Going back decades (23andMe), FDA has honed in on "collection devices" to undercut venders of LDTs. Generally, the collection devices are at one point labeled RUO, but at another point, sold with patient care instructions.
There were several examples circa 1-1-2016. There are other examples in the past at regular intervals.
Here are a couple examples:
(a) “Diagnostic services,” except as otherwise provided under this subpart, includes any medical procedures or supplies recommended by a physician or other licensed practitioner of the healing arts, within the scope of his practice under State law, to enable him to identify the existence, nature, or extent of illness, injury, or other health deviation in a beneficiary.
(b) “Screening services” means the use of standardized tests given under medical direction in the mass examination of a designated population to detect the existence of one or more particular diseases or health deviations or to identify for more definitive studies individuals suspected of having certain diseases.
(c) “Preventive services” means services recommended by a physician or other licensed practitioner of the healing arts acting within the scope of authorized practice under State law to—
(1) Prevent disease, disability, and other health conditions or their progression;
(2) Prolong life; and
(3) Promote physical and mental health and efficiency.
(d) “Rehabilitative services,” except as otherwise provided under this subpart, includes any medical or remedial services recommended by a physician or other licensed practitioner of the healing arts, within the scope of his practice under State law, for maximum reduction of physical or mental disability and restoration of a beneficiary to his best possible functional level.
[43 FR 45224, Sept. 29, 1978, as amended at 78 FR 42306, July 15, 2013]
This is an informal, even deeper excurision into 2007-2008 OIG documents about in office ancillary services.
###
Please provide a detailed discussion of the ins and outs of this 2007-2008 rulemaking for the detail oriented reader who is fascinated by this CMS policy history
###
The 2007–2008 CMS rulemaking embedded in the CY 2008 Physician Fee Schedule final rule occupies a peculiar and revealing place in Medicare policy history. On its face, it is a technical exercise in billing rules—anti-markup provisions, reassignment mechanics, and definitional clean-ups. In reality, it represents one of CMS’s clearest attempts to reassert control over the economic logic of diagnostic testing without banning practices outright or rewriting the Stark statute. For readers fascinated by how CMS actually governs, this episode repays close attention.
By the mid-2000s, CMS had come to believe that it was confronting not a handful of bad actors, but a structural misalignment that had emerged organically from well-intentioned statutory and regulatory changes. Stark law prohibited physician self-referral, yet preserved the in-office ancillary services exception to avoid crippling integrated practice. The Medicare Modernization Act of 2003 liberalized reassignment rules, allowing billing entities to aggregate and bill for services furnished by others under contract. Separately, Medicare had long permitted billing for purchased diagnostic tests, constrained by anti-markup limits designed to prevent pure arbitrage. Each of these rules made sense on its own. Together, however, they created a permissive environment in which physician groups could order, control, and profit from diagnostic services that were increasingly detached from the clinical office itself.
CMS’s concern was not that these arrangements were facially illegal. In fact, many of the “pod lab” models that drew attention during this period were carefully structured to satisfy Stark’s technical requirements, including the centralized building definition. The problem, as CMS framed it, was that these arrangements undermined the original policy balance. They allowed ordering physicians to capture profits from diagnostic volume in ways that resembled the very self-referral risks Stark was intended to mitigate, while exploiting reassignment and purchased test rules that were never designed for this degree of vertical integration.
At the heart of the rulemaking is CMS’s reframing of a deceptively simple question: who actually furnishes a diagnostic service for Medicare purposes? Historically, Medicare had been willing to deem a service “furnished” by a billing physician or group even when the work was done by others, provided certain safeguards were met. By 2007, CMS concluded that this legal fiction had been stretched too far. The agency began to focus less on formal labels—employee versus contractor, purchase versus reassignment—and more on functional realities: who ordered the test, where the work was performed, and whether the billing entity stood to profit from volume it controlled.
This shift is most visible in CMS’s treatment of “office” versus “centralized building.” For Stark purposes, a centralized building could qualify as an in-office ancillary location even if no patient care occurred there. CMS accepted that premise under Stark but refused to import it wholesale into payment policy. In the anti-markup context, CMS deliberately narrowed the concept of an “office” to mean a place where the physician or group regularly furnishes patient care. Space leased exclusively for laboratory operations—even if compliant with Stark—did not qualify. This distinction effectively severed the link between Stark compliance and payment privilege, and it did so without amending Stark itself.
The extension of anti-markup limits to the professional component of diagnostic tests was the most controversial aspect of the rule. Commenters argued that Congress had explicitly addressed only the technical component in section 1842(n) of the Social Security Act, and that physician services were governed by section 1848’s fee schedule rules. CMS’s response was telling. Rather than claiming explicit congressional instruction, CMS emphasized discretion. Reassignment and purchased test billing were framed as options that CMS could condition in the interest of program integrity. Physicians remained free to bill directly for services they personally performed. If they chose instead to bill for services furnished by others, CMS asserted authority to limit the resulting payment to prevent markup-driven incentives.
Employment status received similar treatment. CMS rejected arguments that full-time employees should be treated differently from part-time employees or independent contractors. From the agency’s perspective, these distinctions were formalities that obscured the economic substance of the arrangement. If the work was performed outside the billing entity’s office, or if it was purchased outright, anti-markup applied. This insistence on neutrality across employment models signaled CMS’s broader intent to avoid regulatory gamesmanship and to focus on incentive alignment rather than contractual nuance.
The rulemaking record is also notable for CMS’s candor about overutilization. CMS acknowledged that it was difficult to determine, case by case, whether increased biopsy volume or diagnostic intensity resulted from profit incentives or evolving standards of care. Yet the agency declined to resolve that clinical debate. Instead, it relied on decades of OIG, GAO, and policy research showing that, in aggregate, self-referral correlates with increased utilization. CMS’s conclusion was pragmatic: when financial incentives and ordering authority align, the risk of overuse increases, even if individual practitioners believe their decisions are clinically justified.
Quality arguments received extensive attention but little regulatory traction. Commenters described improved turnaround times, closer collaboration between clinicians and pathologists, and enhanced subspecialization under pod lab arrangements. CMS did not deny that such benefits could exist. What it refused to do was build payment policy around self-reported quality advantages tied to ownership or profit structures. The agency consistently returned to the principle that Medicare payment rules must be administrable, neutral across specialties, and resistant to incentive-driven distortions. Quality oversight, in CMS’s view, belonged elsewhere—in accreditation, CLIA enforcement, and professional standards—not in exceptions to anti-markup safeguards.
Equally revealing are the actions CMS chose not to take. The agency did not abolish the in-office ancillary services exception, did not prohibit pod labs outright, and did not dictate clinical protocols for biopsies or diagnostic intensity. Instead, it used payment policy as a moderating force. Practices could continue to structure their operations as they wished, but if they sought to bill Medicare for services furnished outside their true clinical offices, they would be limited to cost-based reimbursement rather than profit-generating markups.
Seen in retrospect, the 2007–2008 rulemaking foreshadowed much of CMS’s later regulatory posture. It reflects an enduring preference for economic guardrails over categorical bans, for functional analysis over formal compliance, and for payment policy as a lever to shape behavior without criminalizing innovation. For readers interested in how CMS actually governs complex clinical markets, this episode stands as a textbook example of administrative pragmatism—careful, contested, and quietly consequential.
###
These advisory documents covered in office ancillary services. There is a great deal of discussion of what in office means. Such as same building, etc. Is there any discussion of what ancillary services means and whether that definition should be revised? I don’t think there would be, but I don’t know.
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Short answer first, then the explanation: no, these documents do not meaningfully revisit or redefine what “ancillary services” means, and that omission is deliberate and revealing. The discussion is overwhelmingly about where services are furnished (“in-office,” “same building,” “centralized building”) and how they are billed, not about what kinds of services qualify as ancillary in the first place
2007 CMS 1127 72FR66222 Physici…
.
What follows is the longer, historically grounded explanation.
Across the 2007–2008 rulemaking, CMS devotes enormous analytic energy to the phrase “in-office” and almost none to “ancillary services.” This asymmetry is not accidental. CMS treats the scope of “ancillary services” as essentially settled law, while treating the geography and economics of furnishing those services as the locus of emerging abuse.
The statutory foundation matters here. The in-office ancillary services exception in Stark is defined in section 1877(b)(2) of the Social Security Act, and it lists categories of services—clinical laboratory services, radiology, certain diagnostic tests, and related items—that Congress explicitly designated as “ancillary.” By the time CMS reached the mid-2000s, this list had been in place for years and had already survived multiple rounds of litigation, OIG interpretation, and rulemaking. Reopening the definition of “ancillary” would have meant questioning Congress’s own policy judgment that certain diagnostic services are sufficiently integral to physician practice to warrant special treatment.
CMS clearly did not want to do that.
Instead, CMS’s concern in the CY 2008 rulemaking is that services unquestionably covered by the ancillary exception were being furnished in ways that no longer looked ancillary in any meaningful sense. The services themselves—pathology interpretations, histology processing, imaging reads—were not in dispute. What troubled CMS was that they were being carved out into quasi-independent production units, geographically and operationally detached from the physician’s clinical office, while still benefiting from the financial privileges of in-office status.
That explains why the rulemaking is saturated with discussion of “same building,” “centralized building,” and “office of the billing physician or supplier,” yet contains virtually no debate about whether pathology or imaging should be considered ancillary at all. CMS repeatedly signals that the problem is not what services are ancillary, but how far practices have stretched the concept of being “in-office” to preserve the economic advantages attached to that designation.
Importantly, CMS also draws a careful jurisdictional boundary. In multiple places, the agency notes that it merely solicited comments on the scope and application of the IOAS exception but did not propose regulatory text revising the exception itself. As CMS states explicitly, any revision to the in-office ancillary services exception would require a future notice of proposed rulemaking, not a payment-rule add-on. This reflects both administrative caution and legal realism: redefining “ancillary services” would almost certainly provoke intense political opposition and statutory interpretation challenges.
What CMS does instead is far more subtle. Without touching the definition of ancillary services, it decouples Stark compliance from payment entitlement. A service can still qualify as an in-office ancillary service for Stark purposes, yet be subject to anti-markup limits for Medicare payment because it is not performed in the “office of the billing physician or supplier” as CMS defines that term for payment integrity purposes. In other words, CMS leaves the what alone and constrains the benefit.
This approach also avoids a doctrinal trap. If CMS had attempted to narrow the definition of ancillary services, it would have been forced to articulate why certain diagnostic services are no longer “ancillary” to physician practice—a concept that becomes increasingly unstable as medicine grows more specialized and technology-driven. By contrast, focusing on location, ordering authority, and billing structure allows CMS to address abuse without redefining clinical relationships.
So your instinct is correct: there is essentially no effort in these documents to rethink or revise the meaning of “ancillary services.” The silence is itself a policy choice. CMS treats the ancillary-services list as a settled statutory compromise and directs its regulatory energy toward preventing that compromise from being exploited through aggressive interpretations of “in-office.”
Seen this way, the rulemaking is not about narrowing what physicians are allowed to do; it is about narrowing what Medicare is willing to pay a profit margin for when services drift too far from the clinical office that justified their ancillary status in the first place.
###
Could these discussions accomplish very much without actual changes to actual regulations? Isn’t everything else just dicta?
###
This is an excellent and very lawyerly question, and the short answer is: yes, without regulatory text changes much of this is dicta—but not meaningless dicta. In CMS world, there is a crucial middle ground between “binding regulation” and “mere commentary,” and this rulemaking sits squarely in it.
Let me unpack that carefully.
At a formal level, you are absolutely right. Only changes to the Code of Federal Regulations are legally binding rules of general applicability. Preamble discussion, examples, policy explanations, and responses to comments do not, by themselves, amend Stark, redefine IOAS, or prohibit conduct. If CMS had done only narrative discussion without changing §414.50, §424.80, or related definitions, the entire exercise would largely have been interpretive commentary.
But that is not what happened.
What CMS did here is more subtle and more powerful than pure dicta.
First, CMS did make concrete regulatory changes, but they were targeted at payment rather than permission. The revisions to §414.50 (anti-markup), the cross-reference in §424.80, and the revised understanding of what counts as the “office of the billing physician or supplier” are real regulatory hooks. They directly affect what Medicare will pay, and under what circumstances. Once payment is constrained, behavior follows, even if the underlying Stark exception technically remains intact.
Second, the preamble discussion is not free-floating. It is doing heavy interpretive work in service of those regulatory changes. Courts, auditors, ALJs, DOJ, and CMS contractors routinely treat such preamble language as authoritative evidence of agency intent, especially where the regulatory text uses open-ended or functional terms like “office,” “performed,” or “ordered.” In other words, this is not dicta in the way a law review aside is dicta; it is interpretive guidance tethered to enacted regulatory text.
Third—and this is key—CMS is explicitly laying groundwork for future enforcement and future rulemaking. When CMS says, repeatedly, that centralized buildings may satisfy Stark but do not necessarily qualify as offices for payment purposes, it is creating a record. That record matters later when CMS, an OIG auditor, or DOJ argues that a particular arrangement was aggressive, abusive, or knowingly exploitative. The regulated party cannot plausibly say, “we had no notice that CMS viewed this as problematic,” even if the conduct was not per se prohibited.
Fourth, CMS is operating within a regulatory ecosystem where payment denial is often more consequential than formal illegality. Medicare does not need to declare an arrangement unlawful to make it economically nonviable. By limiting billing to the lowest of cost, charge, or fee schedule when services are performed outside the “real” office, CMS effectively neutralizes the profit motive that made pod labs attractive. That accomplishes most of the policy goal without rewriting Stark.
Fifth, CMS is consciously avoiding overreach. Redefining “ancillary services” or rewriting the IOAS exception would have been a frontal assault on statutory language and decades of reliance interests. That would have invited litigation and congressional backlash. By contrast, adjusting payment rules while leaving the statutory exception untouched is administratively defensible and politically survivable. The preamble discussion explains and justifies that strategy, which makes it harder to challenge later as arbitrary.
So is much of the discussion technically dicta? Yes, in the narrow sense that it does not itself change the law.
But is it inert? No.
It functions as:
authoritative interpretation of ambiguous regulatory terms,
notice to the regulated community,
guidance to auditors and enforcement staff,
justification for payment denials,
and a predicate for later rulemaking.
In CMS policy history, this is actually a classic move. CMS often governs by narrowing the economic benefit of compliance rather than the formal scope of permission, and it uses preamble discussion to explain how it will exercise that discretion.
So your instinct is right, but the conclusion is slightly more nuanced:
without regulatory changes, discussion would be mere commentary—but here, the discussion is tightly coupled to payment rules that do change, and that makes it consequential in practice even if Stark itself remains textually untouched.
###
Yes — and you are exactly right to focus on that phrase “or more”, because it quietly does an enormous amount of policy work. What you are pointing to is not an aside to the pod-lab story but one of its most effective enforcement mechanisms, even though it sits in a different part of the payment universe.
What CMS did with prostate biopsy pathology is a classic example of convergent policy control: one lever aimed at who may profit from pathology (anti-markup), and another aimed at how much volume can ever be monetized, regardless of who bills.
For years before 2007–2008, prostate biopsy pathology had a built-in volume escalator. The CPT structure allowed separate payment for each core, and as biopsy protocols evolved from sextant sampling to 10, 12, or more cores, payment rose linearly. From CMS’s perspective, this created a perverse alignment: expanding clinical protocols translated directly into expanding revenue, with no natural brake. Even if the increase in cores was clinically defensible in some cases, the payment system itself had no way to distinguish clinical evolution from financial opportunism.
CMS’s response was not to challenge the medical science head-on. Instead, it imposed a payment ceiling. Once the number of cores reached a defined threshold — commonly remembered as “10 or more” — additional cores ceased to generate additional Medicare payment. The brilliance of the approach lies in its bluntness. CMS did not say “10 is appropriate” or “12 is excessive.” It said, in effect: whatever number you choose clinically, Medicare will not pay more once you cross this line.
That “or more” language is doing the real work. It collapses all higher volumes into a single reimbursement category. Whether a practice submits 10 cores or 18, the marginal revenue beyond the cap is zero. The incentive to keep adding cores for payment reasons evaporates, even though the physician’s clinical discretion remains intact.
When you place this alongside the anti-markup rules discussed earlier, a coherent policy strategy emerges. CMS never needed to prove that pod labs caused overutilization in every case. Instead, it removed the economic fuel that made rising biopsy counts and vertically integrated pathology attractive. The prostate biopsy cap ensures that even if a urology group controls pathology billing, there is no financial upside to chasing ever-larger specimen counts. The anti-markup rules ensure that, if the work is done outside the true clinical office, the group cannot layer profit on top of someone else’s labor.
Importantly, this payment cap operates independently of Stark and IOAS. It does not matter whether the pathology is technically “in-office,” performed in a centralized building, or sent to an independent lab. The cap applies universally. That universality is what gives it legitimacy and durability. CMS avoided specialty-specific prohibitions while still targeting a specialty-specific incentive structure.
This also explains why CMS could afford to leave much of the IOAS debate in narrative form. When payment is capped and markup is constrained, formal compliance becomes far less valuable. A pod lab that once generated growing margins from 12-core, 14-core, or 18-core biopsies suddenly looks much less compelling when reimbursement flattens at “10 or more” and any off-site work is reimbursed at cost. The arrangement may still exist, but its economic rationale is largely neutralized.
In retrospect, this was a more effective intervention than rewriting Stark would have been. Redefining “ancillary services” or narrowing IOAS would have triggered legal challenges and political backlash. By contrast, capping prostate biopsy pathology payment and tightening anti-markup rules allowed CMS to discipline behavior without accusing anyone of wrongdoing. Practices could continue to argue about quality, turnaround time, and collaboration — but the payment system would no longer reward unbounded growth.
So yes: urology, prostate cancer, and biopsy pathology were central to this era, and the payment cap is inseparable from the pod-lab story. It is a reminder that in Medicare policy, the most consequential reforms often arrive not as headline prohibitions, but as small phrases in payment rules — phrases like “or more” that quietly redraw the economic map.
TOP: Rulemaking in Federal Register 72 FR 66222 (circa 66306-21) November 2007.
BOTTOM: Journalistic summaries, most 2004-5.
###
Below is the same substance recast as a continuous essay, with no bullets and a more narrative, analytic flow.
The 2007–2008 CMS rulemaking embedded in the CY 2008 Physician Fee Schedule final rule occupies a peculiar and revealing place in Medicare policy history. On its face, it is a technical exercise in billing rules—anti-markup provisions, reassignment mechanics, and definitional clean-ups. In reality, it represents one of CMS’s clearest attempts to reassert control over the economic logic of diagnostic testing without banning practices outright or rewriting the Stark statute.
For readers fascinated by how CMS actually governs, this episode repays close attention.
By the mid-2000s, CMS had come to believe that it was confronting not a handful of bad actors, but a structural misalignment that had emerged organically from well-intentioned statutory and regulatory changes. Stark law prohibited physician self-referral, yet preserved the in-office ancillary services exception to avoid crippling integrated practice.
The Medicare Modernization Act of 2003 liberalized reassignment rules, allowing billing entities to aggregate and bill for services furnished by others under contract. Separately, Medicare had long permitted billing for purchased diagnostic tests, constrained by anti-markup limits designed to prevent pure arbitrage. Each of these rules made sense on its own. Together, however, they created a permissive environment in which physician groups could order, control, and profit from diagnostic services that were increasingly detached from the clinical office itself.
CMS’s concern was not that these arrangements were facially illegal. In fact, many of the “pod lab” models that drew attention during this period were carefully structured to satisfy Stark’s technical requirements, including the centralized building definition. The problem, as CMS framed it, was that these arrangements undermined the original policy balance. They allowed ordering physicians to capture profits from diagnostic volume in ways that resembled the very self-referral risks Stark was intended to mitigate, while exploiting reassignment and purchased test rules that were never designed for this degree of vertical integration.
At the heart of the rulemaking is CMS’s reframing of a deceptively simple question: who actually furnishes a diagnostic service for Medicare purposes? Historically, Medicare had been willing to deem a service “furnished” by a billing physician or group even when the work was done by others, provided certain safeguards were met. By 2007, CMS concluded that this legal fiction had been stretched too far. The agency began to focus less on formal labels—employee versus contractor, purchase versus reassignment—and more on functional realities: who ordered the test, where the work was performed, and whether the billing entity stood to profit from volume it controlled.
This shift is most visible in CMS’s treatment of “office” versus “centralized building.” For Stark purposes, a centralized building could qualify as an in-office ancillary location even if no patient care occurred there. CMS accepted that premise under Stark but refused to import it wholesale into payment policy. In the anti-markup context, CMS deliberately narrowed the concept of an “office” to mean a place where the physician or group regularly furnishes patient care. Space leased exclusively for laboratory operations—even if compliant with Stark—did not qualify. This distinction effectively severed the link between Stark compliance and payment privilege, and it did so without amending Stark itself.
The extension of anti-markup limits to the professional component of diagnostic tests was the most controversial aspect of the rule. Commenters argued that Congress had explicitly addressed only the technical component in section 1842(n) of the Social Security Act, and that physician services were governed by section 1848’s fee schedule rules. CMS’s response was telling. Rather than claiming explicit congressional instruction, CMS emphasized discretion. Reassignment and purchased test billing were framed as options that CMS could condition in the interest of program integrity. Physicians remained free to bill directly for services they personally performed. If they chose instead to bill for services furnished by others, CMS asserted authority to limit the resulting payment to prevent markup-driven incentives.
Employment status received similar treatment. CMS rejected arguments that full-time employees should be treated differently from part-time employees or independent contractors. From the agency’s perspective, these distinctions were formalities that obscured the economic substance of the arrangement. If the work was performed outside the billing entity’s office, or if it was purchased outright, anti-markup applied. This insistence on neutrality across employment models signaled CMS’s broader intent to avoid regulatory gamesmanship and to focus on incentive alignment rather than contractual nuance.
The rulemaking record is also notable for CMS’s candor about overutilization. CMS acknowledged that it was difficult to determine, case by case, whether increased biopsy volume or diagnostic intensity resulted from profit incentives or evolving standards of care. Yet the agency declined to resolve that clinical debate. Instead, it relied on decades of OIG, GAO, and policy research showing that, in aggregate, self-referral correlates with increased utilization. CMS’s conclusion was pragmatic: when financial incentives and ordering authority align, the risk of overuse increases, even if individual practitioners believe their decisions are clinically justified.
Quality arguments received extensive attention but little regulatory traction. Commenters described improved turnaround times, closer collaboration between clinicians and pathologists, and enhanced subspecialization under pod lab arrangements. CMS did not deny that such benefits could exist. What it refused to do was build payment policy around self-reported quality advantages tied to ownership or profit structures. The agency consistently returned to the principle that Medicare payment rules must be administrable, neutral across specialties, and resistant to incentive-driven distortions. Quality oversight, in CMS’s view, belonged elsewhere—in accreditation, CLIA enforcement, and professional standards—not in exceptions to anti-markup safeguards.
Equally revealing are the actions CMS chose not to take. The agency did not abolish the in-office ancillary services exception, did not prohibit pod labs outright, and did not dictate clinical protocols for biopsies or diagnostic intensity. Instead, it used payment policy as a moderating force. Practices could continue to structure their operations as they wished, but if they sought to bill Medicare for services furnished outside their true clinical offices, they would be limited to cost-based reimbursement rather than profit-generating markups.
[I believe CMS also rewrote and capped coding & reimbursement for prostate biopsy.]
Seen in retrospect, the 2007–2008 rulemaking foreshadowed much of CMS’s later regulatory posture. It reflects an enduring preference for economic guardrails over categorical bans, for functional analysis over formal compliance, and for payment policy as a lever to shape behavior without criminalizing innovation. For readers interested in how CMS actually governs complex clinical markets, this episode stands as a textbook example of administrative pragmatism—careful, contested, and quietly consequential.
“Pod labs” (also called anatomic pathology condominium laboratories or “salon labs”) were a distinctive early-2000s business model in which specialist physician groups—especially urology and gastroenterology—attempted to bring anatomic pathology “in-house” without actually building and staffing a traditional pathology laboratory within their own offices. Instead, physician groups owned small, discrete lab “units” inside larger shared facilities operated by management companies, while the physician group billed for pathology services and paid for technical and professional inputs under contractual arrangements.
At their core, pod labs were an effort to thread the needle of Stark Law, the Anti-Kickback Statute, and Medicare’s anti-markup rules by fitting pathology into the in-office ancillary services (IOAS) exception. IOAS is a well-established and legitimate concept: it allows a physician—such as a cardiologist—to refer patients to ancillary services furnished within the physician’s own practice, like an in-office echocardiography or ultrasound suite staffed by practice employees. Pod labs sought to claim the same protection for anatomic pathology.
The structure was simple but carefully engineered. A developer or operator would establish a building divided into multiple small lab “condos,” each owned by a different physician group, much like residential condominium ownership. Each condo was presented as the physician group’s “in-office” laboratory for IOAS purposes.
Because no single group necessarily had enough volume to justify full-time staffing, the operator arranged shared or rotating histotechnologists and pathologists, who moved from unit to unit as needed. In practice, this sometimes manifested as a hallway of doors, each labeled with the name of a different urology group, while the same technician or pathologist walked room-to-room performing work. From a paperwork standpoint, each room was a separate physician-owned lab; operationally, it functioned as a single shared facility.
Critically, the physician group—not the lab operator—submitted claims, collected reimbursement, and then paid the laboratory staff and pathologists. This billing posture was central to fitting within IOAS and avoiding anti-markup and anti-kickback prohibitions.
The legal theory behind pod labs was straightforward: if a physician group could claim ownership of the lab space and characterize the testing as occurring “within the practice,” then referrals to that lab would fall under the IOAS exception, even if pathology had historically been referred to independent laboratories.
But this theory quickly strained credibility. Many pod labs were physically remote from the physician’s actual clinical offices, sometimes located miles away or even in different states. Specimens were shipped across state lines, processed in these shared facilities, and billed as if the testing occurred inside the referring practice. The contrast between the classic IOAS model—a cardiologist walking a patient down the hall to an ultrasound suite staffed by the practice—and a distant pathology condo lab staffed by itinerant personnel was hard to ignore.
Pod labs emerged first among entrepreneurial urologists, with Florida and Texas becoming early centers of activity. Specialized companies formed to promote the model nationally, offering turnkey development, staffing, and compliance narratives to urology and GI practices interested in capturing anatomic pathology revenue.
By the early 2000s, pod labs were being marketed explicitly as a way to reclaim revenue lost to independent pathology laboratories while remaining technically compliant with Stark and anti-kickback rules through IOAS structuring.
The rise of pod labs coincided with significant Medicare reimbursement reductions for procedural specialties, particularly urology. These cuts intensified the search for ancillary revenue streams. Anatomic pathology—predictable, high-volume, and well reimbursed—became an obvious target.
This economic origin story mattered. The more clearly pod labs were framed as revenue-replacement vehicles rather than patient-care innovations, the harder it became to sustain a credible clinical justification.
Journalists and observers repeatedly noted unusual secrecy surrounding pod lab operations. Organizers avoided publicity, and site visits revealed arrangements that felt more like regulatory constructs than organic medical practices: long corridors of locked doors, each representing a nominally separate physician practice, staffed by the same personnel moving between them.
Even contemporaneous observers captured the core problem succinctly: these arrangements appeared designed to satisfy the formal elements of IOAS while recreating exactly the self-referral incentives Stark was meant to prevent.
Pod labs were never outlawed by a single bright-line rule. Instead, regulatory pressure accumulated gradually. CMS, the Office of Inspector General, and enforcement agencies increasingly treated pod labs as abusive contractual joint ventures, especially when they relied on expansive interpretations of “in-office” that bore little resemblance to ordinary practice operations.
The decisive blow came through Medicare payment policy, particularly the anti-markup rules implemented in 2008, which sharply limited the ability of physician groups to profit from purchased pathology services. Once the markup opportunity disappeared, the economic rationale for pod labs weakened dramatically. Litigation failed to reverse these changes, and prominent pod lab operators were eventually sold or exited the market.
Pod labs collapsed not because ownership or in-house testing is inherently suspect, but because formal compliance did not rescue arrangements whose underlying purpose was revenue capture. The IOAS exception was designed to allow efficient, patient-centered ancillary care—not to serve as a vehicle for industrialized internalization of downstream diagnostics.
This distinction remains central today. Pathologists have long been permitted to order additional tests as part of completing a case because those decisions are bounded by professional norms and clinical necessity. When diagnostic workflows expand—whether into molecular testing or genomics—the pod lab history reminds regulators and providers alike that permission does not end the analysis. Substance, governance, and restraint ultimately determine whether an arrangement withstands scrutiny.
SIDEBAR to a broader article.
Multi-channel automated analyzers began to enter routine clinical laboratory use in the late 1970s and early 1980s, but they became truly widespread during the mid-to-late 1980s and early 1990s. This was the period when hospital and reference laboratories transitioned from largely manual or single-analyte chemistry testing to high-throughput platforms capable of measuring many analytes simultaneously from a single specimen. By the time OIG issued its guidance in 1997 and 1998, these analyzers were no longer experimental curiosities—they were the backbone of routine clinical chemistry.
The key innovation was not simply speed, but parallelization. Earlier analyzers performed one test at a time. Multi-channel analyzers, by contrast, were designed to run multiple assays together because it was operationally easier, cheaper, and analytically cleaner to do so. Once serum was loaded and the instrument calibrated, adding additional analytes often required little incremental effort. This technological reality collided directly with a reimbursement system that still conceptualized testing as a series of individually ordered services.
Out of this collision emerged the chemistry panels that are now so familiar they barely register as “panels” at all. The Basic Metabolic Panel (BMP)—typically including sodium, potassium, chloride, bicarbonate, BUN, creatinine, glucose, and sometimes calcium—reflects a core set of electrolytes and renal markers that were commonly run together on early automated systems. The Comprehensive Metabolic Panel (CMP) expanded this set to include liver-associated analytes such as AST, ALT, alkaline phosphatase, bilirubin, albumin, and total protein, yielding the familiar 14-analyte version used today. Variants with 20 or 21 analytes emerged historically as laboratories added calcium, phosphorus, or other markers depending on platform design and clinical convention.
What is often forgotten is that these panels were not originally “bundles” in a conceptual sense. They were engineering artifacts—groupings that made sense given how the machines worked. Physicians quickly adapted their ordering habits to these groupings because they were clinically useful and readily available. Over time, CPT coding and Medicare policy caught up, formalizing what had started as a technological convenience into standardized billable panels.
By the mid-1990s, however, policymakers faced a new question: what happens when technology makes it easier to run more tests than are clinically necessary for a given patient? OIG’s answer, reflected in the 1997 and 1998 guidance, was not to resist the technology, but to regulate the billing behavior around it. Laboratories could run broad panels if that was how their analyzers worked—but they could not bill indiscriminately.
Seen in this light, modern molecular panels are not a radical departure from historical practice. They are the genomic descendants of the chemistry analyzer. Just as it once made sense to run electrolytes and liver enzymes together, it may now make sense to sequence genes A, B, and C together. The regulatory question has remained strikingly stable for forty years: what matters is not what the machine runs, but what the laboratory reports and bills as medically necessary for each patient.
That continuity is precisely why the 1997–1998 OIG guidance still resonates today.
SIDEBAR to a broader article.
[AI generated text]
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When the Office of Inspector General issued its clinical laboratory compliance guidance in 1997 and then again in 1998, it was responding to a technology shift that now feels quaint but was genuinely disruptive at the time: the widespread adoption of automated, multi-channel analyzers. These platforms could run many chemistry tests simultaneously, often more efficiently than running a single analyte alone. The policy problem was immediate and practical. Medicare payment rules were built around individually ordered tests, but laboratory technology was increasingly optimized around bundled or parallel testing.
OIG recognized that it could not regulate laboratories by pretending this technology did not exist. Instead, the agency focused on what it viewed as the real compliance risk: billing and utilization behavior, not the internal mechanics of the analyzer. Across both guidances, OIG made clear that laboratories were not prohibited from running multiple tests together, even when only a subset was ordered for a particular patient. What mattered was that only those tests that were ordered, medically necessary, performed, and reported were billed to Medicare
This principle runs throughout both documents. OIG repeatedly emphasized that laboratories do not practice medicine and do not decide medical necessity, but they are nonetheless responsible for ensuring that claims submitted to Medicare reflect only services that meet Medicare’s coverage standards. Laboratories were expected to design requisitions, billing systems, and utilization monitoring processes that discouraged overordering and prevented the automatic billing of unnecessary test components. Running a “superset” of tests was not itself problematic; billing indiscriminately for that superset was.
Seen from today’s vantage point, this guidance maps cleanly onto modern molecular workflows. A laboratory may find it efficient to run genes A, B, and C together because they are ordered together most of the time. The OIG’s position—then and now—is not that this efficiency must be undone, but that the laboratory must ensure that gene B or C is not reported or billed when it is not ordered or medically necessary. That is the core continuity between the era of chemistry analyzers and the era of sequencing panels.
Taken together, the 1997 and 1998 guidance articulate a unified regulatory stance. First, physicians may order any tests they believe are appropriate, but Medicare will only pay for tests that are covered, reasonable, and necessary. Second, laboratories are expected to structure their operations to support conscious ordering, not passive or default overutilization. Third, laboratories must have internal controls—requisition design, notices to physicians, utilization monitoring, and billing safeguards—to prevent automated technology from driving inappropriate claims. And fourth, OIG made explicit that laboratories could face False Claims Act or kickback exposure if their pricing, marketing, or billing practices encouraged unnecessary testing
Importantly, neither document treats automation as inherently suspect. The tone is pragmatic, even permissive. OIG’s concern is not how many assays an analyzer can run, but whether the laboratory’s business practices undermine Medicare’s medical-necessity framework.
The 1997 guidance is best understood as a first-generation response to automated testing. It is closely focused on multichannel chemistry panels, CPT-defined profiles, and requisition design. OIG spends considerable time on the mechanics of ordering—encouraging laboratories to design requisitions that force physicians to actively select tests, document diagnoses, and understand the billing consequences of profiles and customized panels. The document also introduces detailed recommendations around physician notices, acknowledgments for customized profiles, and internal monitoring of utilization growth, including the now-famous suggestion to investigate test volume increases exceeding 10 percent year over year
In short, the 1997 guidance is granular and operational. It reads as OIG’s attempt to translate a new technological reality into concrete compliance behaviors for laboratories that were still learning how automation intersected with Medicare rules.
The 1998 guidance does not reverse the 1997 conclusions; instead, it refines and institutionalizes them. By 1998, OIG had issued compliance program guidance for hospitals and home health agencies, and it sought to align laboratory guidance with a broader, cross-industry compliance framework. The 1998 document is therefore more explicitly structured around the seven elements of an effective compliance program, drawing on the Federal Sentencing Guidelines and corporate integrity agreement experience.
Substantively, the 1998 guidance updates the discussion to reflect policy changes, including the elimination of certain multichannel chemistry billing codes from CPT, and it places greater emphasis on standing orders, reflex testing, and confirmation testing. OIG is more explicit about discouraging standing orders as a default practice and stresses that even where standing orders exist, laboratories must periodically revalidate their medical necessity
The tone is less about teaching laboratories how automation works and more about embedding laboratory billing into a mature compliance culture.
Read together, the 1997 and 1998 OIG guidances show an agency grappling—deliberately and incrementally—with the consequences of automation. They do not prohibit efficient testing platforms. They do not require laboratories to cripple their workflows. Instead, they insist on a separation between what technology can do and what Medicare will pay for. That distinction remains foundational today, whether the platform in question is a chemistry analyzer, a sequencing pipeline, or a digital diagnostic workflow.
Understanding this history helps explain why modern debates about molecular panels and reflex testing feel familiar to regulators. The questions are old. Only the machines have changed.
Myriad and PathomIQ;
An Entry Point to Potentially Disastrous AMA CPT Changes
The evolution of the Myriad–PATHOMIQ relationship offers a compact case study in how cutting-edge computational pathology is colliding with a reimbursement and coding system that was never designed to recognize information extraction as a medical service. At its scientific core, PATHOMIQ represents a disciplined and unusually mature attempt to answer a legitimate clinical question: whether routinely generated histopathology images—H&E slides that already exist in every prostate cancer case—contain latent, reproducible signals that can predict recurrence, metastasis, or treatment response. From a research standpoint, the answer increasingly appears to be yes. From a business standpoint, however, the answer has become far more ambiguous, not because the science failed, but because the payment architecture has no place to put it.
PATHOMIQ’s early development reflects a rare alignment of translational oncology, pathology, molecular biology, and enterprise AI. The company did not emerge from a single academic lab nor from a purely technical AI incubator; it was constructed at the intersection of both. Its founders include senior academic pathologists and oncologists with access to long-follow-up tissue cohorts and clinically meaningful endpoints, paired with a CEO whose background signals commercial intent from the outset. That combination shaped PATHOMIQ into what might be called a “model-as-asset” company: not a workflow vendor, not a CLIA service lab, but a generator of validated prognostic models intended to be licensed into larger diagnostic ecosystems. Scientifically, this strategy made sense. Commercially, it assumed that once clinical validity was established, a payment pathway would eventually follow. That assumption is now proving increasingly fragile.
The Myriad licensing deal in early 2025 initially appeared to confirm the viability of this approach. Myriad’s first descriptions of the collaboration framed PATHOMIQ_PRAD as a distinct, AI-driven prostate cancer test—fast, image-based, independent, and in some cohorts outperforming traditional markers. The language suggested optionality: PATHOMIQ could stand beside genomic tests like Prolaris, offering orthogonal insight derived from morphology rather than RNA expression. This framing implicitly tested a bold proposition: that algorithmic interpretation of existing clinical data might itself be treated as a billable diagnostic service. In early 2025, Myriad sounded as though it was prepared to see whether the market—and perhaps the CPT system—might accept that proposition.
By late 2025, that tone had changed markedly. Myriad’s public communications no longer described PATHOMIQ as a standalone test but as an embedded analytic layer inside Prolaris. AI was reframed as an “amplifier,” not an answer; as an enhancement, not a replacement; as supportive of clinician judgment rather than an independent decision tool. This rhetorical pivot was not subtle to those who understand reimbursement mechanics. It reflects a recognition that the standalone “upload DICOM, download report” business model—however elegant scientifically—is structurally homeless in the current CPT ecosystem. What began as a potential new diagnostic modality was quietly absorbed into an already covered one.
This shift exposes the deeper problem: computational pathology sits at the intersection of two Venn diagrams that no longer overlap. On one side is science and product development. PATHOMIQ and similar companies are extracting clinically relevant information from data that medicine already collects, at marginal cost and with increasing rigor. They are not inventing new biomarkers in the classical sense; they are revealing structure in existing data. On the other side is the CPT framework, which remains stubbornly biomarker-centric. PLA codes reward the creation of new analytes. Category I codes reward established professional services. MAAA codes reward multianalyte laboratory tests. None of these categories recognize information itself as the billable output when no new wet-lab signal is produced.
The result is a slow-motion train wreck. Computational pathology tests that do not create new molecules are systematically excluded from PLA eligibility. They are incompatible with Category I because they are proprietary, versioned, and algorithmic, and because CPT resists paying twice for “interpretation” of the same specimen. MAAA is explicitly unavailable because images are not analytes. Category III offers, at best, a tracking code with little prospect of payment. CMAA—if it emerges as currently envisioned—risks becoming a registry for AI tools rather than a reimbursement pathway, a kind of Appendix S for algorithms: visible, cataloged, and unpaid.
What makes this particularly reckless from a policy standpoint is that the CPT system is not merely failing to keep up with innovation; it is actively shaping commercial behavior in ways that suppress it. Myriad’s absorption of PATHOMIQ into Prolaris is rational and probably unavoidable, but it is also telling. The AI does not disappear because it lacks value; it disappears because it cannot survive on its own economically. The cost of innovation is shifted from revenue line to internal expense. The signal is preserved, but the incentive to build similar standalone tools is weakened. Smaller companies without a Myriad-scale partner are left with no viable path at all.
The danger here is not that CPT is conservative—that has always been true—but that it is enforcing an outdated ontology of diagnostics at precisely the moment medicine is becoming information-centric. Computational pathology challenges the assumption that value arises only when a new biomolecule is measured. It argues instead that value can arise when existing data are interpreted more deeply. By rejecting that premise and diverting these services into non-payable categories, the AMA risks creating a perverse outcome: encouraging molecular redundancy while discouraging informational efficiency.
Seen in this light, the Myriad–PATHOMIQ story is less about one partnership than about a systemic mismatch. The science is converging on morphology-derived insight as a legitimate predictor of outcome. The business models are converging on licensing and integration as survival strategies. Meanwhile, CPT is converging on exclusion—pushing these technologies out of PLA, away from Category I, and into administrative limbo. If this trajectory continues, the U.S. risks building a diagnostics ecosystem that pays generously for new molecules while quietly strangling tools that extract more value from what we already have. That is not just a coding problem; it is a policy failure with long-term consequences for how innovation in pathology is financed, scaled, and ultimately delivered to patients.
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Below is a single, continuous essay-style report, written independently and analytically, designed to give you language, framing, and “color” you can mine for a white paper that is openly critical of AMA CPT policy direction. I am deliberately not footnoting or citing documents; this is an interpretive synthesis, not a compliance memo.
ESSAY PART TWO: WHERE IS AMA TAKING US?
The current AMA CPT posture toward artificial intelligence is not malicious, but it is conceptually misaligned with where large parts of diagnostic medicine are actually headed. The principles now being articulated—particularly the resistance to autonomous AI services, the insistence on physician mediation, and the fear of RVU dilution—make internal sense in the world of adjunctive AI in radiology, but they break down badly when applied to computational pathology and genomics, where AI is not advisory, not suggestive, and not subordinate to human interpretation. In those domains, AI is the test.
Radiology AI, which appears to be the tacit reference model for many CPT deliberations, is structurally different. Most radiology AI tools flag regions of interest, highlight subtle findings, prioritize worklists, or suggest second looks. They operate as overlays on a physician’s interpretive act. The radiologist remains the locus of judgment, liability, and narrative authority. From a CPT perspective, it is therefore natural—almost inevitable—to treat these tools as adjunctive, non-billable, or bundled services. They enhance physician work; they do not replace it. In that context, concerns about double payment, RVU inflation, and erosion of physician control are at least internally coherent.
Computational pathology and genomics do not fit that model at all. In these fields, the “result” is not a suggestion to a physician; it is a probabilistic or categorical determination derived from data at a scale no human can meaningfully process. When a genomic assay analyzes hundreds of millions or billions of DNA fragments and reports a pathogenic mutation linked to an FDA-approved therapy, there is no meaningful point at which a pathologist’s opinion is injected into the result. The interpretive act has already occurred—algorithmically, deterministically, and reproducibly—before the report is generated. The physician’s role is clinical integration, not analytical interpretation. Treating this process as if it were analogous to a radiologist glancing at a highlighted corner of a mammogram fundamentally misunderstands the epistemology of the test.
Computational pathology occupies the same conceptual space. When an AI model analyzes a digitized H&E slide and produces a validated risk score for recurrence or metastasis, the output is not a “second opinion” on what a pathologist already saw. It is a new informational product derived from high-dimensional pattern recognition across thousands or millions of features. No human pathologist could reproduce it, even in principle. The insistence that such outputs must be framed as physician-mediated services, or else relegated to non-payable registries, reflects an outdated belief that diagnostic legitimacy flows only through human visual interpretation. That belief is already obsolete in genomics, and it is rapidly becoming obsolete in digital pathology.
The AMA’s resistance is further complicated by a category error about money. Much of the anxiety around AI within CPT appears rooted in the physician fee schedule: fears that new AI services will siphon dollars from E/M and procedural services, accelerate RVU proliferation, and force further conversion-factor deflation. Those are real concerns inside the physician payment system. But they are largely irrelevant to computational pathology and genomics, which live on the Clinical Laboratory Fee Schedule, not the RVU-based PFS. These tests do not compete with physician work RVUs; they compete with other diagnostics. Blocking them does nothing to protect physician income, but it does distort innovation in laboratory medicine.
In effect, CPT is using governance principles designed to prevent AI from unbundling physician interpretation in radiology and applying them wholesale to domains where interpretation has already been disintermediated by data scale. The result is not thoughtful containment but structural exclusion. By rejecting these services from PLA eligibility, declaring them incompatible with Category I, and shunting them toward Category III, Appendix-like registries, or future CMAA constructs that lack payment authority, CPT is signaling that algorithmic information extraction from existing clinical material is not a legitimate diagnostic act. That position is increasingly untenable.
The Myriad–PATHOMIQ evolution illustrates the consequences. Initially, PATHOMIQ was framed as a standalone AI diagnostic test, reflecting confidence in its scientific validity. Within months, it was repositioned as an embedded, invisible enhancement inside an already covered genomic assay. This was not a scientific retreat; it was a reimbursement survival maneuver. The AI did not fail. The coding system did. Smaller companies without a Myriad-scale sponsor will not be able to make this pivot, and many will simply disappear or remain trapped in perpetual pilot status.
The deeper risk is that CPT policy is unintentionally privileging molecular redundancy over informational efficiency. If payment is available only when a new analyte is measured, innovators will be driven to create ever more complex wet-lab assays—even when equivalent or superior information could be extracted computationally from data we already generate. That is not cost containment; it is technological distortion. It rewards chemistry over computation, not because chemistry is better, but because the coding ontology cannot see computation as a test.
In short, AMA CPT is not trying to cause a disaster, but it is governing the future with the wrong mental model. AI in radiology is not the template for AI in pathology or genomics. Advisory tools are not autonomous diagnostics. RVU anxiety is not relevant to CLFS innovation. Until CPT explicitly recognizes that some AI systems are the diagnostic act—rather than aids to it—the collision between policy and science will intensify. And when that collision becomes visible to payers, industry, and Congress, it will not be interpreted as prudent stewardship. It will be seen as an institutional failure to adapt to how medicine now produces knowledge.
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Myriad February to October 2025
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ARe there any interesting differences between Myriad's description of its pATHomIQ collaboration initially (February, march 2025) and recently (October-November 2025)?
Yes — there are meaningful and revealing shifts between Myriad’s initial description (Feb–Mar 2025) of the PATHOMIQ collaboration and the later framing (Oct–Nov 2025). They are subtle in wording but significant in strategic intent, especially when viewed through a reimbursement, coding, and commercialization lens.
Below is a structured comparison, grounded directly in the documents you uploaded.
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1. February–March 2025: PATHOMIQ as a standalone AI test
In the initial press release (Feb 24–25, 2025) and contemporaneous coverage (e.g., Urology Times), Myriad presents PATHOMIQ_PRAD very much as its own clinical test, albeit one licensed and commercialized by Myriad.
Key characteristics of the early framing:
a) Explicit “AI-driven clinical test” language
The press release repeatedly states Myriad intends to “commercially launch its first AI-driven prostate cancer clinical test later this year.” The implication is a distinct test offering, parallel to Prolaris, not merely an internal analytic component
2025 Myriad 0225 PathomIQ PRAD …
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b) Emphasis on speed, independence, and outperforming markers
PATHOMIQ_PRAD is described as:
• Analyzing digitized H&E whole-slide images
• Returning results within 1 day
• Outperforming Gleason, TNM, and genomic tools in some cohorts
This language positions PATHOMIQ_PRAD as a competitive prognostic modality, not just a complementary add-on
2025 Urol Times 0301 Myriad and…
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c) Strong hints at future platform expansion
The early materials stress that although the current model is post-prostatectomy, the foundational model could apply broadly across solid tumors. That reads like a platform commercialization vision, not merely a prostate-specific enhancement
2025 Myriad 0225 PathomIQ PRAD …
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Interpretation:
At launch, Myriad appears to be testing the waters for whether PATHOMIQ could stand as a billable, brand-recognizable AI test—even if bundled operationally with Myriad infrastructure.
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2. October–November 2025: PATHOMIQ as a component inside Prolaris
By October 2025, especially in Myriad’s own blog post (“Enhancing Prostate Cancer Genomics with AI-Powered Morphometric Analysis”), the framing shifts decisively.
a) PATHOMIQ is no longer framed as a standalone test
Nowhere in the October 2025 blog does Myriad describe PATHOMIQ_PRAD as a separate, orderable test. Instead, the language is:
“Soon, the Prolaris Test will integrate AI from PATHOMIQ…”
2025 Myriad 1023 Progress with …
That is a major rhetorical downgrade from “launching our first AI-driven test.”
b) AI is repositioned as an “amplifier,” not an answer
Repeated phrases include:
• “AI plus genomics”
• “Not a replacement; it’s an upgrade”
• “A precision amplifier”
This is a clear de-risking move. PATHOMIQ is now framed as:
• Supporting clinician judgment
• Enhancing an already-covered genomic assay
• Avoiding claims of independence or displacement
2025 Myriad 1023 Progress with …
.
c) Independence is explicitly walked back
The October post even critiques tools that market themselves as “independent decision aids”, arguing instead for consolidated, integrated reports that already incorporate CAPRA, clinicopathology, and genomics.
That passage reads, frankly, like a quiet repudiation of how PATHOMIQ_PRAD was initially positioned earlier in 2025
2025 Myriad 1023 Progress with …
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Interpretation:
By fall 2025, Myriad appears to have concluded that selling PATHOMIQ as a standalone AI test is commercially and policy-risky, and that its highest value is as an embedded analytic layer inside Prolaris.
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3. What changed — and why it matters
From a reimbursement perspective
The shift aligns almost perfectly with the CPT realities you outlined earlier:
• A standalone “upload DICOM → download report” test has no clean CPT home
• PLA is unavailable
• Cat I is structurally hostile
• Cat III is weak and unattractive
• CMAA is uncertain and likely non-paying
Embedding PATHOMIQ inside Prolaris allows Myriad to:
• Avoid new CPT battles
• Preserve existing coverage
• Treat AI costs as internal COGS, not billable services
From a risk-management perspective
The early 2025 language was ambitious and externally facing (investors, urologists, media).
The late 2025 language is defensive, integrative, and payer-aware.
This is classic Myriad behavior:
innovate aggressively, then stabilize within reimbursement reality.
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4. Bottom line
Yes — the evolution is real and important.
• Early 2025: PATHOMIQ_PRAD is framed as a new AI clinical test that could stand alongside or even outperform existing tools.
• Late 2025: PATHOMIQ becomes an embedded morphometric layer inside Prolaris, explicitly positioned as complementary, supportive, and non-disruptive.
That shift strongly suggests Myriad learned — quickly — that AI-only morphology products face structural barriers in CPT and payer systems, and that the winning move is absorption, not exposure.
If you want, next we could:
• Map this transition onto specific CPT committee anxieties, or
• Compare this arc to other AI pathology companies that failed to make the same pivot.
