Thursday, October 29, 2026

All About the Precision Medicine World Conference - Santa Clara - Jan 27-29, 2027

 


For the Precision Medicine World Conference - 3 days at the end of January 2027 -here's the website:

https://pmwcintl.com/

And here's the agenda:

https://pmwcintl.com/program/


I'm on a panel this year.  The panel is chaired by Gabriel Bien-Willner, and includes Dawn Cardeiro of Roche Diagnostics, Stacey Brown of Cepheid, and Asad Ali Ahmad of Network Bio. Friday, 2 pm, track 3, session 3.  From Signal to Standard of Care: What makes a non-cancer blood test actionable?

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AI CORNER

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PMWC 2027: A Detailed Guide to the Conference and Its Agenda

 

The Precision Medicine World Conference returns to Santa Clara January 27–29, 2027, bringing together researchers, clinicians, diagnostics developers, biotechnology companies, investors, and policy specialists. Its agenda spans artificial intelligence, cancer detection, advanced therapeutics, genomics, and emerging applications beyond oncology. For prospective attendees, the central attraction is the opportunity to examine how promising technologies become useful, accessible, and financially sustainable care. Precision Medicine World Conference, Jan. 27-29

What kind of conference is PMWC?

The Precision Medicine World Conference, usually called PMWC, is a three-day meeting about the science, technology, and business of tailoring healthcare to individual patients. Formerly known as the Personalized Medicine World Conference, it began in 2009 under founder and president Tal Behar, working with Stanford Health Care. The 2027 Silicon Valley meeting is scheduled for January 27–29 at the Santa Clara Convention Center, with Stanford, UCSF, and Yale identified as co-hosts. PMWC LLC organizes the event. pmwcintl.com

The conference brings several professional communities into the same setting. Academic investigators describe discoveries; biotechnology and diagnostics companies discuss development and commercialization; clinicians and health-system leaders consider adoption; investors evaluate opportunities; and policy specialists examine access and payment. That mixture gives the meeting particular relevance to people whose work crosses institutional boundaries. A laboratory developing a new assay, for example, may need conversations about clinical evidence, physician use, reimbursement, and financing as much as it needs feedback on the assay itself. pmwcintl.com

The organizers advertise more than 3,000 attendees, 400 speakers, and 150 sponsors for 2027. These are promotional figures rather than independently verified attendance totals. The announced speaker and honoree roster includes Emmanuelle Charpentier, David Baker, Mary-Claire King, Eric Lander, Fei-Fei Li, Andrew Ng, Eric Horvitz, and Daphne Koller. The breadth of that roster illustrates the conference’s combination of molecular medicine and computation. Precision Medicine World Conference, Jan. 27-29

The format includes five main tracks, two company showcase tracks, exhibits, award presentations, and networking receptions. The main tracks contain scientific, clinical, and industry discussions; showcases emphasize company technologies and projects. PMWC also offers a startup competition, renamed in 2026 to honor Atul Butte. Its commercial orientation is explicit and useful for interpreting the meeting: attendees will encounter research presentations alongside product positioning and business development. PMWC Precision Medicine World Conference

For a first-time visitor, the main practical challenge is selection. Multiple simultaneous sessions mean that even an attendee staying all three days will see only part of the program. Prospective participants would benefit from identifying a few central questions and arranging relevant meetings before arrival. A particularly strong use of PMWC is to connect a scientific development with the clinical and commercial decisions that determine whether it reaches patients.


The 2027 agenda

The advertised 15-part program consists of five main tracks, each with a different theme on each of the three days. The company showcases are additional. The following descriptions summarize the posted program as reviewed on October 29, 2026; individual sessions and speakers remain subject to change. pmwcintl.com

1. Advanced therapeutics

Track 1 progresses from engineered cell and gene therapies on Wednesday to immunotherapies and targeted treatments on Thursday, then genetic and RNA medicines on Friday. The program covers competing cell-therapy approaches, manufacturing, delivery into the body, treatment resistance, patient selection, genome editing, and RNA splicing. Listed participants across this area include Katy Rezvani, David Miklos, Antoni Ribas, Emmanuelle Charpentier, Adrian Krainer, and Randy Schekman. LinkedIn

The notable feature is the attention to development constraints. Manufacturing and delivery can determine whether a persuasive biological idea becomes a practical treatment. Sessions addressing individualized therapies also raise a consequential question: how much evidence and infrastructure can be shared across treatments that differ from one patient to another? For biotechnology executives and translational researchers, these discussions may offer more actionable information than a broad survey of new therapeutic mechanisms.

2. Artificial intelligence and computational medicine

Track 2 follows AI through three different settings: diagnosis on Wednesday, clinical deployment on Thursday, and drug discovery on Friday. Diagnostic topics include computational pathology, AI-supported companion diagnostics, genomic interpretation, and combinations of different data types. Thursday includes clinical agents, foundation models, real-world evidence, and AI governance. Friday features computational protein design and drug-development discussions, with David Baker and Daphne Koller among the advertised participants. PMWC Precision Medicine World Conference

This structure helps separate questions that are often bundled together under the label medical AI. A system that interprets a pathology image, one that supports clinical work, and one that proposes a drug target face different tests of usefulness. The clinical program’s inclusion of evaluation and governance suggests that deployment experience will be an important counterweight to demonstrations. Drug-discovery attendees can look for evidence about experimental validation and development success, beyond improvements in computational prediction.

3. Precision diagnostics

Track 3 offers an especially coherent three-day sequence for laboratory and diagnostics audiences. Wednesday addresses early detection and intervention, including risk-based screening, precancerous disease, and the integration of molecular and imaging signals. Its opening discussion reassesses the accomplishments and shortcomings of the first generation of early-detection approaches. The listed contributors include Victor Velculescu, Rebecca Fitzgerald, Nickolas Papadopoulos, and Phil Castle. PMWC Precision Medicine World Conference

Thursday turns to liquid biopsy for treatment selection and monitoring. Topics include whether molecular residual disease, or MRD, should guide additional treatment; how blood tests can identify response and resistance; how tissue, blood, and imaging information should be reconciled; and whether MRD can support accelerated drug approval. Max Diehn and Sarah-Jane Dawson are among the featured investigators. The drug-endpoint session lists Ash Alizadeh as chair and participants including Ola Landgren, Chris Hourigan, and Aparna Parikh. PMWC Precision Medicine World Conference

Friday expands beyond cancer to transplant monitoring, infectious-disease testing, and maternal and fetal health. It also addresses the clinical actionability and reimbursement of non-cancer blood tests. The posted agenda lists Bruce Quinn among the participants in that discussion, chaired by Gabriel Bien-Willner. PMWC Precision Medicine World Conference

The diagnostic track’s strongest analytical thread is the connection between a test result and a subsequent decision. Early detection raises questions about whom to test and what follows a positive result. Monitoring raises questions about when treatment should change. A drug-trial endpoint raises another question: what does a biomarker establish about treatment benefit? These distinctions make the track relevant to clinical-development and market-access teams as well as assay developers.

4. Genomic medicine and implementation

Track 4 begins with genomic diagnosis and broader measurement of human health, including unresolved genetic disease, population and newborn screening, and structural variants. Thursday focuses on implementing precision medicine across healthcare organizations. Friday examines aging, prevention, and healthspan, including metabolic interventions, biological measurements, and digital monitoring. Eventbrite

The Thursday implementation program deserves particular attention from readers concerned with adoption and reimbursement. A session titled “What Gets Covered and Why” lists Dan Knecht, Mike Montalto, Tamara Syrek Jensen, and Shane Mull. Other discussions address operating models, clinical decision support, and the transition from biomarker evidence to routine care. These topics recognize that clinical adoption requires coordinated changes in payment, information systems, and professional practice. PMWC Precision Medicine World Conference

The aging program warrants a different evaluative lens. Attendees can look for a clear account of what a proposed measure changes in clinical care, how an intervention will be evaluated, and which outcomes matter to patients. The inclusion of aging alongside established genomic medicine creates opportunities for comparison, but the maturity of the evidence will differ across individual applications.

5. Spatial biology and disease applications

The new fifth track covers spatial biology on Wednesday, autoimmune and inflammatory disease on Thursday, and neurology on Friday. Spatial biology studies cells and molecular signals in their tissue context. The program connects that approach with digital pathology and biomarker development, then considers immune-directed therapies and biomarkers across autoimmune disease. pmwcintl.com

Friday’s neurology program includes Alzheimer’s blood biomarkers, other neurodegenerative disorders, imaging, digital measurements, and barriers to broader clinical adoption. Henrik Zetterberg, David Holtzman, Li-Huei Tsai, and David Liebeskind are among the leaders highlighted in the organizer’s neurology materials. The stated emphasis on treatment selection and access makes this more than a survey of biomarker discovery. pmwcintl.com

The broader significance of this track is the extension of precision medicine into diseases where patient classification, treatment selection, and longitudinal monitoring are developing along different paths from oncology. Attendees interested in translating an approach from one specialty to another can examine which assumptions survive the move and which require new evidence.

What the agenda suggests about the field

Taken together, the program suggests a field increasingly occupied with the consequences of its own technical progress. More sensitive assays, richer biological data, and more capable AI systems expand what can be measured or predicted. The conference repeatedly returns to the harder question of what healthcare should do with that information. This is an interpretation of the agenda, rather than a claim that the scheduled discussions will resolve those problems.

Three connections are especially useful for prospective attendees.

First, diagnostics and therapeutics are becoming harder to discuss separately. A screening test needs a credible follow-up pathway; an MRD result needs a defined decision; a targeted therapy needs a workable patient-selection strategy. An attendee who crosses between the diagnostic and therapeutic tracks may gain more than one who stays within a familiar technology category.

Second, evidence is becoming a shared concern across AI, laboratory medicine, and health-system implementation. The relevant questions include whether a finding generalizes, whether it changes practice, and whether the resulting change benefits patients. Reimbursement discussions add a practical perspective: what evidence would justify paying for that use? The agenda offers opportunities to compare those standards across specialties, while leaving room to question whether a company’s preferred evidence answers the purchaser’s question.

Third, the expansion into aging, immunology, and neurology makes careful comparison of development stages essential. A scientific mechanism, a validated measurement, a clinically useful test, and an adopted service represent different achievements. The presence of all four at one conference can be informative, provided attendees keep those distinctions in view.

Who is likely to benefit?

PMWC appears particularly well suited to diagnostics developers, biotechnology leaders, translational researchers, investors, and professionals working on clinical implementation or market access. Its breadth may also benefit clinicians seeking a view of technologies moving toward their specialties. Attendees seeking extended instruction in one technical method, or a detailed course in Medicare coding and payment mechanics, should inspect individual sessions closely before deciding whether the program meets that narrower need.

The meeting is in person, with no livestream announced. A full conference pass covers all three days, the main and showcase tracks, exhibits, and receptions. Eligible recordings and slides are offered afterward, subject to speaker permission. The organizer does not offer separate one-day or exhibit-only passes and advertises reduced rates for eligible academic, government, nonprofit, and student attendees. Current prices and participation details are available through the registration page. PMWC Precision Medicine World Conference

For readers weighing the trip, the most useful test is whether the agenda brings together the people and questions needed for a current project. A short list of relevant sessions, several planned conversations, and time reserved to explore an adjacent field would give attendance a clear purpose.

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Compare the agendas for 2024 and 2027..

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Comparing 2024 and 2027 at the PMWC

Comparing PMWC’s 2024 and 2027 agendas reveals continuity, but a sharper emphasis on clinical decisions, implementation, and expanding precision medicine beyond its established domains.

The foundation remains recognizable: cell and gene therapies, oncology, liquid biopsy, genomic analysis, artificial intelligence, and commercial showcases. Neither AI nor implementation suddenly arrived in 2027. The 2024 program already included foundation models, computational pathology, deployment barriers, reimbursement, and real-world evidence. The change is one of specificity and organization.

AI shows the clearest evolution in vocabulary and ambition. In 2024, many sessions emphasized data sharing, harmonization, privacy, and exploring AI’s potential. By 2027, clinical agents, multimodal diagnostics, enterprise deployment, and governance occupy prominent positions. Drug discovery increasingly asks whether computational predictions survive experimental validation and improve development outcomes. The discussion has moved toward evaluating systems that institutions might actually purchase and operate.

Diagnostics similarly becomes more explicitly decision-oriented. The 2024 liquid-biopsy program surveyed clinical status, prevention, and multicancer detection. The 2027 agenda asks whether MRD should trigger additional treatment, when resistance should prompt a therapeutic switch, and how conflicting tissue, blood, and imaging results should be reconciled. MRD as an endpoint for accelerated drug approval receives explicit attention. Screening remains important, but its consequences and limitations receive more pointed examination.

Several subjects lose standalone prominence. Pharmacogenomics occupied an entire day in 2024, with substantial attention to standardization, education, ordering, and reimbursement; it persists in 2027 without comparable billing. Women’s health and biological sex differences also lose their dedicated day, although maternal and fetal diagnostics remain. Infectious disease and microbiome topics are redistributed into broader diagnostic and immunology programs. These are changes in conference emphasis, not evidence that the fields have stalled.

The largest expansion is a fifth main track covering spatial biology, precision immunology, and neurology. Aging and healthspan also gain a dedicated day. Therapeutics places greater emphasis on programmable medicines, delivery, and manufacturing. 

Collectively, the agenda suggests growing interest in connecting biological measurements to interventions and workable care pathways. For returning attendees, the strongest reason to return is the opportunity to examine those connections across specialties, rather than simply revisit familiar technologies with newer examples.



Journal of Pathology Informatics: How Momentum Changed from 2022 to 2026

 A companion blog discusses the excellent Michagan conference, December 10-12, 2026, sponsored by Association for Pathology Informatics.

Here, we take a deep dive, reviewing the Journal of Pathology Informatics publications in 2026,  We used the same framework to take a look-back to 2022.  Finally, we discusses changes in interest, momentum, and emphasis.




Find the white  paper PDF in the  cloud,  HERE.

This three-part review argues that digital pathology's central challenge has shifted from proving technical feasibility to achieving widespread, sustainable clinical adoption. Comparing Journal of Pathology Informatics publications from 2022 and 2026 reveals remarkable advances in AI, foundation models, interoperability, and clinical implementation. Yet technological progress continues to outpace practical integration. 

iThe next breakthroughs may depend less on better algorithms than on complete AI-assisted diagnostic workflows, intuitive and empowering human interfaces, convincing economic benefits, and regulatory and reimbursement policies that support adoption rather than obstruct it.


Digital Pathology Gets Real: A Timely December Workshop at Michigan Medicine / Dec 10-11-12

 

Digital Pathology Gets Real: A Timely December Workshop at Michigan Medicine / Dec 10-11-12

Byline: Chat GPT 6 (Los Angeles, October 29)

An unusually practical conference on digital pathology and AI arrives as CAP and DPA join forces and federal regulators reconsider longstanding approaches to laboratory oversight and reimbursement.

Digital pathology is entering a new phase. After years of advances in whole-slide imaging, computational pathology, and artificial intelligence, the field faces increasingly difficult questions about clinical implementation, workflow, regulation, and reimbursement.

Against this backdrop, the Association for Pathology Informatics (API) will hold its Inside the Digital Lab 2026 workshop at Michigan Medicine, University of Michigan, December 10–12, 2026, in Ann Arbor.  The conference is circa $900 (varies with time and registrant type).  Thursday evening December 10 is a reception. 

The program is particularly appealing because it emphasizes what happens when digital pathology moves beyond demonstrations and research studies into the daily operations of a major medical center. Attendees will hear from experienced implementers, tour a functioning digital pathology laboratory, and operate actual digital sign-out workstations.

Conference program and detailed agenda

Registration



A Timely CAP–DPA Partnership

The conference follows an important development in the pathology community. On October 23, the College of American Pathologists (CAP) and the Digital Pathology Association (DPA) announced a memorandum of understanding establishing a formal collaboration through December 2029.

The agreement addresses interoperability, standards, workforce development, education, regulatory and reimbursement advocacy, and verification frameworks for whole-slide imaging and AI.

The partnership is particularly welcome because digital pathology faces a complicated federal policy environment. In July, CMS and CDC issued a request for information on updating CLIA regulations, including oversight of AI and digital diagnostic technologies. CMS has also proposed major changes to Medicare reimbursement for Software as a Medical Service (SaMS), including moving selected algorithmic laboratory services outside traditional Clinical Laboratory Fee Schedule payment pathways.

These changes could have far-reaching consequences for clinical laboratories and developers of computational pathology services. Whether CMS's proposed approach is well suited to pathology remains highly debatable.  Changes pending at AMA are also critical (like a revised Appendix S on coding digitally intensive service and a new code schedule "CMAA.") 

Previous articles in Discoveries in Health Policy have discussed the CLIA modernization RFI and CMS's proposed reclassification of digital pathology services.

The CAP–DPA collaboration is separate from API's Michigan workshop, but the developments are complementary. One strengthens the profession's capacity to address common policy challenges; the other provides an unusually valuable opportunity to explore the practical realities of clinical implementation.

CAP announcement of the CAP–DPA agreement

Inside the Digital Lab: The Michigan Experience

The heart of the conference is Friday morning's program, led by Drs. Ulysses Balis and Mustafa Yousif of Michigan Medicine.

Their opening presentation, "The Michigan Model: Building a Fully Digital Pathology Department at Enterprise Scale," describes the institution's approach to comprehensive digital primary diagnosis.

Even more distinctive is the subsequent 2½-hour laboratory tour, "From Glass to Pixels."

Participants will follow a specimen from grossing and slide preparation through digitization and clinical interpretation. They will observe laboratory staff, explore digital viewing stations configured for ten pathology subspecialties, and have the opportunity to navigate cases at workstations equipped with full sign-out capability.

This hands-on experience should be a major attraction for institutions considering or expanding digital pathology. Technical specifications and vendor demonstrations are important, but they cannot fully convey what it takes to make an integrated digital workflow function every day.

Friday: Scaling Up, Interoperability, and Long-Term Sustainability

Friday afternoon contains two sessions addressing challenges that become increasingly important as digital pathology moves into routine practice.

The first focuses on scalable deployment of image management systems and AI.

  • Balis and Yousif discuss the "last mile" of implementation: tools that turn a digital pathology platform into a complete clinical workflow.

  • Larissa Furtado (Penn Medicine) presents a practical lifecycle framework for AI-based clinical assays, from concept to clinical reporting.

  • Juan C. Santa-Rosario (CorePlus) discusses building a scalable digital pathology and AI ecosystem.

A second session addresses lifecycle management, interoperability, and institutional sustainability.

  • Rebecca Rojansky (Stanford) examines how existing pathology infrastructure can evolve to support clinical AI.

  • Andrew Evans and Jim Tsourgiannis (Mackenzie Health) tackle the difficult subject of replacing digital pathology platforms without sacrificing previous institutional progress.

  • Keluo Yao (Cedars-Sinai) discusses cytopathology in an era of disruptive digital pathology and AI technologies.

Both sessions conclude with extended panel discussions.

The topics are well chosen. Digital pathology is not simply a matter of purchasing scanners and installing software. It requires durable clinical infrastructure, reliable interoperability, and the ability to accommodate evolving technology without repeatedly rebuilding the laboratory.

Saturday: From AI Hype to Practical Implementation

Saturday's session, "Hype, Hope, Horror, and the Here and Now: Exploring the Promise of Agentic AI Within the Lab," examines a particularly fast-moving area of computational pathology.

Three speakers address this subject:

  • Matthew Cecchini (Western University): "Human Brilliance, Augmented: Building Agentic Workflows One Tile at a Time."

  • Jochen Lennerz (Natera): "The Final Adaptation of Routine AI."

  • Jitin Makker (UCLA Health): "Agentic AI in the Pathology Lab: From Hype to Practical Implementation."

Lennerz recently emphasized the significance of this transition in a LinkedIn commentary promoting the meeting. He argued that the critical challenges for clinical AI are shifting away from technical performance alone toward regulation, reimbursement, laboratory workflows, quality management, and workforce adaptation.

He also provided a useful preview of his presentation: three practical stories drawn from academia, industry, and professional advocacy.

Lennerz has separately written about the economic implications of CMS's proposed SaMS framework, arguing that reimbursement systems designed around conventional services and material resources may not adequately capture the value of clinically useful algorithmic analysis.

His perspective nicely captures the larger theme of the Michigan meeting. The question is increasingly not just whether AI can perform an impressive diagnostic task, but how it can be integrated, supervised, financed, and maintained in routine medical practice.

Why This Meeting Matters

One of the striking features of the Michigan agenda is its breadth within a tightly focused, practical program. It combines laboratory operations, enterprise implementation, AI assay development, interoperability, system replacement, cytopathology, and agentic AI.

Equally important, it draws on experience from academic medical centers, community and commercial settings, and industry.

The timing is excellent. Digital pathology is advancing rapidly, but the regulatory and reimbursement environment remains unsettled. The new CAP–DPA collaboration offers an opportunity for more coordinated professional leadership, while the API workshop provides a close look at how digital pathology can actually work at scale.

For pathologists, laboratory leaders, informaticians, and AI developers, the Michigan meeting promises something more valuable than another demonstration of technological possibility: a serious examination of what it takes to make digital pathology work in the real world.


Conference Information

Inside the Digital Lab 2026 — Michigan Medicine

Dates: December 10–12, 2026
Location: Ann Arbor, Michigan; meeting sessions at The Vanguard Hotel, with laboratory tours at Michigan Medicine's North Campus Research Complex.

Conference overview:
https://www.pathologyinformatics.org/inside-the-digital-lab-idl-2026

Detailed agenda:
https://www.pathologyinformatics.org/idl-2026-schedule

Registration:
https://www.pathologyinformatics.org/idl-2026-registration

CAP–DPA partnership announcement:
https://www.cap.org/news/cap-and-dpa-join-forces-to-advance-digital-pathology-and-artificial-intelligence/



See a review that compares momentum and trends in J Pathol Informatics, 2022 versus 2026.  Here.

Wednesday, October 28, 2026

GenomeWeb Makes PAMA’s Impact Personal—with a Downloadable Spreadsheet

 

GenomeWeb Makes PAMA’s Impact Personal—with a Downloadable Spreadsheet

The reporting: substantial cuts, and uncertain relief

Chat GPT 6 (Los Angeles, October 28)

GenomeWeb’s October 27 coverage pairs Adam Bonislawski’s reporting on looming PAMA cuts with a companion “By the Numbers” data feature. Together, they translate a national reimbursement debate into estimated consequences for individual laboratories and providers.

Bonislawski reports that approximately 1,700 independent laboratories face Medicare payment reductions in 2027, with more than 80 laboratory companies projected to lose at least $1 million. Quest Diagnostics and Labcorp each face roughly $100 million in cuts. Physician practices and pathology groups also face reductions, while contracts tied to Medicare rates could amplify the financial impact.

The policy story centers on the industry-backed RESULTS Act (HR 5269), which would use a third-party private-payor claims database to establish rates. Industry representatives argue that this would improve market representation and moderate cuts. Congressional budget scoring remains pivotal, and another temporary postponement may prove less politically attractive if it carries a budgetary cost.  

The innovation: reporting readers can investigate

A downloadable XLS adds practical value

The creative feature is GenomeWeb’s premium-subscriber spreadsheet, offered alongside the reporting and through a separate data article. GenomeWeb discloses that AI helped combine the datasets, with manual confirmation of clinical-laboratory figures and spot checks for other providers.  

The seven-tab workbook includes approximately 150,000 provider records, laboratory parent-company totals, state and provider-type summaries, and projected rate changes through 2029 and full phase-in. Readers can locate a laboratory, compare organizations, or explore geographic exposure themselves. This is a novel, useful extension of trade journalism: the downloadable analysis becomes a reusable research resource.  

Estimates, with explicit boundaries

The projections hold 2024 utilization constant, apply preliminary rates, and underrepresent hospital outreach programs. Subsequent acquisitions, closures, and changing test volumes can therefore alter actual results.

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BQ: Find lab-by-lab CMS payments in the cloud at CMS - here.

SOURCES

Article, By the numbers...

https://www.genomeweb.com/business-news/reimbursement/gnw-data-pama-2027-impact-2026-1014/

Article, Thousands of labs...

https://www.genomeweb.com/business-news/regulatory/cms/gnw-congress-pama-results-cms-20261027/

Both end with links to XLS.


Tuesday, October 27, 2026

PAMA Bizarre Patterns Revisited: When Outliers Drive Your Cash Flow

 A week ago, we used PAMA raw data to show not just the median price for codes, but the actual distribution of  payments (normal vs bimoda vs skewed left or right, etc).  Blog here.   In a later blog, we wondered if accusations (from employers) that United Healthcare was overpaying some providres, might be related to the most extreme prices seen on the far-right column of our bar charts.  Blog here.

I've now had Chat GPT re-run the raw data.  

First chart. In each triplet of charts, the top chart (all in blue bars) is the number of paid claims in each "bin" of price ($100-200, $201-300, etc.)  Price distributions are very broad; for 81408, from $5 to $2100 per unit test (median $477).  The ratio of highest-paid claim to lowest-paid was 40X.  

Then, for the second and third bar charts, the Y-axis is no longer test volumes, but actual revenue dollars.  (For example, 10 units of a $100 test is "10" on first chart, but the revenue of the test is $1000, on 2nd and  3rd charts).  

Finally, for the third bar chart, we arbitrarily assumed that 35% of the median price (the CLFS price) is a ballpark number for COGS.  We subtracted that, so in the third bar chart the Y axis is still dollars but now as contribution margin (revenue - COGS).

81513 (Example)

For example. for code 81513, "Aptima BV," price bins run from $0-$50 up to $200-plus.  

"Bin $200-plus" is only 6.9% of unit volume, but brings 38% of revenue (payments), and brings  almost half (48%) of contributio margin.  That means: for 81513 data, 7% of claims paid at top-end prices are half of profit.

click to enlarge or download PDF set

See a full set of examples in PDF format HERE.

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For more PAMA MATH, see two articles at Genomeweb.



By the numbers...

https://www.genomeweb.com/business-news/reimbursement/gnw-data-pama-2027-impact-2026-1014/

Thousands of labs...

https://www.genomeweb.com/business-news/regulatory/cms/gnw-congress-pama-results-cms-20261027/

Includes subscription download XLS...






Employers Sue United Healthcare: Does It Overpay Providers??

 Header:  A large group of employers sues United Healthcare, asserting it overpays providers when it is merely dolely out third-party administrator payments (the employer's money.)  They say it is more careful when it is acting as an insurer and paying its own money.   ?Could this show up as high-end payments for lab tests (e.g. $200 for $10 test) in PAMA data?

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  • See Benefits Digest [open] here.
  • See Beckers [open] here.
  • See Insurance Newsnet [open] here.
  • See Bloomberg Law [firewall] here.
  • See Law360 [firewall] here.
  • Find the case, Eastern District Texas, 62pp, here.
    • Aramark Services, Inc., et al. v. United Health Group Incorporated, et al.
    •  2:26-cv-009490JRG
    • Filed on October 20, 2026, redacted.  [PDF link via Benefits Digest]
AI note: I asked AI to look for articles, put them in a table, flag if firewalled, and find any that included a court case PDF link.

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See 7 page PDF report in cloud, HERE.


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I recently published a blog showing how strange the PAMA price survey distributions can be, including odd outliers (e.g. $200 payment for $10 test).  Blog here.



Obviously, when you subtract COGS from each claim, the far-right, top-end payments provide a much larger contribution to the profit per case (gold bars). 

click to enlarge

In a cartoon example above, a test has one PAMA payment at $50, 10 at $100, one at $500, and COGS is $50.  The ten tests contribute $500 margin, the one high test contributes $450 margin just by itself.

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AI Corner: Chat GPT 6

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1 From payment distributions to laboratory economics

What a median cannot show

Bruce Quinn’s recent PAMA analysis illustrates the starting point. Distributions of reported private-payer rates for selected laboratory codes show patterns that a single average or median cannot communicate. Some rates cluster tightly; others are widely dispersed or have multiple concentrations. A billing code is a useful unit of comparison, although it does not always identify an identical assay, service configuration, or contractual setting.

The next analytical step is to distinguish three quantities: the number of tests at each price, the total dollars associated with those tests, and their contribution after an explicit cost assumption. In PAMA reporting, a data row can represent a rate and an associated volume. Counting rows therefore does not necessarily count tests. The calculations should use each exact reported rate multiplied by its reported volume, then aggregate those amounts into display bins. CMS also includes applicable patient cost sharing in reported private-payer rates, so those dollars should not automatically be described as payments made entirely by insurers. CMS reporting guidance

How a small number of claims can drive contribution

Consider an intentionally simple example: one test is paid at $50, ten at $100, and one at $500. Assume a median payment of $100 and a cost of $50 for each test. The twelve tests generate $1,550 in payments and $950 after subtracting the assumed $600 cost. The single $500 payment represents 8.3% of test volume, 32.3% of payments, and 47.4% of contribution after assumed cost.

If that one payment fell from $500 to $100, total contribution would fall from $950 to $550, a decline of 42.1%, with no change in test volume or assumed cost. A payment below $50 would make a negative contribution in this model. These are illustrative calculations, not estimates of any laboratory’s actual margins. Contribution here means payment less the stated cost assumption, before overhead; it is not net profit or net cash flow.


 

click to enlarge

The same calculation can be performed on hundreds of exact dollar-and-cent rates without replacing them with bin midpoints. An open-ended category such as “more than $1,000” presents no difficulty when the underlying prices remain available. But a national distribution cannot establish which laboratory receives the high payments, what its costs are, or why those rates exist. A high-price tail identifies a question for investigation; it does not establish an overpayment.

2 Employers challenge UnitedHealth

TPA versus insurer and who bears the risk

The employer dispute brings that question into a different setting. A third-party administrator, or TPA, administers a health plan: it processes claims, applies coverage and payment rules, and arranges payments. In a self-funded employer plan, the employer or plan bears the covered claim costs. In a fully insured arrangement, an insurer receives premiums and bears the contractual financial risk of covered claims. The same corporate group can serve as a TPA for some employers and as an insurer for others. The distinction concerns its role in the particular arrangement.

The case and the parties

That distinction is central to Aramark Services, Inc., et al. v. United Health Group Incorporated, et al., No. 2:26-cv-00949-JRG, in the Eastern District of Texas, Marshall Division. The 62-page redacted complaint, filed as Document 3 on October 20, 2026, brings together Aramark, Whirlpool, W.W. Grainger, Kraft Heinz, Ralph Lauren, and Sterling Jewelers, along with associated plans and benefit committees. Defendants include UnitedHealth entities, Healthscope Benefits, and United Medical Resources, commonly known as UMR.

The plaintiffs allege that United administered their self-funded plans, improperly approved claims, extracted undisclosed compensation, and obstructed oversight. They say the resulting losses amount to millions of dollars. These are allegations in a complaint, not judicial findings. United disputes them; in a statement reported by InsuranceNewsNet, the company said, “We strongly disagree with these allegations and intend to vigorously defend against them.” Many contractual passages and transaction amounts are redacted, which limits independent evaluation of the public pleading.

3 Inside the complaint

Alleged payment errors and inadequate review

The complaint describes specific alleged failures beyond a general objection to high medical prices. It alleges payments for claims with missing or invalid billing information, high-value claims paid without supporting medical-record review, and services excluded under the particular plans. It also describes inconsistent claims that would require comparison across related bills. One example concerns infusion services allegedly paid twice for the same member and date, under different claim identifiers, without evidence of a separate infusion. The dollar amount of that example is redacted. (Complaint, paragraphs 62–72, pages 22–25.)

The pricing allegations are particularly relevant to the distribution analysis. The employers say that even the limited data available revealed hundreds of payments exceeding the provider’s billed amount and thousands of claims paid at allegedly excessive rates. They compare payments with amounts the provider ordinarily received, commercial network prices, and Medicare rates. Those comparisons are investigative benchmarks; a payment above Medicare or above a statistical median does not, by itself, establish a contractual violation. The applicable coverage rules, contract, coding, and circumstances still matter. (Paragraphs 73–75, page 26.)

The employers also allege that United applied less scrutiny when spending self-funded plan assets than when paying claims for its own fully insured business. They describe extensive automated adjudication with little meaningful human review. Automation itself is not the legal issue. The allegation concerns whether the administrator used adequate controls and fulfilled its obligations when approving payments with plan money. (Paragraph 40, page 15; paragraphs 107–109, pages 38–39.)

Another striking allegation concerns what the complaint calls provider “exclusion lists.” In this context, the term means exclusion from some claims scrutiny. The employers contend that United offered certain providers little or limited review as an inducement to join its network, without informing the employer clients. The complaint expressly says discovery will establish the use of these arrangements. That wording matters: the allegation is presented partly as something the plaintiffs expect to substantiate through litigation. (Paragraphs 110–112, pages 39–40.)

What the complaint says about laboratories and genomics

Laboratory providers are mentioned, but the public complaint does not present a laboratory or genomics case study. Paragraph 82, on page 29, includes laboratory service providers among the healthcare businesses United allegedly owns through affiliates. The next paragraph alleges that the plans paid United-owned providers unjustifiably high rates compared with independent providers. The plaintiffs acknowledge that restricted data access has prevented a robust comparative analysis. The public text does not identify a particular laboratory test, genomic assay, sequencing service, or PAMA payment distribution as evidence. Its laboratory relevance is therefore both explicit, through the reference to laboratory providers, and analytical, through the broader questions about payment and ownership incentives.

Cross-plan offsetting and who receives the recovery

The complaint’s treatment of cross-plan offsetting explains why following the money matters. Its example begins with a doctor receiving $1,000 from an employer plan for a service later determined to warrant $600. United allegedly recovers the $400 difference by reducing a subsequent payment to the same doctor for a patient in a United fully insured plan. Instead of paying the doctor $600 on that second claim, United pays $200. According to the example, the original employer plan receives no $400 credit; United’s insured business benefits from the reduced payment. This is the complaint’s explanatory illustration, not a separately established transaction. (Paragraphs 85–92, pages 30–33.)

The issue is which plan receives the benefit of a recovery. The complaint invokes Peterson v. UnitedHealth Group, a 2019 Eighth Circuit decision. That court rejected United’s interpretation of the plan language at issue as authorizing cross-plan offsetting and discussed the fiduciary concerns it creates. It did not decide that every possible cross-plan offset violates ERISA. The present employers challenge both the handling of their money and the adequacy of contractual authorization and disclosure.

Repricing fees and the meaning of savings

The allegations about out-of-network repricing and “shared savings” fees add a further complication. The plaintiffs say United used repricing vendors, including MultiPlan, to negotiate provider payments and charged fees calculated from the difference between a provider’s billed charge and the amount ultimately paid. They argue that the billed charge could substantially exceed what the plan was ever obligated to pay, making the claimed savings an inflated basis for compensation. Some plan provisions, they say, already limited benefits using Medicare-based or other benchmarks. (Paragraphs 93–102, pages 33–36.)

The employers further allege that these fees sometimes exceeded the provider’s payment and were concealed within claim-funding requests or disclosed only in aggregate. This aspect of the case is especially relevant to interpretation of laboratory data: the employer’s total expense, the laboratory’s receipts, and the administrator’s compensation are different quantities. An employer could allegedly spend too much even while a provider was paid relatively little. A chart of laboratory payment rates cannot reveal all the fees or transfers between the plan and its administrator.

Access to payment records and meaningful audits

The demand for underlying data consequently runs through the complaint. The employers seek the records needed to reconcile what providers submitted, what the administrator approved, what the plans funded, and what providers received. They discuss electronic claim submissions, known as 837 transactions, and electronic remittance advice, known as 835 transactions. Remittance records contain payment and adjustment information needed to understand the disposition of claims. The plaintiffs allege that some employers received only partial data and others received incomplete, unusable, or inaccessible information. (Paragraphs 45–60, pages 16–22.)

Audit design matters as well. The complaint challenges restrictions on claim sampling and extrapolation and argues that checking a few hundred claims cannot reliably detect problems requiring comparison across the entire claim population. For example, examining one infusion bill alone may miss its alleged duplicate under a different claim number. The employers also allege that movement of funds through United-controlled accounts made it difficult to reconcile amounts collected from plans with amounts paid to providers. (Paragraphs 103–105, pages 36–37; paragraphs 117–120, pages 41–42.)

4 Legal stakes and implications for laboratories

Fiduciary duties and the claims under ERISA

The legal architecture explains why the case reaches beyond an ordinary dispute over service quality. The plaintiffs contend that United was a fiduciary under the Employee Retirement Income Security Act, or ERISA, a role carrying duties of loyalty and prudence toward the plans and their participants. They offer three grounds: contractual fiduciary designations, discretionary authority over benefit and payment decisions, and control over plan assets. Whether an administrator acted as a fiduciary for the particular conduct challenged is an important legal question; the label TPA alone does not resolve it. (Paragraphs 29–44, pages 10–16.)

The first five counts invoke ERISA duties, prohibited transactions, and compensation disclosure requirements. A prohibited-transaction theory asks whether plan assets were used in a conflicted transaction, such as self-dealing or an impermissible transfer benefiting a related party. That is a different inquiry from whether an isolated bill was carelessly processed. The remaining counts include contract, declaratory-relief, good-faith, alternative common-law fiduciary, negligence, gross-negligence, and unjust-enrichment claims. These are alternative legal routes pleaded by the employers, not twelve violations established by a court. (Pages 44–60.)

The scope of compensation disclosure

One disclosure theory relies on ERISA section 408(b)(2)(B), added by the Consolidated Appropriations Act, 2021. Its scope deserves precision: Department of Labor guidance describes requirements for covered brokerage or consulting services, subject to the statute’s conditions. It should not be paraphrased as an automatic disclosure rule for every TPA arrangement. How the challenged services and compensation fit the provision is part of the legal inquiry. (Complaint, paragraphs 121–126, pages 42–44; Count V, pages 49–51.)

What the employers want the court to order

The requested remedies are extensive. The employers seek reimbursement of losses, disgorgement of profits, attorneys’ fees, and orders providing access to claims data with privacy protections. They specifically ask for employer, plan-sponsor, or trust identification and taxpayer identification numbers on relevant 835 remittances, including those sent through clearinghouses such as Change Healthcare. They also request punitive damages. These are requests for relief; the complaint does not establish that each remedy is available or will be awarded. (Pages 60–61.)

What laboratory executives can examine now

For laboratory businesses, the immediate research opportunity is to measure dependence on unusually high payments accurately. A volume-weighted distribution can show how often those payments occur. Dollar-weighted calculations can show their revenue importance. Explicit, test-specific cost assumptions can estimate their contribution, preferably across several plausible cost scenarios. Those calculations should preserve the underlying rates and volumes and distinguish a national dataset from the experience of an individual laboratory.

The UnitedHealth lawsuit supplies a reason to ask the next question: what supports the payments on which that contribution depends? They may reflect valid contracts, differences in services, or other legitimate circumstances. The employers allege that some medical payments instead reflect deficient review, conflicts, or undisclosed arrangements. The public complaint does not connect those allegations to particular PAMA outliers. It does show why access to detailed payment records matters to both sides of the transaction: the employer trying to account for its spending and the laboratory trying to understand the durability of its revenue.

Source note: Case analysis is based on the public, redacted complaint filed October 20, 2026, Document 3, with paragraph and page references supplied above. It describes the pleading rather than a judicial determination of liability.


Monday, October 26, 2026

A Mouse is Not a Microscope: Digital Pathology Waiting for Quantum Leap in User Devices

Header:  Should digital pathology have a true revolution in the quality of input devices?

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Recently, we blogged about how digital pathology advances slowly.  And rather than looking to radiology for advice, we should look to...the adoption of Da Vinci robotic surgery.

Robotic surgery probably took half the prostatectomy market in ten years - at huge cost in equipment and infrastructure.  There were four potential drivers:

1) Health outcomes
2) Economics (faster-cheaper)
3) Surgeon enthusiasm
4) Hospital competition

Per that blog and Da Vinci white paper, there was little early evidence for better outcomes.  The costs were high, not self-propelling.   However, #3 surgeon enthusiasm was high, and #4 hospital competition (keeping up) was a big fact.

1) Health outcomes
2) Economics (faster-cheaper)

3) Surgeon enthusiasm
4) Hospital competition

For digital pathology, big health outcomes aren't expected, it's more expensive, some pathologists like digital but it's hardly a stampede of excitement, and hospital competition (e.g. billboards or radio ads) is off the table. 

One thing we might be able to change is #3, pathologist enthusiasm.  I think it's pending two things: AI prepares a full digital report ready for careful validation and sign out (it's not so far off) and second, there may be a missing "quantu leap" in user interactions.

On the latter count, see a new article by Lopes et al, new horizons for input devices.  It got a write-up in CAP TODAY as well.

Here, let's try to take it further with a 14-page white paper from Claude.

Find the white paper here.

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White Paper Summary

Whole-slide imaging has spent twenty years solving the hard problems of optics, file formats, scanner throughput, FDA clearance, and now artificial intelligence. It has spent almost no effort on the question that sits between the pathologist and all of that machinery: how, physically, a human being should steer a gigapixel image with their body. The de facto answer in 2026 is mostly the same as in 2009, which is a computer mouse, a scroll wheel, and a toolbar of small icons designed for spreadsheets. The small literature that exists on alternatives, which runs to perhaps a dozen papers across fifteen years, is consistent in finding that pathologists would rather use almost anything else, and consistent in being underpowered, task-contrived, and politely ignored by the companies that build viewers.

The most recent and most interesting entry, a 2026 Archives study from Western University testing eye and head tracking, is good work that nonetheless illustrates the field’s smallness of ambition, right down to its survey question asking whether pathologists would spend a hundred dollars a year of their own money on a better way to look at cancer. 

This paper argues that the interaction problem is real, that it has consequences for diagnostic accuracy and not just for wrists, that incrementalism is structurally guaranteed by the way the field is organized, and that a deliberately radical, well-funded, year-long design effort by a small mixed team is the appropriate response. The goal should be a different way of working, not a better mouse.

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prompt

Research and write a white paper type essay on the need for, underexploration of, and value of novel creative devices for pathologists to interact with WSI systems  I first saw these in 2009, and thought, this mousing around a WSI is awful for a diagnostic pathologist, clicking tiny submenus and so forth.  based on the world Dig Path Assoc conference a  week ago, we aren't that much further!  I think maybe we aren't creative enough.  In my mind, you'd send ten engineers, designers, pathologists, experts to an island for a year and ask them to reinvent the interaction of pathologist and slide.   See some recent materials attached.   write an essay on the state of the field (probably a mouse and drop down tiny click boxes or sliders), why quantum change is hard to envisage but perhaps needed, and some existing (Lopes) and future directions for change.   The vvery fact Lopes asked participants to pay extra for a better input device is a glaring sign we are thinking too tiny.   maybe it would be eye tracking maybe something that looks like playing a theremin, maybe real time verbal.   we don't yet know yet must explore boldly to achive a "quantum leap" from the starting point, not a six inch advance.

Sunday, October 25, 2026

Version 2: CMS, NIH, FDA Websites Switching to "SUPER INTELLIGENCE"

VERSION TWO - SUPER INTELLIGENCE

The original version of this blog discussed government websites switching to "SUPER INTELLIGENCE" terminology.  

I included a playful, silly parody news article as well.

This triggered a content warning from Google Blogger (my blog host), apparently because any kind of parody is something that is "not true" so it needs to be flagged.

Here, I move the humorous parody part, to a Google doc, link at the end.

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You might have heard the White House use the phrase "Super Intelligence" a couple times.  

This stems from a September 29 Executive Order that talks about AI policy but includes an order that the government switch exclusively to the term "Super Intelligence," not artificial intelligence.   That's wide-ranging - every webpage, ever new FDA guidance document, and so on. 

See Executive Order 14434.


See e.g. PubMed which is part of NIH:


CMS has not changed its text in this screen shot, but notice the web home page is already SI.cms.gov.


See Arnold and Porter.  See Politico.   See Navy.
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See a parody humor news article at link




Version One; It's Here, It's Now: CMS, NIH, FDA Websites Switching to "SUPER INTELLIGENCE"

This summary is not available. Please click here to view the post.

Saturday, October 24, 2026

PAMA Unveils Bizarre Patterns for US Lab Test Pricing

Here's an analysis run mostly by AI, based on my ability to "vibe code" instructions of what AI had to do with raw PAMA Excel data.

Data shows the bar charts of the private payer price distribution for about 15 codes.  The distributions are strange and not many are "Guassian" or "normal."  While some are tightly distributed and others spread evenly around the price range.   

See a prior study in 81455, 81456 here.  See a prior study of CPT neuro code data here.

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I went to the giant raw data files for PAMA price reporting and created smaller spreadsheets for PLA code data and for 815nn (MAAA code) data.  I asked Chat GPT to consider only codes with more than 200 rows of data.  

This gave 4 just charts for PLA data (of 500 PLA codes in PAMA) and 11 charts for 815nn data.  

  • Note that CMS does not usually provide sole-source lab data, so I'm not sure why there seem to be data for 81528 Cologuard but not others (e.g. Oncotype Dx Breast 81519, Veracyte AFIRMA 81546, etc).  With distributed kits like Biofire you'd expect to see data from many TINS, though, and CMS posts the data.
Data jumps from MAAA 81517 to 81528:


Data jumps from MAAA 81539 to 81596:



Anyway, so far, we've identified codes in the PLA series or 815/MAAA series with > 200 rows of PAMA data.

Then I instructed Chat GPT to take the price data for each code that qualified, and bin the price data in 8 bins (equal size, but I let AI figure it out) as vertical bar charts per price bin.

See all the results in ZIP file.

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See a separate figure at bottom of this blog, that shows outliers to the right side have a much larger contribution margin than median and lower cases.  I will explore that further, in a future blog.  

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0359U IsoPSA

0503U Precivity

CMS New Voluntary Exclusion Authority: What Court Cases Have Said

This month, RFK Jr gave CMS itself the elective exclusion authority long reserved only for referral to the OIG's attorneys. Blog.

Here I've asked Claude to put on its virtual law school professor hat and discuss how case law may have shaped the interpretation of the statute.   (The statute allows years of exclusion for violations as loosely defined as "unnecessary services" or "overcharging."  The exclusion arrives in days, but fighting it might mean years in court.)

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AI CORNER

Essay by CLAUDE.

See shorter essay by Chat GPT  here.

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See the cloud 8p PDF here.


Two Hands on One Lever:

CMS, Permissive Exclusion, and Forty Years of Case Law

CLAUDE OPUS Oct 24, 2026 · @Bruce Quinn  AI Writing - Not Legal Advice

On October 14, 2026, Secretary Kennedy published a one-page Statement of Delegation of Authority that may turn out to be the most consequential program-integrity document of the year. It hands the CMS Administrator the Secretary's permissive exclusion powers under section 1128(b) of the Social Security Act, 42 U.S.C. § 1320a-7(b). The Office of Inspector General keeps everything it had. The delegation withholds two things, the authority to conduct hearings and the authority to issue regulations, and it ratifies any exclusion-related action CMS took before the notice appeared. CMS may redelegate within the agency.

Nothing in the statute changed. What changed is who may pull the lever, and that turns out to matter a great deal, because section 1128 has spent four decades being interpreted on the assumption that the entity pulling it was a law-enforcement office rather than the payer. The question for law professors is what the accumulated case law has to say to a new actor; the question for policy people is whether that case law will discipline CMS the way it has disciplined OIG, or whether a payer with its own data warehouse and its own grievances will find the doctrinal fences less constraining than they look.

The statute CMS inherits as of October 2026

Exclusion predates OIG's custody of it. The 1977 Medicare-Medicaid Anti-Fraud and Abuse Amendments gave the Secretary authority to bar providers convicted of program-related crimes, and the Medicare and Medicaid Patient and Program Protection Act of 1987 reorganized the authority into the structure we still use: section 1128(a) mandates exclusion for a short list of convictions (program-related crimes, patient abuse, and later felony fraud and felony controlled-substance offenses), while section 1128(b) permits exclusion on a longer and more heterogeneous list (17 instances, some with detailed rules.) The Secretary delegated both to OIG in the 1980s, and OIG has run the machinery, and written the regulations at 42 C.F.R. Part 1001, ever since. The Affordable Care Act added grounds in 2010, including section 1128(b)(16) for false statements on enrollment applications, a provision that sits squarely in CMS's own territory.

The permissive grounds are worth reading as a list, because their diversity is the point. Some require a conviction: misdemeanor fraud, obstruction of an investigation, misdemeanor controlled-substance offenses. Some require no conviction at all: loss of a state license, exclusion from another federal program, furnishing unnecessary or substandard services, charging substantially in excess of usual charges, engaging in kickback or false-claims conduct found administratively, being an owner or officer of an excluded entity, defaulting on health-education loans. "Permissive" describes the Secretary's discretion once a ground is established; it says nothing about how much process preceded the finding. A conviction-based permissive exclusion rides on a judgment entered by a court. A section 1128(b)(6) exclusion for unnecessary services rides on a medical-review file assembled by the agency, which, as of this month, may be the same agency that decides whether to exclude.

The consequences are also worth stating plainly for the non-lawyers. Exclusion is not revocation. Revocation under 42 C.F.R. § 424.535 removes a supplier's Medicare billing privileges and is appealed through the enrollment track. Exclusion bars payment by every federal health care program for any item or service furnished, ordered, or prescribed by the excluded person; it lands the name on the public LEIE; it exposes any employer who bills for the excluded person's work to civil monetary penalties; and it is appealed through an ALJ and the Departmental Appeals Board under 42 C.F.R. Part 1005, with judicial review after that. CMS has for years run a smaller version of this, the Medicare Advantage and Part D preclusion list and a seldom-used set of Part 402 exclusion grounds, but those were the minor leagues. Section 1128(b) is the real thing.

Exclusion is remedial, which is why the courts let it be harsh

The foundational line of cases established that exclusion is not punishment, and nearly every later doctrine depends on that characterization.

The problem arose because excluded providers were often also prosecuted, and after United States v. Halper (1989) it was briefly fashionable to argue that a civil sanction imposed on top of a criminal conviction was a second punishment. Dr. Manocchio, a physician who pleaded guilty to filing a false Medicare claim and then received the mandatory five-year exclusion, made exactly that argument. The Eleventh Circuit rejected it in Manocchio v. Kusserow, 961 F.2d 1539 (11th Cir. 1992), holding that exclusion serves to protect the programs and their beneficiaries from untrustworthy providers rather than to punish, and so raises no double-jeopardy problem. The Ninth Circuit reached the same conclusion from the ex post facto direction in Travers v. Shalala, 20 F.3d 993 (9th Cir. 1994), where a physician's offense predated the 1987 amendments that created the five-year mandatory minimum; because the sanction was remedial, applying the longer term to earlier conduct was permissible.

The remedial label did enormous work. It is why exclusion need not be proportioned to culpability in the way a sentence must be, why it can follow a conviction without constitutional objection, and why the government may act before a full hearing. For CMS, the label is a gift and a warning. It is a gift because an agency that excludes to protect beneficiaries need not prove much about the provider's state of mind. It is a warning because the remedial rationale has to be true in the individual case. Hanlester, discussed below, is what happens when a court decides it is not.

No hearing first, usually

A second early cluster of cases settled that due process does not generally require a hearing before exclusion takes effect, provided the provider has notice, a chance to respond in writing, and a prompt hearing afterward.

Ritter v. Cohen, 797 F.2d 119 (3d Cir. 1986), involved a Pennsylvania physician suspended from Medicare on findings that he had furnished excessive and unnecessary services. He argued that his livelihood could not be taken without a prior evidentiary hearing. Applying Mathews v. Eldridge, the Third Circuit held that written notice, an opportunity to submit evidence and argument, and a post-suspension hearing were enough, given the government's interest in stopping harm to patients and the program. Two years later the Eighth Circuit faced the same argument from Dr. Ruben Thorbus, a rural Minnesota physician whose clinic drew roughly sixty percent of its patients from Medicare and Medicaid and whom federal medical reviewers accused of performing excessive diagnostic endoscopies and delivering substandard care. HHS imposed a five-year exclusion after he had an opportunity to respond, and he sought a preliminary injunction to keep practicing while his administrative appeal proceeded. Thorbus v. Bowen, 848 F.2d 901 (8th Cir. 1988), affirmed the denial. The court found no likely due-process violation and, in the balance of harms, put the risk to patients ahead of the physician's financial and reputational loss, even in a community where he was one of few available doctors.

Congress later carved out one important exception. Exclusions under section 1128(b)(7), the ground for kickback and false-claims conduct found administratively rather than by a court, do not take effect until after a hearing, unless the Secretary determines that the provider's continued participation poses a risk to health or safety. The distinction is sensible: a conviction or license revocation has already been adjudicated somewhere, whereas a (b)(7) exclusion asks the agency to prove the underlying violation itself. CMS now holds (b)(7) authority, and if it is tempted to lean on the health-or-safety override to skip the pre-exclusion hearing, the Thorbus and Ritter line will be read against it: those courts tolerated speed because the statute and regulations supplied prompt review afterward, not because the agency's say-so about danger was self-validating.

"Related to" is capacious, but the length must be explained

The most important modern appellate decision on permissive exclusion is Friedman v. Sebelius, 686 F.3d 813 (D.C. Cir. 2012), and it cuts both ways.

The facts are familiar to anyone who followed the opioid litigation. Purdue Frederick had marketed OxyContin with claims that it was less addictive and less prone to abuse than competing opioids. In 2007 the company pleaded guilty to felony misbranding, and three senior executives, the chief executive, the general counsel, and the chief medical officer, pleaded guilty to misdemeanor misbranding under the responsible corporate officer doctrine. That doctrine, which dates to Dotterweich and Park, imposes liability on an officer who had authority to prevent or correct the violation, without proof that he knew about it. OIG then excluded all three for twelve years under section 1128(b)(1), which reaches misdemeanor convictions "relating to" fraud in connection with the delivery of a health care item or service.

The D.C. Circuit answered two questions. First, was a strict-liability misdemeanor "related to" fraud? Yes. The court read the phrase broadly: the conduct underlying the conviction was fraudulent misbranding, and the executives' pleas admitted a relationship to it, even though their own offense required no fraudulent intent. That holding gives the government a long reach; it means an executive can be excluded for a crime that required nothing more than being in charge. Second, was twelve years lawful? Not as explained. OIG had never before imposed anything close to that length on individuals in comparable circumstances, and the agency's decision did not grapple with its own prior practice. Under ordinary administrative-law principles, an agency may change course, but it must acknowledge that it is doing so and say why. The court vacated the twelve-year term and remanded; the executives ultimately received substantially shorter exclusions.

For CMS, Friedman is the case to tape to the wall. The agency arrives with a mandate, voiced by the Secretary in July and in the delegation notice itself, to remove bad actors more aggressively than OIG has. Nothing in section 1128 forbids that. But the baseline against which any CMS exclusion will be measured for arbitrariness is OIG's forty-year corpus of decisions, aggravating and mitigating factors at 42 C.F.R. §§ 1001.102 and 1001.201, and the Board's settled rule that an ALJ reviews the length of a permissive exclusion for reasonableness rather than substituting his own judgment. Because the delegation withholds rulemaking, CMS cannot write itself a new set of factors; it must apply OIG's, and it must explain any departure from how OIG has applied them. A payer that wants to signal toughness by handing out fifteen-year exclusions for conduct OIG historically treated with five will be writing briefs for the D.C. Circuit.

When exclusion stops being remedial: the laboratory case

Hanlester Network v. Shalala, 51 F.3d 1390 (9th Cir. 1995), is the decision diagnostics people already know, usually for its (since-overruled) holding on anti-kickback intent. Its exclusion holding deserves more attention than it gets.

Hanlester Network organized three clinical laboratory joint ventures in California, selling limited-partnership interests to physicians who were, not coincidentally, in a position to refer specimens. SmithKline BioScience Laboratories managed the labs and performed most of the testing under contract. A Hanlester marketing agent told physician investors, in substance, that their returns would track their referrals. The Inspector General found anti-kickback violations and sought permissive exclusions under section 1128(b)(7) against the network, the three joint-venture laboratories, and several individuals.

The Ninth Circuit affirmed that the entities had violated the statute, through the agent's conduct, on a theory of vicarious liability. It then reversed the exclusions. The court's reasoning was the remedial rationale turned around and pointed at the government: exclusion exists to protect the programs from providers who are likely to cause future harm, the entities' culpability was derivative of an agent who had long since departed, and there was no evidence on the record that they remained untrustworthy. A violation had occurred; exclusion was still unwarranted.

Two cautions. The intent holding in Hanlester, which required proof that the defendant knew the conduct was unlawful and specifically intended to violate the statute, was legislatively displaced in 2010 when the ACA added section 1128B(h). And Hanlester does not stand for the proposition that firing the salesman cures the company; its outcome depended on a thin record of ongoing risk. But the structural point survives: the statutory ground and the remedial justification are separate inquiries, and a court will police the second. For CMS, which will often be acting on data showing that a laboratory or a physician billed aberrantly in 2024, the question a reviewing tribunal will ask is whether that history establishes untrustworthiness now.

The grounds CMS is best positioned to use, and least tested in using

The delegation notice says CMS is "uniquely positioned to investigate, identify, and develop the evidentiary basis" for permissive exclusions. That is true, and it is also the problem. The grounds where CMS's data advantage is greatest are precisely the ones with the thinnest case law.

Section 1128(b)(6)(B), unnecessary or substandard services, is the Thorbus ground, and Thorbus is a preliminary-injunction decision about interim relief, not a merits ruling about how many unnecessary endoscopies make a pattern. Section 1128(b)(6)(A), charges substantially in excess of usual charges, has never been defined; OIG proposed a rule in 2003 and withdrew it in 2007 after concluding it could not draft a workable definition, and the ground has lain largely dormant since. A payer that sets its own fee schedule and then excludes a laboratory for charging "substantially in excess" of its usual charges would be testing a provision that has no appellate gloss at all. Section 1128(b)(16), false statements in enrollment, is new enough that the Board's decisions are sparse, and CMS already revokes enrollment on the same facts under section 424.535(a)(4); the delegation lets it convert an enrollment dispute into a program-wide bar with a different appeal track and far heavier collateral consequences. Section 1128(b)(15), reaching owners and officers of excluded entities, invites exactly the kind of derivative-liability exclusion that Hanlester reversed.

None of this means CMS lacks authority. It means CMS will be making law in areas where OIG, for whatever mix of prudence and caseload, chose not to.

What the cases, read together, tell a new enforcer

Three threads run through the decisions. The statutory ground must be established as written, and the courts have read "related to" generously but have not read it to swallow the enumerated list. The decision to exclude, and the length of exclusion, must be justified on the record as protective rather than punitive, and must be consistent with the agency's own prior practice or explain the inconsistency. And the timing of review is fixed by the statute: ordinarily after the fact, with the (b)(7) pre-exclusion hearing as the exception, and with district courts disinclined to enjoin exclusions in the interim.

The institutional novelty is that these constraints were developed with OIG as the respondent, an office whose culture is prosecutorial and whose exclusion docket has been dominated by convictions and license losses, grounds where someone else did the fact-finding. CMS is a payer. Its instinct is to act on claims data, its grievance is overpayment, and its new authority is unaccompanied by new regulations, new hearing procedures, or any public statement about how it will coordinate with OIG, honor OIG's exclusion waivers in False Claims Act settlements, or treat entities already operating under corporate integrity agreements. The delegation notice resolves none of this and, in withholding rulemaking and hearings, suggests the Secretary did not intend it to.

The case law will not stop CMS from excluding anyone. It will insist that CMS do what OIG has had to do: name the ground, prove it, explain the term, and be prepared to defend the exclusion as something other than a sanction for having annoyed the payer. Friedman and Hanlester were both decided against an agency that had been doing this for decades. The first several CMS exclusions to reach the Board, and the first to reach a circuit, will tell us whether the statute's accumulated discipline transfers with the delegation or whether, as the Secretary's July remarks implied, the point of a second hand on the lever was to pull it harder.

Sources