying pathogenic variants informs timing of surgery, surveillance strategies, and cascade testing.

  • Recognized gene panels influence decisions well before aortic diameter reaches generic intervention thresholds.


Summary Implications

Together, these LCDs establish broad Medicare coverage for two distinct forms of inherited cardiovascular disease:

  • One focused on amyloidosis of cardiac and/or neurologic origin (hATTR),

  • The other on genetic aneurysmal disease of the thoracic aorta (HTAD).

Both policies:

  • Require pre-test counseling, use of validated gene panels, and MolDX TA approval

  • Emphasize early intervention and family risk stratification

  • Are anchored in strong guideline support and target diseases with overlapping but misdiagnosed phenotypes

These LCDs will likely drive:

  • Expansion of NGS panels in cardiovascular practice,

  • Increased testing in Black Medicare populations (esp. hATTR),

  • Coverage for multigene panels aligned with ACC/AHA guidelines, and

  • Pressure for national harmonization of cardiac genetics coverage.

Let me know if you'd like side-by-side tables, CPT implications, or billing summaries.

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Disclaimer.  The AI summary is for curiousity only.  I haven't proofed it against every detail of the LCDs.

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I then asked Chat GPT to provide constructive criticism for the LCD author.

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Yes — both LCDs (L39950 and L39946) are generally well-aligned with clinical guidelines and thoughtfully written, but they do suffer from some recurring issues that may hinder clarity, consistent application, and efficient use by labs, clinicians, and payers. Here's a structured critique:


⚠️ Common Issues Across Both LCDs

1. Overly Verbose and Redundant Language

Both LCDs repeat ideas in multiple places, especially in the coverage sections. For example:

  • The need for counseling, minimum gene content, and test utility appears multiple times, sometimes with slightly different phrasing.

  • They mix clinical eligibility, test design requirements, and regulatory compliance into a single list, when they could be cleanly separated.

Impact: Slows comprehension and increases the risk that clinicians or test developers misinterpret which criteria are patient-facing vs lab-facing.


2. Vague Terms Without Operational Definitions

Both LCDs use terms like:

  • "Features consistent with expert consensus"

  • "Genes with definitive or well-established evidence"

  • "Properly validated" or "unclear clinical utility"

These phrases are not anchored to a specific source, leaving ambiguity:

  • Which specific guidelines qualify as “expert consensus”? ACC/AHA? ESC?

  • Which genes are deemed valid? The LCD references ClinGen in L39946 but does not give a list.

Impact: Creates interpretive flexibility that could lead to coverage disputes or inconsistent TA approvals.


3. Lack of Clarity About Single-Gene Testing vs Panel Testing

While both LCDs permit single-variant testing when a familial mutation is known, they don’t:

  • Clarify if this applies to duo/trio testing or reflex testing.

  • Clarify if limited panels (e.g. just TTR, or just FBN1/ACTA2) are acceptable for patients without known familial variants.

Impact: Labs may be uncertain whether they can offer targeted panels unless a family mutation is already known, potentially discouraging cost-effective testing.


4. Limited Guidance on Cascade or Family Testing

Both LCDs imply support for familial risk assessment, but do not clearly state:

  • Whether testing in asymptomatic relatives is covered

  • Whether cascade testing is included when the proband is Medicare-eligible

This is particularly relevant in L39946 (HTAD), where early detection in relatives can be life-saving.

Impact: May deter cascade testing or lead to unnecessary denials.


5. Technical Assessment (TA) Language Is Ambiguous

Both LCDs require that a test:

“has successfully completed a technical assessment (TA)...”

However, they don’t:

  • Define what the TA evaluates (analytical validity, clinical validity, or both?)

  • Link to a checklist or reference document explaining TA criteria

  • Distinguish between new and grandfathered tests

Impact: Adds friction for test developers seeking coverage, particularly new market entrants.


🔍 LCD-Specific Observations

📄 L39950 (hATTR)

  • The clinical phenotypes of hATTR-CM and hATTR-PN are mixed together in one long bulleted list. It would be clearer to break them into two distinct diagnostic pathways.

  • There's an overemphasis on detailed drug mechanisms and trials (tafamidis, acoramidis, RNAi agents). This may be more appropriate in a background article, not an LCD.

📄 L39946 (HTAD)

  • The LCD refers to ACC/AHA and ClinGen guidelines, but doesn’t specify a minimum list of genes (though it hints at 11 validated genes). A table of “required core genes” would enhance usability.

  • While it’s based on high-quality data, the gene–phenotype correlations are buried in long paragraphs that make it hard to parse actionable coverage implications.


What They Do Well

  • Align with current guidelines (especially 2022 ACC/AHA for aortopathies and hATTR diagnosis).

  • Emphasize clinical utility, not just analytic validity — a good signal for payers and clinicians.

  • Include appropriate flexibility for new evidence or guideline changes.


🛠️ Suggested Fixes

  • Help the reader - Streamline coverage criteria into 3 buckets: (1) Patient eligibility, (2) Test design, (3) Compliance.

  • Provide an appendix or hyperlink to required gene lists (ClinGen, ACC/AHA)

  • Clarify whether family member testing is covered when a proband has a known mutation

  • Offer TA submission guidance in a separate MolDX companion article


Would you like a suggested redraft of the coverage criteria section using these structural improvements?

Wednesday, June 11, 2025

Joe Grogan in WSJ: Time to Pull the Plug on "CED" in NCDs

Health policy expert Joe Grogan, of USC's Schaeffer Institute, pens an Op Ed in the WSJ today, arguing that it is time to pull the plug on the arthritic and outdated "Coverage with Evidence" era at CMS.

CED was the heart of the "TCET" Transitional Coverage for Emerging Technologies" framework from the recent Biden administration.

Find Grogan's article here.   (Grogan handled health policy for the White House in 2019-2020).

https://www.wsj.com/opinion/agency-overreach-leaves-patients-untreated-4ead2d0a


Here are some opening quotations:

Medical innovations remain stuck between FDA approval and full Medicare coverage. Of 27 medical devices covered under CED since 2005, four have “graduated” to unrestricted coverage. Two product decisions were ceded to Medicare’s regional administrative contractors. The other 21 remain in limbo. Implantable cardioverter defibrillators languished under CED for 18 years. How much data does CMS need?

The program’s fatal flaw stems from confusion about agency roles. The FDA evaluates safety and efficacy. CMS’s mandate is to determine whether a product or service is reasonable and necessary to diagnose or treat an illness or injury. CED gave CMS free range to infringe on the FDA’s authority with predictable results: slowing access and blocking patients and doctors from making informed treatment decisions.

The program is also outdated. Unlike in 2005, digital health data is ubiquitous. The FDA can employ real-world evidence and artificial intelligence to analyze millions of patients’ treatments. CED’s clinical trial constructs are obsolete.

CED also restricts access by location, favoring urbanites who live near large academic medical centers over rural Americans. CMS should dramatically reform its process for making coverage decisions, with an eye toward speeding up access for patients. After decades of disappointing results, CED has earned its place in the regulatory graveyard.

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Grogan does not mention, but where data is available, the program also strongly favored White participants (e.g. Amyvid PET trials).

Also not mentioned, there were publicly issued legal arguments against the use of CED in the 2020/2021 closing months of the prior Trump administration.  

In recent comments, ACLA described the NCD change process as intolerably slow - here.

See a 2024 paper, Roadmap for Improving CED, here.

Tuesday, June 10, 2025

Caris Files for IPO at $5B: Documentation Links; Key Quotations and Metrics

Update - 360Dx on IPO - June 18.  Here. Trading was around $28 (cap $7B), ticker CAI (as in, C+AI).  LinkedIn notes by Bowerman.

####

Caris Life Sciences has filed for an IPO, with a planned value of $424M, at a valuation per share of $16-18.  According to one summary, this yields a market cap of $4.8-5.3B.

See coverage at MedTechDive here:

https://www.medtechdive.com/news/Caris-Life-Sciences-files-424M-IPO/750341/

See also Axios here and Reuters here.

See the June 9 press release here:

https://www.carislifesciences.com/about/news-and-media/caris-life-sciences-announces-launch-of-initial-public-offering/

See the SEC Preliminary Prospectus (dated June 9) here:

https://www.sec.gov/Archives/edgar/data/2019410/000110465925057593/tm2415719-16_s1a.htm

For me the PDF of the web document tallies 364 pages.

Recall that Caris won FDA approval for its paraffin comprehensive genomic profiling test in November 2024; the assay includes a full transcriptome and whole exome sequencing.  Here.  See the extensive FDA documentation for the test (P240010) here.

##

Caris states it has:

  • Profiled 849,000 cases
  • Measured 38 billion biomarkers
  • Built 51 petabytes of genomic data
  • Utilized 220 AI tools
  • Digitized 4.4M slides
  • Now assesses 23,000 genes per order (RNA, WES)
  • 5,500 regularly ordering oncologists (> 4/yr)
  • 270 commercial sales force
  • 96 members of the Caris Precision Oncology Alliance
  • 200+  patents
  • 1700+ employees
  • 31% CAGR (case volume) 2019-2024.. Revenue CAGR 28%.


Caris opens its summary by stating:

  • We are a leading, patient-centric, next-generation AI TechBio company and precision medicinepioneer. We develop and commercialize innovative solutions to transform healthcare through the use of comprehensive molecular information and artificial intelligence/machine learning algorithms at scale. 
  • Our entire portfolio of precision medicine solutions is designed to benefit patients, with an initial focus on oncology, and serves the clinical, academic, and biopharma markets.

###

Caris states that its current MolDx pricing for LBx therapy selection (Caris Assure) is $3649.   By my tally, the word "MOLDX" occurs 37 times in the prospectus.

Topics like LCDs, NCDs (p. 40), crosswalk/gapfill, and PLA coding are discussed.  They note (page 217) that AMA issued a PLA code for MI Cancer Seek of 0211U which is priced by CMS at $8455.  

They add, "We have obtained Medicare coverage for MI Cancer Seek for CPT code 0211 under the NGS NCD" and that "we began to market MI Cancer Seek in the first quarter as the WES WTS NGS component of MI Profile."  

MI Profile

See the web page hereMI Profile is the full package and includes DNA, RNA, proteins (IHC).  When ordering MI Profile, Caris will perform MI Cancer Seek CDx.  But, if the sample does not qualify for the FDA CDx test, then they will run the comparable LDT, MI Tumor Seek Hybrid.

MI Profile will also run IHC on 25+ markers, CISH, pyrosequencing for MGMT methylation (for glioma), and AI signatures, which include Caris GPSai for CUP (cancer of unknown type) and Caris FOLFIRSTai for CRC cases.

Gapfill

Separately, they describe that AMA issued PLA code 0485U for liquid biopsy Caris Assure for therapy selection, which is being priced by "the gapfill method."  As released in April for public comment, the proposed national gapfill price is $3649 for 0485U.  See my April 2025 article on the gapfill process here.

Risks

As to risks, among other statements Caris remarks,
  • Third-party payers are increasingly attempting to contain healthcare costs by limiting both coverage of certain diagnostic tests and the amounts that they will pay for such tests. Payers may also create conditions for coverage or may contract with third-party vendors to manage laboratory benefits, in both cases creating administrative hurdles for ordering physicians and patients that may make our services more difficult to sell.....
  • Obtaining approvals from third-party payers to cover our existing and new solutions and establishing adequate coding recognition and reimbursement levels is an unpredictable, challenging, time-consuming, and costly process, and we may not always be successful. 
AI Corner (Not Guaranteed)

I gave Chat GPT the 364-page prospectus and asked the AI to read and summary Caris' AI strategy.  

I have not read the full prospectus, so I can't vouch for the summary, and I copy it below "as is" and "if of interest" only.

Based on the S-1 filing, Caris Life Sciences' AI strategy is a core pillar of its business model, deeply integrated into its clinical services, research tools, and pharmaceutical partnerships. Their approach can be described as a data-driven precision oncology platform, where AI and machine learning (ML) are used to unlock insights from complex multi-omic and clinical datasets at scale.


1. AI Strategy Overview

Caris has created a vertically integrated platform that generates, aggregates, and analyzes whole exome sequencing (WES), whole transcriptome sequencing (WTS), and matched clinical data. Their AI strategy focuses on:

  • Automating the interpretation of molecular profiles

  • Predicting therapeutic response

  • Identifying novel biomarkers

  • Supporting clinical decision-making and trial enrollment


2. Key AI Products

Caris offers several AI-driven tools that exemplify their strategic priorities:

  • DETECT: A proprietary dataset of over 1.6 million molecular profiles linked with detailed clinical outcomes. This forms the training and validation foundation for their AI models.

  • CODEai: A cloud-based analytics engine that allows pharma partners to explore the DETECT dataset using natural language processing and AI. It supports hypothesis generation, biomarker validation, and trial site selection.

  • Caris Molecular Artificial Intelligence (MAI™): A suite of AI-based predictive algorithms trained on WES/WTS and outcomes data. These models aim to:

    • Predict patient benefit from specific therapies (e.g., checkpoint inhibitors, EGFR inhibitors)

    • Classify cancer subtypes based on transcriptomic signatures

    • Forecast prognosis and therapy resistance

  • Biosimilarity AI Models: These include models that predict which therapy classes (not just individual drugs) a tumor is most similar to in terms of molecular response, which is useful when direct evidence is limited.


3. AI Infrastructure

Caris has made significant investments in AI infrastructure, including:

  • A dedicated bioinformatics and AI team of ~140 employees

  • A cloud-native architecture optimized for high-throughput computation

  • Integration of deep learning and natural language processing (NLP) models for data extraction, annotation, and hypothesis testing


4. Strategic Use Cases

Caris deploys its AI for both clinical and biopharma-facing applications:

  • In the clinic, MAI algorithms provide oncologists with therapy prediction scores and help interpret complex molecular data.

  • In biopharma, AI is used for:

    • Patient stratification and trial matching

    • Novel target identification

    • Biomarker-driven drug development support

They highlight AI as a tool to reduce time and cost in drug development and increase R&D efficiency for their pharma clients.


5. Differentiation

Unlike some peers that rely primarily on static gene panels, Caris emphasizes multi-omic breadth (DNA, RNA, protein) and AI-enhanced interpretation. This gives them a competitive edge in producing actionable insights from complex biology.


Summary

Caris’s AI strategy is tightly woven into its clinical, research, and business operations. By linking comprehensive WES/WTS data with real-world clinical outcomes—and applying robust AI/ML analytics—Caris positions itself not only as a test provider but as a molecular intelligence company that bridges diagnostics, therapeutics, and data science. This strategy underpins their goal of becoming a market leader in precision oncology and biomarker-driven drug development.

Reminder: AI summary offered "as is" and "for interest only."

##

##

Forbes ran a short profile of billionaire founder David Hilbert.

  • Acquired "Molecular Profiling Institute" in 2008
  • Raises $494M at value $7.4B, 44% of company = $3.3B
  • Revenue $412M, loss $282M.
  • Hilbert is 69, BA in business from Abilene Christian University.
  • Founded Advance PCS 1987, sold to Caremark in 2004 for $7.5B.
  • Investment firm Caris Capital = $1.2B assets.
  • In May 2021 [covid bubble] raised $830M led by Sixth St (value $7.8B)