Saturday, June 27, 2026

Humor: AI News Article About My Appendix S Blog

Header: All About a New Blog about Appendix S


June 27, 2026 (Los Angeles)

By: Chat GPT 5.5

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

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

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

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

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

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

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


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See also: Is an ICD an AI?

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

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

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

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

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

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


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CHAT GPT 5.5 followed by CLAUDE OPUS 4.8

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

AMA CPT: Coding Policy EARLY RELEASES: Cat I, Cat III, PLA, APP S AI, ADMIN MAAA

 AMA has released a website that displays "early release" updates in policy in five areas:

  • Category I Codes
  • Category III Codes
  • PLA Codes
  • Appendix S: The "AI Taxonomy"
  • Administrative MAAA codes
Find them all here:


Early Release
The Category I, Category III, PLA, and administrative MAAA code sets all include some form of early-release codes. Category III, PLA, and administrative MAAA codes are early release by definition: Category III codes are released twice a year, and PLA codes are released quarterly. Category I codes are rarely released early, with vaccines being one exception.

Guest AI Blog: Radiology is Starting to Write Reports. Pathology Should Pay Attention.

 

Radiology AI Is Starting to Write Reports. Pathology Should Pay Attention.

[Claud Opus 4.8]

Radiology AI is crossing the line from flagging findings to drafting the report. STAT's recent coverage of Cognita, Aidoc, RSNA 2025, and two new FDA breakthrough designations is, for digital pathology, a preview of the next three years — including the awkward part nobody markets: a draft report doesn't save the physician's time so much as it relocates that time into editing.


For a decade, AI in medical imaging has meant a spot detector. Flag the pneumothorax. Count the positive cells. Measure the tumor. Highlight the suspicious region. Useful, narrow, and bounded — and in every case the physician still writes the report.

That line is now being crossed. A narrow tool says "possible pneumothorax." A report-drafting model says "small right apical pneumothorax, new since prior study," and drops that language into a preliminary report for a radiologist to review, edit, and sign. The first is an alert. The second is an attempted clinical work product. The difference is the whole story.

Three STAT articles by Katie Palmer trace the move. Worth reading as a set, because they form an arc that pathology is likely to walk in turn: a marquee acquisition, a field-wide reality check, and the FDA beginning to engage.

Friday, June 26, 2026

Pathology Codes for September 2026 Minneapolis Meeting

The next AMA CPT meeting is in Minneapolis, September 17-19, 2026.

The registration isn't open yet, but will be found here:

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

Lab tests follow an early comment cycle, from now June 26 to July 13.

Note that comments are due noon central, ten pacific, on July 13.

(Regular, non-lab code list to be released July 10).

See the lab code agenda here:

https://www.ama-assn.org/system/files/september-2026-lab-agenda.pdf

The lab code list is pretty simple (note, there will also be 20-plus PLA codes.)

Tab 38, revise bone marrow biopsy, 88305-7.

Tab 39, deletet 81520, breast cancer recurrence score. (This is a legacy Prosigna score, a new NGS based Prosigna code is coming.)

Tab 40, revisions to blood bank services.

Tab 41, 87xxx for adenovirus.

Tab 68, Cat III for digitized prostate slides.  "X672T"

Tab 94, Revise pathology code application to accomodate AI issues.

##

Note: The agenda PDF has a link that sends you to a comment portal.  You will find yourself at "CPT Smart App" and near the top you have to click the option for "Interested Party Portal."

As of noon PT, 6/26, the Agenda PDF for labs was posted but no comment options had yet appeared on the 'CPT Smart App."  


Very Brief Blog: Price Analysis of Wild 2017 PAMA Data

 We're gearing up for PAMA cycle II, CMS will release millions of lines of data in August or September 2026, in preparation for the new CLFS fee schedule in 2027.

Here's a look back at some of the wild data results in 2017.

https://www.discoveriesinhealthpolicy.com/2017/09/pama-raw-data-provides-unprecedented.html

Here's one panel from the 2017 blog.

Eg BRCA pricing ran from $1000 to $3220 (without mentioning outliers).  I suspect the peak around $3000 was legacy 2014-forward Myriad BRCA sole source pricing, and the range around $1700-2000 was newer entrants contracting to a fraction like 70% or 80% of the CLFS at the time.


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AI in My Daily Life

I knew you could still get some of the 2017 data (not line items less than 10 units) at data.cms.gov, but Google wasn't finding it.  Chat GPT was able to find it in a second.

###
ME:
Cms.data.gov still has a web page that takes you to cloud data for 2017 PAMA CLFS pricing, but it's hard to find the link. Help??
###
Chat GPT quickly answers:
###

Yes — CMS hides the important link a bit.

The CMS CLFS landing page still has it near the bottom under “For more information” as:

“View the CLFS Applicable Raw Data File (from 2017 reporting)”
https://data.cms.gov/provider-characteristics/hospitals-and-other-facilities/medicare-clinical-laboratory-fee-schedule-private-payer-rates-and-volumes

CMS describes the current CLFS as based on PAMA private-payor-rate reporting and says the 2017 reporting used the January 1, 2016–June 30, 2016 data collection period; that same period still drives 2020–2026 CLFS rates because later statutory delays postponed new reporting effects. (CMS)

The easier direct CSV link, [Excel] from the federal data.gov catalog, is:

https://data.cms.gov/sites/default/files/2021-12/CLFS%20Applicable%20Information%202018%20Raw%20Data%20File-updated%2012152021.csv

Data.gov also lists the API endpoint:

https://data.cms.gov/data-api/v1/dataset/0e57f57d-0acc-4c9c-8f8c-973e3f4a3c4b/data

The dataset title is “Medicare Clinical Laboratory Fee Schedule Private Payer Rates and Volumes.” Data.gov describes it as raw data from applicable laboratories reporting private payor rates and associated volumes for CLFS tests, and it lists the CSV download URL above. (catalog.data.gov)

The Wide Dispersal of Payment Rates for...Anatomic Pathology

From time to time, there are articles about the wide dispersal of prices in US healthcare.  (One patient and health plan pays $1000, another patient and health plan pays $6000).  We saw that wide dispersal of pricing in the 2016 clin lab payment data released in mid 2017 by CMS as part of PAMA market rates for lab test pricing.  By August 2026, we'll have a huge update of 1H2025 clin lab prices for PAMA-II.

Here's a new case study, provided by Jason Nakka at LinkedIn.  He had access to data on contracted pathology biopsy rates (CPT 88305) from Cigna.  As he writes,

"A slide prepared in Washington State can be read by a pathologist in Iowa, for three times the price.   The 88305 read pays median $17 in Oklahoma, and $71 in Nebraska, a 4.2X spread."

Find his dollarized article here.  Find his earlier ratio-based article here.  

See a commercial consultancy/vender for price data PriceMedic.Com.

click to enlarge


He remarks, "the slide travels..."   Obviously that slide, once prepared on glass, can travel even faster by digital pathology.

##

Sidebar

I asked Chat GPT to find 3 articles on the same topic, wide price variability (in other clinical domains).  I quote below but haven't validated myself.

##

Here are three strong comparators for your pathology-price-variation blog. I’d use Oakes 2024 as the closest “John with BCBS vs Tom with United” example, Whaley 2025 as the broad Transparency in Coverage / TiC-era national frame, and Cooper 2019 as the classic economics anchor.  TiC = federally required payer machine readableprice files.

1) Cooper Z, Craig SV, Gaynor M, Van Reenen J. “The Price Ain’t Right? Hospital Prices and Health Spending on the Privately Insured.” Quarterly Journal of Economics. 2019;134(1):51–107. doi:10.1093/qje/qjy020.

Full link: https://doi.org/10.1093/qje/qjy020
Yale page: https://isps.yale.edu/research/publications/isps15-027

This is the classic article showing that, for privately insured patients, prices—not utilization—drive much of the geographic variation in spending, unlike Medicare. It reports threefold variation in private spending across HRRs and very large price dispersion for relatively homogeneous services, including lower-limb MRI prices varying twelvefold nationally and about twofold within HRRs. (isps.yale.edu)

___

2) Oakes AH, Ikard M, Patton C, et al. “Understanding Variation in Negotiated Rates Using Novel Health Plan Price Transparency Data.” JAMA Health Forum. 2024;5(9):e243020. doi:10.1001/jamahealthforum.2024.3020.

Full link: https://jamanetwork.com/journals/jama-health-forum/fullarticle/2823759
PubMed: https://pubmed.ncbi.nlm.nih.gov/39302670/

This is probably the best direct analogy to your “same service, different payer” point. Using Transparency in Coverage data, the authors compared UnitedHealthcare and Blue Cross Blue Shield of Illinois rates for hip/knee replacement and found substantial variation within the same market and even within the same hospital across different payers; the PDF reports a mean same-hospital BCBSIL-vs-UHC difference of $5,178, about 20% of the mean negotiated rate. (JAMA Network)

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3) Whaley C, Radhakrishnan N, Richards M, Simon K, Chartock B. “Understanding Health Care Price Variation: Evidence from Transparency-in-Coverage Data.” Health Affairs Scholar. 2025;3(2):qxaf011. doi:10.1093/haschl/qxaf011.

Full link: https://academic.oup.com/healthaffairsscholar/article/3/2/qxaf011/7965202
PMC: https://pmc.ncbi.nlm.nih.gov/articles/PMC11798183/

This is the broadest current national Transparency in Coverage - TiC-based article, documenting price variation across geography, payer, and provider. A nice quotable example for your blog: the mean facility fee for a foot X-ray was $86 at Anthem vs $190 at UnitedHealth, and the authors found weak consistency across inpatient and outpatient price levels—supporting your point that commercial prices are negotiated artifacts, not natural reflections of service cost. (academic.oup.com)


Digital Pathology Association/DPA Issues Two Linked Documents on AI Validation and Reimbursement

Digital Pathology Association Issues Two Linked Documents
on AI Validation and Reimbursement

1. Recommendation Statement for the Validation, Implementation, and Clinical Application of Artificial Intelligence Within a Clinical Laboratory from the Digital Pathology Association

https://journals.sagepub.com/doi/10.1177/2993091X261455975

2. Full Speed Ahead: Shaping the Future of Digital Pathology Reimbursement in 2026
https://digitalpathologyassociation.org/blog/full-speed-ahead-shaping-the-future-of-digital-pathology-reimbursement-in-2026

[chat GPT 5.5]

The Digital Pathology Association (DPA) has recently issued two important and closely linked documents. The first is a formal recommendation statement, published in AI in Precision Oncology, Silberman et al., on validation, implementation, and clinical use of AI in digital pathology. The paper addresses analytical validation, clinical validation, scanner and algorithm performance, pathologist oversight, clinical utility, and real-world reliability.  (I covered this 27-page paper in detail earlier.)

The second is an April 6, 2026 DPA Reimbursement Task Force webpage outlining the association’s 2026 policy agenda for digital pathology reimbursement. It frames reimbursement and market access as central barriers to adoption, and states that DPA’s goal is to define and shape the pathway to reimbursement for digital pathology solutions.

The linkage between the two is explicit:

DPA presents the Silberman validation paper not only as a clinical roadmap for laboratories, but also as an evidence base for reimbursement. In DPA’s formulation, payers will not pay simply because AI is interesting or efficient. The field must show that digital pathology AI is safe, validated, clinically meaningful, and important to patient care.

The April 6 policy page is especially notable because it signals a more organized reimbursement strategy. 

DPA says it has partnered with McDermott+ to monitor and influence CMS, AMA, Congress, and other policy venues. The stated goal is to promote positions supporting coding, coverage, payment, and adoption of digital pathology technologies and infrastructure through official comment and direct agency engagement.

DPA writes, "We are no longer just reacting to policy - we are proactively influencing and shaping the future reimbursement framework. 

Take home lesson: 

For readers following digital pathology, this burst of activity is worth watching. The validation paper supplies the scientific and clinical framework; the reimbursement page describes the policy machinery DPA intends to build around it. Together, they suggest that DPA is trying to move digital pathology from promising technology toward a reimbursable, policy-recognized clinical infrastructure.

_________________________

Sidebar: Reimbursement Task Force
https://digitalpathologyassociation.org/reimbursement-task-force

_____

Sidebar: Conference

The DPA "Pathology Visions" conference will be October 16-18 in San Diego.

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Sidebar: CMS and Software Valuation

Last summer, CMS issued RFIs (requests for information) in both Physician/PFS and Outpatient Hospital/OPPS rules.  Responses were due by September; CMS merely acknowledged the receipt of numerous responses in the November final rules.  We may see more in July 2026 policymaking for PFS and OPPS.

Last December, HHS issued an RFI for clinical AI which asked about (1) regulation, (2) R&D, and (30 Reimbursement.  HHS held a webinar yesterday (June 25) highlighting its activities in some of these areas, but leaving "reimbursement" out of scope. 

_____

Sidebar: The DPA in 2023 and in 2026

DPA has had policy articles twice in 2023, then none in 2024 or 2025, and now this new reimbursement program of activity in 2026.  


Chat GTP compares the 2023 and 2026 blog here.  Concisely it concluded:

DPA’s October 2023 reimbursement article was a sophisticated but technical map of possible payment pathways, centered on the then-new Category III slide digitization codes but extending into CMS authority, HCPCS alternatives, OPPS software pa

 

yment, and the need for valuation data.

The April 2026 article is different. It is shorter, less technical, and more strategic. Rather than explaining the maze, it announces that DPA is building the machinery to navigate it: a validation/evidence statement for AI, a more explicit reimbursement mission, and a policy partnership with McDermott+ to engage CMS, AMA, Congress, and other decision-makers. In that sense, the 2026 piece reads less like a reimbursement tutorial and more like an organizational reboot.


Thursday, June 25, 2026

The June 25 HHS Update on AI in Clinical Care: Meeting Summary

In December 2025, HHS announced an RFI on how it could improve access to AI for clinical care.  See webpage here, Fed Reg here.  (90 FR 60108, 12/23/2025).

On June 25, HHS held an hour-long webinar to update the public on progress.  While the three arms of the program are regulation, research and development, and reimbursement, they opened by announcing this webinar would include regulation and R&D (not reimbursement).

See coverage at Healthcare Dive here.  HCD frames the webinar as it was advertised, an update based on the December RFI and January public feedback.  But I think it was really an direct update on a half-dozen various active projects and demos underway at  HHS.  

Claude Opus summarizes the transcript.

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HHS Hosts a "One HHS" Clinical-AI Webinar — A Landscape Tour, Not a Comment Readout

A working record of the June 2026 HHS webinar tied to the December 23, 2025 Request for Information, "Accelerating the Adoption and Use of Artificial Intelligence as Part of Clinical Care" (RIN 0955-AA13).


Summary  

In June 2026, HHS held a public webinar tied to its December 23, 2025 Request for Information on accelerating AI in clinical care (RIN 0955-AA13). Rather than reporting comment feedback, seven officials sketched a landscape of departmental AI activity under Secretary Kennedy's "One HHS" banner. The RFI names three levers—regulation, reimbursement, and research & development—but the webinar addressed only regulation and R&D; reimbursement was noted to be out-of-scope, for today.

Speakers positioned AI as a "third lever" alongside lifestyle and care infrastructure within the Make America Healthy Again agenda, emphasizing cost growth, chronic-disease management, agentic clinical AI (ARPA-H's ADVOCATE), caregiving and aging (ACL), and risk-proportionate FDA oversight.

Very Brief Blog; Implementing Enhanced CLIA (HR 8890)

Repr. Dr. Dunn of Florida has introduced CLIA enhancement legislation.   Read the 45-page bill here, see a law firm introduction to it, f rom Covington, here.

Over at LinkedIn, Dr Joe Lennerz provides a detailed and illustrated depiction of how the legislation might be implemented and how, and when, it would affect real-world laboratory tests in your lab.

Find it here:

https://www.linkedin.com/pulse/what-would-enhancing-clia-act-2026-look-like-practice-joe-lennerz-cdibe/

##

The legislation is well-written, with many new ideas fitted together.  But it is also at any early stage, being sponsored by Dr. Dunn alone (who is retiring soon); it does not have a Democrat House co-sponsor nor any Senate sponsor.  (Often, stakeholders try to introduce legislation with 4 sponsors, 2 Rep., 2 Dem, 2 House, 2 Senate.)

Gapfill-ology 2026: Variances in MAC Gapfill Proposals Summer 2026

This year 18 codes are in the Gapfill process, with comments accepted to July 13, 2026.

Find the spreadsheet at the CMS CLFS webpage, scrolling down to Gapfill proposals.

https://www.cms.gov/medicare/payment/fee-schedules/clinical-laboratory-fee-schedule-clfs/annual-public-meetings

What's Up/

There were only 2 codes of 18 where MolDx and Novitas prices aligned (0420U, 0569U).  

But there were 8 of 18 where MolDx and NGS MAC aligned.

Biggest Oddities

I counted 9 codes where, to my eye, there were substantial differences among the MAC prices.

For example, for 0552U, MolDx was $1160, while Novitas was $164 higher and NGS MAC was $835 lower.  

Two codes were really bizarre.  For 87182, MolDx was $9.65 and Novitas was $4 higher.  But NGS MAC was $640 higher than that. ?!?

For 0594U, MolDx was $12.05 and Novitas was 42 cents higher.  But NGS MAC came in at $2498 higher than MolDx.

The nine codes with wide variances at one or two MACs, relative to MolDx and its Median, are shown in the table below.  Click to enlarge.  Find a Google Sheets version of my work here, note it has multiple tabs.

As in past years, the required "rationales" are usually boilerplate (the same for every result).

click to enlarge


Wednesday, June 24, 2026

The Mystery of Wellpoint Federal (aka NGS MAC) CAC Meetings

Recently, Noridian announced that on August 20, 2026, there will be a Contractor Advisory Meeting on the topic of tests for neurodegeneration.   it will be multi-contractor, including CGS, Noridian, Wellpoint Federal, and Palmetto.   

See an announcement at Noridian here, at CGS here.

I didn't see Novitas as a co-sponsor and at least so far, nothing on their CAC calendar page.

But here's a mystery. By myself, I couldn't find any kind of CAC webpage for NGS MAC.  I did learn that since April 1, this MAC generally writees "Wellpoint Federal" as its name, but is generally still listed as NGS MAC by CMS and it still uses the ngsmedicare.com website..   

To jump to the finish line, there IS a CAC web page at NGS Medicare:.

https://www.ngsmedicare.com/web/ngs/contractor-advisory-committee-cac?selectedArticleId=3261501&lob=96664&state=97178&rgion=93623

But you can't get to it by google searches like - NGS medicare contractor advisory committee

And you can't get to it by entering that phrase into the NGS Medicare search box on its own website.  That search CAN get a few individual standalone meeting announcements. And those announcements, may inside their text include a link to the NGS MAC home page.  And once you get to the CAC home page, it seems to be framed as a subpage of "Medical Policies / LCDs" but ... if you are on the Medical Policies LCDs page, it doesn't link forward to the CAC page.

OK, so there IS such a NGS CAC home page, but it's not easy to find.  It's still true, for example that AI can find all the CAC webpages except NGS, and it's still true, that even when you have the link given to you, and know what it is, it's hard to re-create a path to it.

###

Here's Chat GPT web research:

It writes:  I checked the six MACs you named. The pattern is uneven.

MACDedicated CAC information page?What I found
NoridianYes — strongNoridian has a clear CAC landing page under Policies → LCD → Contractor Advisory Committee. It has overview language, upcoming meetings, prior meetings, agendas, key questions, recordings, and transcripts. It explicitly says all CAC meetings are open to the public. (Medicare)
PalmettoYes, but titled “LCD Development Meetings,” not simply CACPalmetto’s page has a CAC section explaining that Palmetto periodically hosts CAC meetings, uses formal CAC panels, records meetings, and posts meeting dates/times and materials there. It also covers open meetings on the same page. (Domino Apps)
WPS GHAYes-ish; less clean as an indexWPS has a page titled “The J5 & J8 Contractor Advisory Committee (CAC),” plus CAC volunteer and meeting-document pages. Search snippets show it describes CAC as advisory and evidence-focused for LCD development, but the site did not render cleanly in the browser tool. (WPSGHA)
NGSI did not find a dedicated public CAC landing pageTargeted searches of ngsmedicare.com for “Contractor Advisory Committee,” “CAC,” “Local Coverage Determination,” and the IVL CAC produced no NGS CAC landing page. However, NGS clearly participates in and hosts CACs; other MACs list NGS-hosted meetings, including the August 20, 2025 IVL CAC. (FCSO Medicare)
NovitasYesNovitas has “Contractor advisory committee (CAC) meetings” pages for JH/JL. The search result text says CAC meetings are held to obtain advice about the strength of published evidence. CMS’s MCD for a Novitas proposed LCD links directly to Novitas JH/JL CAC meeting pages. (Novitas Solutions)
FCSO / First CoastYes — strongFCSO has a “Proposed LCD: CAC meetings” page, a multi-jurisdictional CAC page, CAC minutes pages, and a CAC fact sheet. The CAC page says all CAC members and the public are welcome by webinar, prior meetings are recorded/transcribed, and registration opens about two weeks before meetings. (FCSO Medicare)

Practical finding

The strongest “clean CAC landing page” is Noridian. FCSO is also strong, though split across several pages. Palmetto has a functional page, but it is nested under LCD Development Meetings rather than branded as a standalone CAC index. (It seems that CMS prefers to call them Contractor Advisory Meetings" while Palmetto prefers to call them "LCD Development Meetings") Novitas has dedicated CAC pages, although the site is JavaScript-heavy and not always easily rendered. WPS has CAC information, but it looks more fragmented. 

So: NGS is the outlier: the web page was harder to find that the several other MACs.

That matters for your point: a meeting can be technically public, recorded, and linked somewhere, while still being poorly discoverable if the host MAC does not maintain a predictable CAC index page.



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Wellpoint Federal is the new name of NGS MAC since April 1, 2026.   See Wellpointfederal.com vs NGSMedicare.com.   Use the latter link "during the transition."



Part 2: DOJ Treasure Trove of Health Fraud:Twelve Themes and Two Defenses

Yesterday, I published a long blog taking a first look at a 'treasure trove' of over 300 DOJ case summaries and some 300 actual full length court documents.  Yesterday I focused on the 300 case summaries.

In today's blog, I downloaded the first 20 of the 300 full-length court documents (complaints, indictments), and asked Chat GPT 5.5 to take the role of a law school professor expert in healthcare fraud.

Today's AI-written blog summarizes then catalogs twelve courtroom themes.  And then — presents two "defense" cases in detail.

Find yesterday's blog here.  

Find the 300 court cases at an online archive at DOJ here.


###
As often with DOJ press materials, adverse behavior is alleged and not convicted, with court cases underway.
###

 

  1. The “reimbursable clinical fiction” is the core unit of fraud.

  2. Medical necessity is the hinge, but scienter is the lock.

  3. Certification is the bridge from regulatory violation to fraud.

  4. Kickbacks are alleged as causation, not merely corruption.

  5. Provider enrollment is a fraud chokepoint.

  6. The cases separate nominal clinicians from economic architects.

  7. Documentation is often alleged to be the crime scene.

  8. Vulnerable patients are not incidental to the theory.

  9. Program-design gaps become fraud opportunities.

  10. Laundering and forfeiture convert billing cases into proceeds cases.

  11. Civil, criminal, and administrative theories are increasingly braided.

  12. The best defense themes arise from the same architecture as the prosecution themes.

###

Common Principles in the 

DOJ Health Care Fraud Cases

The recent DOJ health care fraud pleadings are not merely a stack of unrelated indictments, informations, complaints, and settlements. Read together, they form a compact seminar in how modern health care fraud is alleged, structured, documented, and defended. The cases range across laboratories, pharmacies, wound care, hospice, durable medical equipment, behavioral health, controlled substances, and provider-enrollment schemes. Yet the recurring principles are strikingly consistent.

At the center is not simply a false bill. It is a false clinical premise converted into a reimbursable claim.

The government’s basic theory in case after case is that the defendant did not merely ask Medicare or Medicaid to pay too much. Rather, the claim allegedly represented that a qualifying medical event had occurred when, in the government’s view, the event was fabricated, distorted, induced, medically unnecessary, not documented, not performed, performed by the wrong person, or made possible by a kickback. The claim is the final electronic artifact. The alleged crime is the upstream manufacture of the medical reality that the claim purports to describe.

1. The “reimbursable clinical fiction” is the core unit of fraud.

The strongest unifying concept is the reimbursable clinical fiction. A hospice patient is represented as terminally ill. A laboratory test is represented as medically necessary and performed. A wound product is represented as clinically selected for an appropriate wound. A pharmacy claim is represented as a real prescription for a real patient need. A behavioral-health encounter is represented as a qualifying service provided by qualified personnel. A DME order is represented as physician-directed and beneficiary-needed.

The government’s theme is that these representations were not just incorrect; they were constructed. In the XXX laboratory case, the theory is that testing was routinely ordered without individualized medical judgment, sometimes not performed, and allegedly not used for diagnosis or treatment. In the XXX wound-care cases, the government’s theory is that sales and reimbursement incentives drove product selection rather than independent clinical judgment. In the XXX hospice case, eligibility documentation allegedly became a tool for converting non-qualifying or even impossible episodes into claims.

For prosecutors, this is a clean narrative: “They built paper medicine.” For defense counsel, the answer often begins by breaking apart that narrative: Was there an actual service? Was the service clinically arguable? Was any defect a billing failure, a documentation failure, or a knowing fraud? Did the defendant know the relevant facts at the time?

2. Medical necessity is the hinge, but scienter is the lock.

Medical necessity appears everywhere, but it does not carry the whole case by itself. In legitimate medicine, necessity is often probabilistic, contextual, and retrospective. A test may be low-yield but not fraudulent. A wound product may be expensive but not per se improper. A hospice prognosis may be uncertain. A behavioral-health service may be imperfect but still therapeutic.

The government therefore tends to make medical necessity persuasive by adding harder facts: no patient encounter, no specimen, no individualized assessment, blanket ordering, forged signatures, deceased patients, unqualified staff, impossible volumes, repeated high-dollar outliers, or records generated after the fact. In other words, the pleadings often use medical necessity as the doctrinal hinge, but objective evidence as the proof structure.

For defense lawyers, this distinction matters. A case built mainly on “that was unnecessary” is very different from one built on “there was no patient encounter, no specimen, no physician judgment, and the records were fabricated.” The former invites expert disagreement. The latter looks like fraud.

3. Certification is the bridge from regulatory violation to fraud.

The pleadings repeatedly emphasize enrollment forms, CMS-1500 forms, electronic claim submissions, EDI agreements, NPIs, CLIA-related obligations, provider participation agreements, and program manuals. This is not mere boilerplate. It is the legal bridge from operational misconduct to false claim.

A Medicare or Medicaid claim is treated as more than an invoice. It is a certified statement that the provider is eligible, the service was furnished as represented, the claim is accurate, and the service meets coverage conditions. The XXX laboratory FCA complaint makes this explicit: electronic claims certify medical necessity, truthfulness, accuracy, completeness, and the provider’s responsibility for claims submitted by its employees or agents. That certification architecture allows the government to argue that false clinical facts, false enrollment facts, and false compliance facts were material to payment.

For law professors, this is the jurisprudential heart of the modern FCA and health care fraud problem: when does regulatory noncompliance become payment fraud? These pleadings answer by stacking the elements. Not every violation is fraud. But a violation plus certification, plus materiality, plus payment, plus knowledge, plus concealment or remuneration, becomes the government’s preferred architecture.

4. Kickbacks are alleged as causation, not merely corruption.

The kickback allegations are especially important. They are not pled simply to show bad ethics. They are pled to explain causation.

In the XXX wound-allograft cases, kickbacks allegedly caused products to be ordered, patients to be found, providers to participate, and claims to be submitted. Sales representatives allegedly identified patients, selected or recommended product quantities, and received compensation tied to what could be billed. Providers allegedly became the credentialed conduit through which sales-driven care entered Medicare.

This matters because kickbacks solve a proof problem. Without kickbacks, a defendant may argue that the physician or clinician independently ordered the item. With kickbacks, the government argues that the medical judgment itself was corrupted before the claim was born. The kickback is thus not merely a separate Anti-Kickback Statute count; it becomes evidence that the resulting claims were false, tainted, and not the product of independent clinical decision-making.

For defense counsel, the counter-questions are equally important: Was the remuneration actually connected to referrals? Was it fair-market-value compensation for legitimate services? Did the clinician retain independent judgment? Did the defendant know the arrangement was unlawful? Was the claim false because of the remuneration, or was the government relying on guilt by association?

5. Provider enrollment is a fraud chokepoint.

Several cases show that provider enrollment is not administrative background. It is a fraud chokepoint.

The XXX reference-laboratory settlement is a compact example. The alleged misrepresentation was not that a particular lab result was wrong. It was that the provider-enrollment application concealed a relationship with another laboratory that was under suspension and investigation. The government’s theory is materiality at the threshold: had the relationship been disclosed, the program would not have enrolled the provider, and later claims would not have been payable.

This has broader implications. Health care fraud enforcement increasingly focuses on who gets access to the payment system in the first place. NPIs, ownership disclosures, managing-employee disclosures, related-party questions, prior suspensions, and nominee ownership structures are not clerical issues. They are gatekeeping representations. Falsehoods at the enrollment stage can make later claims suspect because the provider’s very right to bill was allegedly obtained by misrepresentation.

6. The cases separate nominal clinicians from economic architects.

A recurring feature is the distinction between the licensed person and the economic architect. The nominal clinician may be the prescriber, certifier, hospice physician, nurse practitioner, lab director, or ordering provider. But the alleged scheme is often designed by someone else: a marketer, owner, consultant, biller, sales representative, nominee owner, spouse, management company, or pass-through entity.

This distinction is central to both prosecution and defense. Prosecutors often argue that the person who designs the revenue machine “causes” the false claims, even if another person signs the order or submits the claim. Defense counsel may argue that causation is overextended: the billing company did not control medical judgment; the marketer did not submit the claim; the owner relied on professionals; the lab director did not know billing details; the clinician made an independent decision.

The cases therefore raise a common question: who is legally responsible for the final claim? The person who obtained the patient? The person who signed the order? The person who submitted the claim? The person who structured the kickback? The person who owned the entity? The government often answers: all of them, if they knowingly joined the mechanism that made the claim false.

7. Documentation is often alleged to be the crime scene.

In ordinary compliance, documentation is evidence of care. In these pleadings, documentation is often alleged to be the instrument of fraud.

The government repeatedly alleges false orders, forged signatures, backdated records, prefilled forms, cloned notes, false certifications, records generated after audits, false progress notes, and eligibility documents designed to pass program scrutiny. In the XXX hospice case, the alleged fraud turns heavily on patient status, certifications, identifiers, timing, and records. In the XXX laboratory and pharmacy cases, requisitions, prescriptions, orders, claims data, and audit responses become central evidence.

This is an important conceptual point. Health care fraud is rarely proven only by showing money moved. It is proven by comparing three records: the clinical record, the billing record, and the real-world patient event. The gap between those three is where the case lives.

8. Vulnerable patients are not incidental to the theory.

Several pleadings involve populations with reduced practical ability to detect, resist, or report exploitation: elderly Medicare beneficiaries, hospice patients, substance-use treatment patients, Medicaid beneficiaries, Native American fee-for-service Medicaid members, behavioral-health patients, and beneficiaries whose identities were used without meaningful consent.

This vulnerability does legal work. It helps explain why a scheme could scale. It supports the government’s narrative that the defendants selected populations less likely to challenge the claim event. It may influence detention, sentencing, restitution, and judicial perception. It also makes the cases more than financial fraud cases; they become abuse-of-trust cases.

For defense counsel, this creates a risk of moral overhang. Even where patient harm is not an element of the charged offense, the narrative of vulnerable beneficiaries can dominate the case. The defense must separate emotional gravity from statutory proof without appearing indifferent to patient welfare.

9. Program-design gaps become fraud opportunities.

The XXX pharmacy case is especially instructive because it shows how fraud allegations can arise from a policy transition. The alleged scheme exploited a temporary prior-authorization suspension for certain high-reimbursing drugs. The government’s theory is that defendants recognized a payment-system gap and flooded it with claims.

This category is likely to grow. Health care is full of temporary flexibilities, emergency policies, payment transitions, telehealth expansions, prior-authorization changes, new codes, and high-priced products. Fraud enforcement follows the gaps created by those transitions. The legal challenge is separating criminal exploitation from aggressive but facially permissible use of a changing rule.

That distinction should matter to both sides. A prosecutor will say: the defendants knew the clinical predicate was false, even if the payment window existed. A defense lawyer will say: the rule changed, the payment system accepted the claims, and the government is retrofitting criminal intent onto a messy administrative transition.

10. Laundering and forfeiture convert billing cases into proceeds cases.

The charging documents often do not stop at health care fraud. They add money laundering, monetary transactions in criminally derived property, seizure, forfeiture, substitute assets, and proceeds tracing. This is not incidental. It changes the litigation.

For prosecutors, proceeds allegations make the fraud tangible: real estate, vehicles, investment transfers, luxury goods, pass-through accounts, shell entities, foreign wires. These facts are narratively powerful because they show what the fraud allegedly bought. They also support asset restraint and potential recovery.

For defense counsel, proceeds counts create separate battlegrounds. Were the funds actually criminally derived? Was the transaction sufficiently connected to the specified unlawful activity? Did the money move before or after the alleged fraud was complete? Can the government trace the funds? Are legitimate revenues commingled? Does the forfeiture amount reflect gross proceeds, net proceeds, or loss?

11. Civil, criminal, and administrative theories are increasingly braided.

The cases show a continuum rather than a clean division. The same conduct can be framed as criminal health care fraud, conspiracy, kickbacks, money laundering, FCA false claims, reverse false claims, unjust enrichment, payment by mistake, provider-enrollment fraud, exclusion exposure, licensing misconduct, or controlled-substance violations.

For prosecutors, this allows strategic selection. The most egregious cases become criminal. Others resolve civilly. Some combine restitution, forfeiture, exclusion, and compliance consequences. For defense counsel, it means early characterization matters. A case may begin as an audit, become a suspension, become an FCA investigation, and later become a criminal matter if the government finds texts, emails, false records, kickbacks, or concealment.

The practical lesson is that health care fraud risk is not a single legal category. It is an ecosystem.

12. The best defense themes arise from the same architecture as the prosecution themes.

These cases also reveal the likely defense map. The principal defense issues are not mysterious. They are scienter, materiality, causation, medical necessity, reliance, delegation, loss, and regulatory ambiguity.

Scienter asks whether the defendant knew the claim was false, or merely operated in a confusing reimbursement environment. Materiality asks whether the misstatement actually mattered to payment. Causation asks whether the defendant caused the claim or was too remote from billing. Medical necessity asks whether the clinical judgment was fraudulent or merely debatable. Reliance asks whether the defendant reasonably relied on clinicians, billers, lawyers, consultants, or program guidance. Loss asks whether billed amounts, paid amounts, or medically worthless services are the correct measure. Regulatory ambiguity asks whether the government is criminalizing uncertainty.

The strongest government cases anticipate these defenses by alleging objective impossibilities, admissions, kickbacks, no services, fake records, or concealment. The weaker or more contestable cases are those that depend mainly on disagreement over clinical judgment or complex payment conditions.

Bottom Line

The common principle across these cases is that health care fraud is now charged as a systems crime. The alleged misconduct is not simply that someone lied on a claim form. It is that defendants allegedly learned the operating logic of Medicare, Medicaid, TRICARE, or another program, found the weak point, and converted clinical trust into reimbursable paper.

That is why these cases matter to prosecutors, defense attorneys, and law professors. They sit at the boundary between medicine, billing, administrative law, criminal law, and organizational design. The government’s best narrative is industrialized false medicine: patients, codes, forms, signatures, and program rules assembled into a revenue engine. The defense’s best response is precision: not every coverage violation is fraud, not every unnecessary service is criminal, not every payment error is material, and not every actor in the chain caused the false claim.

The serious legal work lies in that boundary.

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CASE STUDY 01:  MEDI-CAL PHARMACY, THE INDICTMENT AND THE DEFENSE

For #1, I’d pick the XXX Medi-Cal pharmacy complaint as the best defense-study example. It is factually serious, but analytically rich: it involves a temporary prior-authorization suspension, high-reimbursing non-contracted generic drugs, alleged sham prescriptions, alleged kickbacks, disputed medical necessity, causation through intermediaries, and the procedural posture of a criminal complaint supported by a probable-cause affidavit rather than a trial-tested record. The complaint alleges about $269 million in false claims and about $178 million paid, and it describes emails, beneficiary data, prescription forms, cooperator/witness statements, and approximately $279,000 allegedly paid to the XXX defendant.

A Defense-Strategy Case Study: 
The XXX Medi-Cal Pharmacy Complaint

A particularly useful case to study from the defense perspective is the XXX Medi-Cal pharmacy complaint. As alleged, the defendant participated with others in a large pharmacy-billing scheme involving non-contracted generic drugs during a period when Medi-Cal had temporarily suspended prior authorization requirements as part of a pharmacy-benefit transition. The complaint alleges that prescriptions were generated for beneficiaries without real medical necessity, that some medications were not provided, that a pharmacy billed Medi-Cal for high-reimbursing drugs, and that the defendant received payments allegedly derived from the scheme. The case is especially interesting because it sits at the intersection of fraud, policy transition, medical necessity, kickbacks, causation, and the difference between aggressive exploitation of a payment window and criminal deception.

The defense should not begin by denying that the billing numbers look dramatic. They do. A better strategy is to force precision. The government’s narrative is “massive fraud following a prior-authorization suspension.” The defense should reframe the case around individual elements: What exactly did this defendant know? What exactly did this defendant do? Which specific prescriptions are charged or provable? Which medications were actually dispensed? Which patients were actually harmed? Which claims were false because of non-dispensing, which because of medical necessity, and which merely because the government now dislikes the economic effect of a temporary payment policy?

The first defense theme should be regulatory ambiguity and policy context. Medi-Cal temporarily suspended prior authorization for many prescription drugs during a program transition. That does not immunize fraud, but it matters greatly to scienter. The defense should argue that a fast-changing public program opened a legitimate billing pathway that Medi-Cal itself chose to create. The government will say the defendants exploited a safeguard failure. The defense should answer that exploiting an available coverage pathway is not itself fraud unless the government proves knowing falsity claim by claim. This is especially important if the charged conduct occurred in a confusing window when providers, pharmacies, prescribers, marketers, and intermediaries were all adjusting to new Medi-Cal Rx rules.

The second defense theme should be role separation. The defendant appears to be alleged as a facilitator or intermediary, not the pharmacy, not the state program, and not necessarily the licensed prescriber. The defense should isolate the defendant’s actual legal duty. Did the defendant submit claims? Did the defendant have direct access to the pharmacy’s billing system? Did the defendant control dispensing? Did the defendant make clinical determinations? Did the defendant know whether each beneficiary was seen, whether each medication was medically necessary, or whether each medication was dispensed? The government will try to collapse the chain into one conspiracy. The defense should pull it apart into separate actors: prescriber, pharmacy, marketer, billing entity, patient-contact person, and payer.

The third defense theme should be medical necessity as a contested clinical concept. The government’s strongest allegations are that prescriptions were generated without patient evaluation. But the defense should resist allowing “not medically necessary” to become a slogan. For each representative claim, the government should be forced to prove why the drug was unnecessary for that patient, what records existed, what diagnosis or complaint was documented, and what the prescriber understood. If the medication was facially within a prescriber’s authority and the patient had a plausible clinical indication, the defense can argue that the government is substituting retrospective skepticism for proof of fraud. The defendant’s non-clinician status, if applicable, strengthens this point: a non-clinical intermediary may not be able to adjudicate medical necessity.

The fourth defense theme should be causation and materiality. Medi-Cal paid the pharmacy, not the defendant. The defense should examine whether Medi-Cal would have denied payment if it knew the precise facts attributed to this defendant, as opposed to facts known only to the pharmacy or prescriber. If the prior-authorization requirement was suspended, the usual materiality story becomes more complex. The defense can argue that the alleged falsity must be tied to a condition of payment that remained operative during the suspension. The government may still prove falsity through lack of medical necessity, non-dispensing, or kickbacks, but it should not be allowed to imply that the mere absence of prior authorization was material when prior authorization had been suspended.

The fifth defense theme should be payments do not automatically equal kickbacks. The complaint alleges payments to the defendant, but the defense should characterize them, where possible, as consulting, administrative, marketing, patient-support, or business-development compensation unless the government proves unlawful remuneration tied to federal-health-care-program referrals. The defense should demand specificity: what service was supposedly bought, which referral was supposedly induced, what claim followed, and what evidence shows corrupt intent? If contracts, invoices, or business records exist, the defense should use them not as complete exoneration but as evidence that the relationship had at least a facial business form inconsistent with simplistic bribery.

The sixth defense theme should be attack the complaint posture. This is a complaint supported by an affidavit. It is a probable-cause document, not a conviction, not a tested indictment record, and not a set of facts found by a jury. The affidavit likely compresses witness statements, claims data, emails, bank records, and investigator interpretations into a single government narrative. The defense should stress that probable cause is a low threshold and that the case will depend on cross-examination, full context, document completeness, witness incentives, and claim-by-claim proof.

The seventh defense theme should be cooperator credibility and narrative contamination. If the government relies on pharmacy owners, prescribers, marketers, or other participants, the defense should assume those witnesses have powerful incentives to shift blame. A prescriber may say the defendant knew patients were not being seen; a pharmacy actor may say the defendant knew claims were false; a marketer may say payments were corrupt. The defense should test whether those statements are corroborated by contemporaneous documents or whether they are retrospective blame allocation by people with their own exposure.

The defense should also prepare for the government’s best facts. Emails attaching prescription forms, beneficiary lists, payment records, and alleged sham documentation will be hard to explain away if they are clear. The defense therefore should not overpromise innocence. A more credible strategy is to distinguish bad optics from criminal elements. It may be true that the business was aggressive, messy, highly profitable, and poorly supervised. The issue for trial is whether this defendant knowingly and willfully caused false claims to be submitted.

The ideal defense narrative is therefore: This case arose from a chaotic Medi-Cal policy transition. The state temporarily removed a payment safeguard. A pharmacy and licensed prescribers were responsible for dispensing, ordering, billing, and clinical judgment. The defendant was at most an intermediary in a business network and did not knowingly cause false claims. The government is using eye-popping dollar figures and the hindsight of an enforcement investigation to convert a complicated reimbursement environment into a simple fraud story.

That is not a guaranteed acquittal strategy. The alleged facts are serious. But it is the most intellectually coherent defense: narrow the defendant’s role, separate policy exploitation from criminal falsity, force claim-level proof, contest scienter, and prevent the prosecution from using the size of the scheme as a substitute for proof that this defendant knowingly caused false claims.


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CASE STUDY 01:  WOUND CARE, THE INDICTMENT AND THE DEFENSE


For #2, I’d use the XXX wound-allograft sales-executive indictment as the second strong defense-study case. It is useful because the government’s theory is sweeping — $1.2B billed, $614M paid, alleged kickbacks, sham invoices, pass-through accounts, vulnerable hospice patients, and personal proceeds — but the defense issues are also sophisticated: a sales executive versus treating clinicians, pricing versus kickbacks, Medicare reimbursement mechanics, causation, medical necessity, and proof of willful criminal intent. The DOJ summary says the defendant was charged by indictment with health care/wire fraud conspiracy, health care fraud, kickback conspiracy, paying kickbacks, and transactional money laundering.

A Second Defense-Strategy Case Study:
The XXX Wound-Allograft Sales-Executive Indictment

A second especially interesting case from a defense perspective is the XXX wound-allograft sales-executive indictment. As charged, the defendant was a senior sales executive for a company selling expensive amniotic wound allografts. The government alleges a large national scheme in which allografts were purchased, ordered, and billed through arrangements involving sales representatives, medical providers, alleged sham invoices, pass-through bank accounts, and kickbacks. According to the government’s theory, these financial incentives caused elderly Medicare patients, including some terminally ill or in hospice care, to receive medically unreasonable and unnecessary wound allografts, leading to approximately $1.2 billion in claims and about $614 million in payments.

This is a powerful prosecution narrative, but it is also a very instructive defense case because the defendant is not described as the bedside clinician, the treating physician, the nurse practitioner applying the graft, the Medicare-enrolled billing provider, or the person certifying medical necessity. He is alleged to be an economic and sales-side architect. That makes the defense problem different from the classic “doctor billed for services never rendered” case. The defense should not try to make the case sound small. It is not small. The better strategy is to separate commercial leadership from criminal causation.

The first defense theme should be role separation. The government will try to collapse the chain: sales executive, product distributor, sales representatives, providers, patients, claims, and payments all become one fraud machine. The defense should pull the chain apart. Who actually evaluated the wound? Who decided whether the allograft was medically necessary? Who applied it? Who documented the wound? Who selected the billing codes? Who submitted the Medicare claim? Who certified the claim was accurate? A sales executive may influence product sales, pricing, distributor strategy, and customer relationships, but those facts do not automatically prove that he knowingly caused a false medical claim.

The second defense theme should be medical necessity belongs first to clinicians. The government’s most emotionally powerful allegation is that vulnerable elderly patients, including hospice patients, received unnecessary allografts. The defense should not appear indifferent to that allegation. But it should insist that medical necessity is a patient-specific clinical judgment. Some wounds in elderly or medically complex patients may be difficult, chronic, recurrent, or clinically ambiguous. The fact that a patient was elderly, or even in hospice, does not by itself prove every wound-care intervention was fraudulent. The government should be required to prove, claim by claim or through statistically valid proof, that the allografts were unnecessary and that this sales executive knew they were unnecessary when the claims were submitted.

The third defense theme should be pricing and profit are not kickbacks by themselves. High product prices, aggressive sales incentives, rebates, discounts, and distributor margins may look ugly in hindsight, especially when Medicare reimbursement is large. But the defense should distinguish ordinary commercial economics from illegal remuneration. Was the alleged payment made to induce referrals or purchases reimbursable by federal programs? Or was it a discount, rebate, sales commission, consulting payment, distribution arrangement, or pricing structure with at least a facial business rationale? If invoices were inaccurate, were they intentionally sham documents designed to conceal kickbacks, or were they poorly structured commercial documents in a confusing reimbursement environment? The defense should force the government to prove corrupt purpose, not merely high margins.

The fourth defense theme should be causation is the hard element. The indictment theory, as summarized, appears to require that the executive’s conduct caused providers to submit false claims. That is a long causal chain. The defense should ask: Did the executive direct providers to bill Medicare? Did he know the providers’ actual acquisition cost? Did he instruct them what amounts to put on claims? Did he know what was in the patient charts? Did he know which patients were hospice patients? Did he know which wounds were infected, nonhealing, or unsuitable? Did he know any specific claim was false? The prosecution will use scale, emails, payment flows, and sales patterns to infer knowledge. The defense should answer with individualized proof problems: volume does not replace element-by-element causation.

The fifth defense theme should be attack the “sham invoice” label. The word “sham” is doing enormous work for the government. The defense should avoid accepting it. An invoice can be mistaken, incomplete, nonstandard, commercially aggressive, or even misleading without proving beyond a reasonable doubt that the defendant intended a federal health care fraud. The defense should examine whether invoice practices were reviewed by accountants, lawyers, reimbursement consultants, customers, or internal compliance personnel. If the providers themselves chose how to report acquisition cost or seek reimbursement, the defense should argue that responsibility for any billing representation rested with the billing provider, not the product seller.

The sixth defense theme should be separate Anti-Kickback Statute exposure from health care fraud exposure. The government will likely argue that kickback-tainted claims are false claims. The defense should still insist on precision. A possible AKS violation does not answer every question about health care fraud, wire fraud, intent, loss, or money laundering. If remuneration is disputed, the defense contests AKS. If remuneration is proven but medical necessity is disputed, the defense contests the scope of false claims. If claims were paid for products actually furnished, the defense contests loss. If the funds were ordinary business proceeds before any adjudication of fraud, the defense contests laundering and forfeiture theories.

The seventh defense theme should be use compliance ambiguity carefully. The defense should investigate whether the company had compliance materials, training, contracts, legal opinions, reimbursement guidance, fair-market-value analyses, or policies that the executive can point to. This is not a magic shield. But it can be powerful on willfulness. A sales executive who operated in a documented business structure, with lawyers or compliance personnel involved, is different from someone secretly paying cash in envelopes. The defense should look for evidence that the defendant believed the arrangements were lawful commercial relationships, not hidden inducements for federal program business.

The eighth defense theme should be humanize the business function without trivializing the conduct. A jury may dislike a defendant who made large sums while vulnerable patients were used in the scheme. The defense therefore must avoid sounding as if it is defending exploitation. The better narrative is narrower: this defendant sold a real wound-care product, through a commercial organization, to providers who had independent clinical and billing obligations. If some providers abused Medicare, or if some salespeople crossed lines, the question remains whether this defendant knowingly joined a criminal agreement to submit false claims.

The ninth defense theme should be contest loss and proceeds. The government’s large numbers will dominate the case unless narrowed. The defense should distinguish billed charges, allowed amounts, paid amounts, company revenue, gross product revenue, net profit, defendant compensation, and allegedly tainted transactions. If allografts were actually delivered and applied, the defense should challenge any loss theory that treats every dollar as worthless. If only a subset of claims is medically unsupported or kickback-tainted, the defense should resist extrapolation beyond reliable proof. On money laundering, the defense should test whether transactions involved criminally derived property, whether the defendant knew that, and whether the government can trace funds through business accounts.

The final defense narrative could be: This is a case about a high-dollar Medicare product market that the government now portrays as a fraud machine. But the defendant was a sales executive, not the treating clinician, not the Medicare billing provider, and not the person making patient-specific medical necessity decisions. The government must prove more than aggressive sales, high profits, and bad outcomes. It must prove beyond a reasonable doubt that this defendant knowingly caused false claims and knowingly paid unlawful remuneration, not merely that he participated in a lucrative and controversial wound-care business.

This is not an easy defense. The alleged facts are severe, and “sham invoices,” “pass-through accounts,” hospice patients, luxury purchases, and massive payments are all damaging themes. But as a defense case study, it is excellent because the best defense is not denial of scale. It is disciplined narrowing: role, knowledge, causation, clinical independence, lawful commercial structure, claim-level proof, and loss.

Tuesday, June 23, 2026

Part 1: DOJ Releases Little-Remarked Treasure Trove of Medical Fraud Data

On June 23, 2026, you couldn't swing a cat without encountering news articles about a big HHS anti-fraud operation.   Most of the first-day articles stuck close to a couple case studies and near-the-surface source material.

NY Times:

CNN:

  • Today we'll take a first look at the data. 
    • Where is Medicare "hackable?"
    • See also several Appendices at bottom.
  • Tomorrow, we'll look at overall themes as well as two defense strategies.

DOJ released an interesting trove of data, though, across several websites.

Website One:

Main press release with some key anecdotes and graphics - plus links to richer data.

Website Two:

Multiple screenfuls of infographics.

Website Three:

Verbal summarizes of dozens of cases, a paragraph each.  Chat GPT counts 334 cases, which meets a sanity check (that's ~4 per page x 79 pages, which validates ~ 300 count).

Website Four:

This website is an inventory of dozens and dozens of court documents - variously indictments, comlaints, and "information."   It's 15 pages, about 20 rows per page, so again, circa 300.  Chat GPT counts 246.

Chat GPT counts the actual court documents as 131 federal, 115 state (246).  86 are indictments, 67 are 'information," 50 complaints, 15 settlements, 21 arrest warrants.  For more on the court documents, see tomorrow's blog.  

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As often with DOJ press materials, adverse behavior is alleged and not convicted, with court cases underway.

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Here's a Chat GPT essay about the 344 case summaries.



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The DOJ’s 334-Case Fraud Takedown: 

A Map of Where Medicare and Medicaid Are Most Hackable

The DOJ page describes “case summaries,” but the scale is better understood as a panoramic audit of how health care fraud mutates across benefit designs. The cases are not random. They cluster around a few recurring pressure points: high-reimbursing products, vulnerable patients, loose documentation pathways, paid referrals, nominee owners, identity misuse, and the conversion of Medicare or Medicaid payments into cash, real estate, luxury cars, watches, jewelry, and shell-company transfers. The 334 summaries are therefore less a list of isolated bad actors than a map of where public health insurance is most mechanically exposed. The DOJ’s own summaries range from amniotic wound allografts and durable medical equipment to hospice, laboratory testing, behavioral health, COVID-19 tests, genetic testing, pharmacy claims, and fake licensure schemes.

The first striking theme is product arbitrage. Fraud follows the margin. In these summaries, the most spectacular dollar figures arise where a product or service can be billed repeatedly, at high unit prices, with thin real-time verification. Wound allografts are the poster child. The allegations often describe elderly Medicare patients, sometimes terminally ill or in hospice, receiving expensive skin substitutes that were unnecessary, not properly applied, applied to inappropriate wounds, or supported by fabricated records. One Arizona-related case alleges a $1.2 billion wound allograft scheme involving sham invoices, kickbacks, vulnerable patients, and approximately $614 million paid; another wound case cited more than $906 million billed and about $297 million paid.

A second theme is that fraud often lives in the gap between clinical need and billing documentation. The claim form says one thing; the patient’s clinical reality says another. Hospice cases allege patients who were not terminally ill, sometimes with beneficiaries induced or misled into enrollment. Laboratory cases allege genetic, respiratory, urinary, toxicology, or other tests ordered without real medical necessity, often through paid marketing or recycled beneficiary information. DME cases allege braces or supplies that were unnecessary, ineligible, or procured through kickbacks. This is the grammar of health care fraud: create a paper trail that looks like medicine, then bill as if medicine happened.

A third theme is industrialization. These are not merely “doctor billed wrong code” stories. Many summaries describe businesses built to manufacture reimbursable events: marketers acquire patients; call centers obtain or buy beneficiary information; clinicians or nominal prescribers sign orders; billing entities transmit claims; shell companies move the money; and consultants explain how to avoid scrutiny. The alleged COVID-19 test schemes are almost pure industrial fraud: beneficiaries did not request tests, yet their Medicare numbers were used to ship or bill for kits. In one Florida case, Medicare beneficiary identification numbers were allegedly purchased and used both for COVID-19 tests and for laboratory testing referrals.

A fourth theme is the exploitation of administrative transitions. Fraudsters watch policy changes the way investors watch markets. The California Medi-Cal pharmacy case is a vivid example: the complaint alleges that a temporary suspension of prior authorization for certain non-contracted generic drugs created an opening for hundreds of millions in claims. According to the complaint, cheap generic ingredients were packaged into high-reimbursing products, prescriptions were generated without real patient evaluation, and Medi-Cal paid more than $178 million on roughly $269 million in false claims.

A fifth theme is that fraud often targets the least visible patients. The summaries repeatedly involve elderly beneficiaries, people with substance use disorders, Medicaid patients, Native American health program enrollees, hospice patients, behavioral health patients, and residents of nursing or assisted-living settings. In one Arizona Medicaid case, the alleged victims were patients in AHCCCS’s American Indian Health Program, with claims for services not provided, substandard, medically unnecessary, or tainted by kickbacks.

The final pattern is personnel fraud: fake nurses, fake credentials, impersonated providers, forged signatures, and stolen identities. These cases are smaller in dollars but disturbing in a different way, because they attack the licensing assumptions beneath the health care system. A person who fakes nursing credentials is not just stealing wages; she is turning the provider credential itself into a billing instrument.

The genius-level TLDR is this: modern health care fraud is rarely a single false claim. It is usually a business model that discovers a payable code, a weak verification point, a vulnerable patient population, and a way to convert medical documentation into cash. Medicare and Medicaid are built on trust, speed, delegation, and documentation. The takedown shows what happens when those same virtues are reverse-engineered by people who understand the payment system almost as well as the people who run it.

SIDEBAR: Six Surprises Hidden in the 334 Case Summaries

1. The biggest fraud theories were not always about exotic medicine.
Some of the largest alleged schemes turned on ordinary administrative vulnerabilities: beneficiary numbers, provider enrollment, prior authorization gaps, routine orders, and electronic claims. The Medi-Cal pharmacy case is especially striking because the alleged opening was a temporary suspension of prior authorization during a payment-system transition, which allegedly enabled $269 million in false claims in just 11 months.

2. Wound allografts became the new “molecular testing” of fraud headlines.
A fraud-watcher might expect DME, home health, opioids, or genetic testing. But the summaries repeatedly spotlight amniotic wound allografts, including a $1.2 billion alleged scheme involving sham invoices, kickbacks, pass-through bank accounts, and elderly patients, some terminally ill or in hospice.

3. AI appears, but not where you might expect.
The AI hook was not a futuristic diagnostic algorithm; it was allegedly fake consent recordings. In one COVID-19 test-kit case, the defendant allegedly supplied laboratories with recordings in which Medicare beneficiaries supposedly agreed to receive tests, and the source of the recordings reportedly said they were AI-generated.

4. Hospice fraud had a macabre identity-theft variant.
The hospice cases were not limited to patients who were not terminally ill. One Los Angeles case allegedly involved buying the identifying information of already-deceased beneficiaries from a mortuary employee, then purporting to enroll them in hospice before death to make the hospice statistics look better.

5. The “patient” was sometimes less a patient than an entry in a production process.
Several schemes appear to have treated beneficiaries as raw material: names to be bought, induced, enrolled, called, shipped to, or billed against. In the Arizona AHCCCS case, the alleged target population was Native American Medicaid members in a fee-for-service program, with claims for services that were allegedly not provided, substandard, medically unnecessary, or tainted by kickbacks.

6. Credential fraud was its own quiet category.
Not all the surprising cases were billion-dollar billing machines. Some involved people allegedly posing as licensed health professionals: for example, an Idaho defendant allegedly used victims’ names and nursing licenses to obtain jobs at facilities including behavioral health, rehabilitation, skilled nursing, and hospice businesses.


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Appendix

1. Information vs Indictment
2. Labs, Not Predominant
3. Virtual Fraud
4. Nationalit/Regions

1. Chat GPT adds, regarding the court cases:

Information. An information is a formal criminal charging document filed by prosecutors, rather than returned by a grand jury; it is commonly used when the defendant waives indictment or is expected to plead/resolve the case. In the Galbraith example, the document simply says “The United States of America charges” the defendant with health care fraud, then lays out the alleged Medicare hospice scheme.

Indictment. An indictment is a formal criminal charging document returned by a grand jury after prosecutors present evidence and the grand jury finds probable cause to charge the defendant. In the Lopez example, the caption identifies the “February 2026 Grand Jury,” and the charging language begins, “The Grand Jury charges.”

Complaint. A criminal complaint is usually an earlier-stage charging document supported by a sworn affidavit showing probable cause, often used to obtain an arrest warrant before indictment or information. In the Mareik example, the complaint says it is based on an attached affidavit, and the affidavit states it is offered to support a criminal complaint and arrest warrant and “does not purport to set forth all” the investigator’s knowledge.

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2. Labs?  Not Predominant in These Cases

Claude Opus tallied only about 18-19 cases of lab test fraud, whether genetics or COVID.  Chat GPT tallied only 16.  (Indictments online providef full names.)

Count: ~18 matters (19 filings if you split the two Puerto Rico actions).

Grouped by type:

Genetic / genomic testing

  1. CM (MDFL) — COVID test kits and genetic testing via beneficiary-info sales to labs.
  2. SM (MDFL/SDFL) — ASAP Labs, genetic and respiratory diagnostic testing kickbacks; $5M FCA + guilty plea.
  3. TB (SDFL) — $62M genetic-testing telemarketing/"doctor-chasing" scheme.
  4. DN (EDNC) — Andor Labs / Minerva Genetics; cancer genomic, toxicology, COVID; >$15M paid.
  5. AK(OR) — Oregon Clinical Laboratory, genetic testing to MA plans; >$15M.
  6. BE (NDTX) — Neva/Areahou Diagnostics; lab testing incl. genetic; $65M billed, $43M paid.

Clinical lab / toxicology / drug testing
7. LC (CDCA) — UTI tests, respiratory pathogen panels, oral tox screens; $9M billed (some specimens from deceased beneficiaries).
8. DD (CT) — reference-lab Medicaid enrollment fraud; related lab settled for medically unnecessary drug tests.
9. CB (DE) — medically unnecessary urine drug tests + tests never performed; $2.8M.
10. HK (EDMI) — false oral-fluid drug-test results; $150K civil.
11. WE (MDNC) — thousands of fictitious drug tests; $2.8M.

COVID-19 / respiratory lab billing
12. BL (MDFL) — ~152,000 COVID claims; $14.4M reimbursed.
13. BB (NDIL) — sold beneficiary info, AI-faked consent recordings; caused labs to bill ~$342M ($240M paid).
14. BI (EDLA) — RPP testing bundled with COVID; $51.7M billed, $28.4M paid.
15. SI (EDMI) — $566M COVID lab-test billing fraud.
16. BK(NDOK) — pharmacies billing Medicare/Medicaid for unrequested COVID tests.
17. MK et al. (NDTX) — COVID test-kit kickback scheme; >$73M billed.
18. CM (PR) — two filings: a civil settlement (services lacking medical necessity/ordering) and an indictment (repetitive/consecutive COVID-test billing, $114K).


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3. Electronic Fraud ("Virtual Fraud")

Claude Opus thinks as many has half the 344 cases might be electronic fraud rather than involving actual hospice care, lab tests, skin grafts, etc.  That's higher than I would eyeball-it, but I don't have a need to confirm and double-check it.
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Good distinction to draw, and it's actually the most analytically revealing cut you can make on this document. Three buckets, not two, because a meaningful slice fits neither:

Bucket What it means Rough count
Pure electronic (phantom billing, no clinical event) The service never happened to anyone. Fraud lives entirely in the claim/timesheet/record. ~150–160 (roughly half)
Improper clinical event A real test/device/drug/procedure occurred, but it was unnecessary, upcoded, diverted, or delivered by an unqualified/excluded person. ~80–90 (~25–30%)
Neither Pure theft/embezzlement, eligibility/identity fraud, PPP/SNAP/check fraud, abuse-or-neglect-only. ~30–40

These are estimates, not a census — many are genuinely mixed, and reasonable people would shuffle 20–30 entries between buckets. But the central finding is robust: pure electronic fraud is the largest category, and it dominates because of the state Medicaid Fraud Control Unit caseload.

What drives the "pure electronic" half. The state cases — Louisiana, Missouri, Illinois, Minnesota, Pennsylvania, Mississippi, Washington, Ohio, the Carolinas — are overwhelmingly personal-care-attendant / timesheet fraud. The signature fact pattern is "billed for services that could not have been provided": the aide was at a second job, in another state, at Walmart or Jack-in-the-Box, or the recipient was hospitalized, incarcerated, out of the country, or dead. No clinical event of any kind — just a phantom hour entered into an EVV system. Your X dead-beneficiary hospice example is the federal-scale version of exactly this: the BIN got billed, the corpse got no care. (X is technically mixed — he also enrolled living non-terminal patients who did get unwanted hospice — but the dead-enrollment portion is the purest of pure.)

The clean federal "pure electronic" entries are the ghost-supplier schemes: X's $3.76B and the Operation Gold Rush DME shells (XX $10.6B, XXXX), the 12-clinic Florida "bust-outs," X's nominee clinics, Xs fictitious eyelid surgeries run out of optical shops, X billing for Pediasure he never bought, Whipple billing for care while in Hawaii and after patients died.

What's genuinely improper-clinical (the real-event quarter). Three sub-patterns:

  • Real product, applied: the amniotic allograft cases (XXXXX) — these grafts were physically slapped onto infected, healed, or terminally-ill patients' wounds. Most DME-delivered and skin-substitute matters live here.
  • Real drugs, moved: the pill mills and diversions (X's 1.08M doses, X's 5.6M, the Houston clinics, XX, plus the Indiana nurse-diversion cluster). Pills genuinely changed hands.
  • Real test, run unnecessarily / upcoded: X's cardiovascular testing, the EEG case, Broussard's RPP panels, the Washington dental upcoding (ibuprofen billed as parenteral medicaments).

One conceptual wrinkle worth flagging for your taxonomy. There's a recurring sub-type that resists clean placement: a clinical event happened, but the wrong person did it — services rendered by an excluded provider (XX), by an unlicensed person under a licensee's number (XXX), or by LPNs billed as RNs (XX). Physically, care occurred; legally, the billable event never existed. I parked these in "improper clinical" because a human clinical interaction took place, but you could equally argue they belong with the phantom-billing group since the billed service (qualified-provider care) is fictional. Roughly 10–12 cases hinge on this judgment call, which is most of the wobble in the totals.

The headline, if you're writing this up: the modern takedown is mostly a billing-data crime, not a bad-medicine crime. The dollar value skews toward improper-clinical (allografts and DME, where a real expensive thing got delivered), but the case count skews heavily toward pure electronic fiction — phantom hours and ghost suppliers — because that's what EVV records, NPI-misuse, and dead-beneficiary matches catch cheaply at scale.

4. Nationality: Oz, Turkish, Armenian, 

A few months ago, there was a brouhaha in California when CMS's Dr. Oz talked about "Armenian" healthcare fraud mobsters, and Armenian stakeholders opposed Oz's view (Oz's family background is Turkish).

Claude Opus tried to classify cases by national or regional origin.  It did not identify any Armenian predominance in this national data.

Ex-Soviet. 10-12, DME shells

South Asian (inc Indian), 16-20, day care, DME

Sub-Saharan, 14-18, Behavioral health, hospice

Latino, 30, Medi-Cal timesheets, Florida clinics

East Asian (incl China), 12-15, hospice, lab, wound care

Middle Eastern, 8-10, pharmacy, DME