Saturday, August 22, 2026

Blog 5 of 5: AI Rewrites My Human Blog #3 (Super-Providers)

In this series of 5 blogs, Blog 3 (national and super-provider utilization) was written by Quinn by hand.  Here is  Blog 3, rewritten from source material entirely by Chat GPT 5.6.

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88305: Blog 5 of 5 — What Medicare’s Biggest Users Tell Us About the 25-Minute Problem

The developing Medicare controversy over CPT 88305 can be approached from two directions. The Maryland Health Care Commission approached it at the level of the provider-day: multiply the number of 88305 services billed by Medicare’s assigned physician time, and ask whether the resulting workload can fit into an actual day. Sometimes it cannot. Maryland found hundreds of days on which 88305 alone translated into more than 24 hours of nominal physician work.

There is another way to look at the same issue. Instead of studying individual days in Maryland, one can pull back and examine an entire year of national Medicare utilization. CMS’s CY2024 Medicare Physician & Other Practitioners — by Provider and Service public-use file offers exactly that perspective. Filtering the enormous database to a single code, 88305, reveals both the scale of the business and some remarkable concentrations of utilization.

The national data cannot determine how many minutes a pathologist actually spent on a particular slide. Nor should they be treated as if they could. But as a broad reality check on the longstanding assumption that a typical 88305 contains 25 minutes of pathologist intraservice work, they are unusually provocative.

[Note, the following is a huge, confusing and complicated CMS cloud database that AI navigates with ease!]

CMS Medicare Physician & Other Practitioners — by Provider and Service

First, 88305 Is Nearly a Billion-Dollar Medicare Business

In CY2024, 88305 generated roughly $931 million in Medicare allowed amounts. “Allowed” is important terminology here: this is not simply the amount of Medicare checks written to laboratories and physicians, but the Medicare allowed charge, including the beneficiary share where applicable.

The national file contains about 17,430 provider/place-of-service rows for 88305. That does not mean 17,430 different physicians. CMS aggregates this file by NPI, HCPCS code, and place of service, so one NPI can generate more than one row. Nevertheless, the specialty distribution gives a good picture of where the code lives economically. Roughly 13,700 rows are classified as pathology, about 1,700 as dermatology, and about 900 as gastroenterology. Only a few dozen are classified as urology.

The near-absence of urology is historically interesting. Medicare long ago removed routine prostate needle-biopsy pathology from ordinary per-specimen 88305 billing and moved it to the bundled G0416 structure. No longer could 50  prostate needles be billed as 88305x50 (!).  As a result, by now ,urology practices are almost absent from the 88305 business line.

The broad national picture is therefore approximately:

CY2024 measureApproximate result
88305 Medicare allowed amount$931 million
Provider/place-of-service rows17,430
Clinical Laboratory allowed amount$226 million
Other provider categories$705 million
Average 88305 services per beneficiaryabout 2.0

For laboratories, pathology groups, and investors who own pathology businesses, this is obviously not an academic argument over a dusty RUC number. Even a moderate change in 88305 valuation could move substantial amounts of money.

The Largest Clinical Laboratories

About $226 million, roughly one quarter of national 88305 allowed dollars in this file, appears under the Clinical Laboratory category. The business is also fairly concentrated. The top 15 laboratory rows alone account for approximately 1.2 million 88305 services and $77 million in allowed amounts, roughly one third of the entire Clinical Laboratory portion.

[INSERT TABLE — TOP 15 CLINICAL LABORATORIES]

click to enlarge


The largest laboratory row contains nearly 138,000 88305 services in a single year. Several others exceed 100,000. Those figures are impressive, but they are not inherently implausible. A large pathology laboratory may employ or contract with many pathologists, receive specimens from a wide geographic area, and operate a substantial histology production system.

The interesting exercise is to translate those volumes back into the language of physician time used to construct the fee schedule. The accompanying spreadsheet uses a deliberately conservative assumption of roughly 20 minutes per 88305, rather than Medicare’s 25-minute intraservice figure. Even at 20 minutes, the top 15 laboratories collectively represent about 400,000 nominal pathologist hours, or approximately 200 pathologist-years if a full professional year is represented as 2,000 hours.

At the individual laboratory level, this works out to roughly 9 to 23 pathologist-years of nominal 88305 work per entity. For a sufficiently large laboratory, that is at least conceptually possible. It might actually have a dozen or two dozen pathologists supporting the operation. The calculation therefore does not show that anything is wrong with these laboratories. Instead, it demonstrates the enormous professional workforce that Medicare’s historical time assumption says should sit behind their 88305 production.

The data become stranger when the same exercise is applied to provider records identified with individual NPIs.

When an Individual NPI Begins to Look Like a Pathology Department

The top 15 non-laboratory provider rows—almost all classified as pathology, with one dermatologist—reported roughly 537,000 88305 services during CY2024 and about $32 million in allowed amounts.

[INSERT TABLE — TOP 15 PATHOLOGISTS / DERMATOLOGISTS]

click to enlarge


The highest-volume row contains 58,180 services for approximately 32,000 Medicare beneficiaries. Even at the reduced 20-minute assumption used in the spreadsheet, those services correspond to about 19,200 nominal hours of pathologist work. That is nearly ten 2,000-hour professional years compressed into one calendar year.

And the top row is not an isolated statistical freak. Other individual-provider rows translate into five, six, seven, or eight nominal pathologist-years. Even at the bottom of the top-15 table, approximately 25,000 services correspond to more than 8,000 nominal hours, or about four full-time professional years. Taken together, these 15 records represent roughly 177,000 nominal hours, approaching 90 full-time pathologist-years.

Nobody should read those calculations literally and conclude that 15 pathologists somehow performed 90 years of labor during 2024. The point is almost the opposite. If legitimate Medicare billing produces utilization volumes that cannot remotely coexist with the time attached to the service, then the time assumption itself becomes a reasonable object of scrutiny.

There is also an important distinction from the large-laboratory table. These are not merely 15 rows labeled as giant corporate clinical laboratories. CMS identifies these high-volume records with individual NPIs. Payment reassignment, practice organization, technical-component billing, and other claims mechanics can complicate what that means operationally, but the basic observation remains striking.

A Claims-Data Caveat, Once

The CMS public-use file is highly aggregated. In particular, this simple analysis cannot fully disentangle professional-component, technical-component, and global 88305 billing, together with the claims reassignment and date-of-service conventions that may lie behind a particular row. A technical-component-only service obviously should not be converted into 20 or 25 minutes of personal pathologist microscope time.

For example, a "Dr Wilson" may be attributed 5000 units of 88305, but 4500 were technical component only and shipped to a different sign-out doctor.  Dr Wilson signed out only 500 interpretations, just ten per week.    The simple public tables don't distinguish his global, professional, or "only-technical" billing events.

On the other hand, there is another reason the national analysis may actually understate total physician activity: the CMS file covers traditional Medicare fee-for-service, not the provider’s Medicare Advantage, commercial insurance, Medicaid, or other work.  And within fee-for-service, we haven't tallied extra special stains of immunohistochems (each +20 minutes) for the super-providers.  While the CMS file (used by me here today) is CMS only, the Maryland file had all-payor origins.

Maryland Asked the Same Question One Day at a Time

This national utilization exercise fits remarkably well with the Maryland analysis that triggered CMS’s current review. The Maryland Health Care Commission used its All-Payer Claims Database to examine claims provider by provider and day by day. It multiplied billed services by the physician intraservice time embedded in the Medicare Physician Fee Schedule and asked whether the resulting workday was plausible.

For 88305, the answer was repeatedly troubling. Maryland identified 1,763 provider-days on which 88305 alone represented more than eight hours of nominal intraservice physician time. On 587 days, 88305 by itself represented more than 24 hours. When the other services billed by those providers were added, the extraordinary days averaged roughly 37 hours of nominal fee-schedule time. The Maryland investigators described 88305 as their most extreme outlier.

  • [For more about the Maryland analysis, Mesta et al. published June 2026 in Health Affairs - see our Blog #4.].

Maryland appropriately emphasized that these calculations were not accusations of fraud. Medicare does not require a physician to spend exactly the RUC-assigned number of minutes on every service, and efficiency is not improper. The implication is instead directed back at the valuation methodology: if physicians can legitimately produce service volumes that make the assigned time physically impossible, then perhaps the assigned time is not an accurate description of contemporary practice.

The CY2024 Medicare analysis reaches essentially the same issue from the opposite direction. Maryland finds impossible-looking numbers within particular working days. The national data show individual provider NPIs accumulating several professional years’ worth of nominal time over a calendar year.

Multiple Specimens Are Part of the Story

There is another reason 88305 is particularly interesting as a payment unit. It is fundamentally a specimen-based code, and a single patient encounter can appropriately generate more than one separately examined specimen.

Across the national file, the average is approximately two 88305 services per beneficiary. Gastroenterology runs somewhat higher, around 2.6. A small number of gastroenterology provider rows reach roughly five to ten services per beneficiary.

Those figures are not evidence of overuse by themselves. A colonoscopy or upper endoscopy may appropriately produce specimens from several anatomical sites, and a dermatology encounter may likewise produce multiple biopsies. But the numbers illustrate the economic importance of the specimen as the billing unit. Every additional specimen can generate another 88305 payment and, within the fee-schedule model, another complete block of physician time.

Medicare has encountered this “multiples” issue before. Prostate needle biopsy pathology is the clearest precedent. Under the older system, separating many prostate cores could generate numerous units of 88305. CMS ultimately rejected that linear relationship and adopted G0416, paying a single pathology service regardless of how many prostate needle-biopsy specimens were submitted.

That history does not imply that all 88305 pathology should be bundled. It does demonstrate that CMS has previously concluded that incremental specimen count and incremental professional work need not rise in a one-for-one relationship.

What 88305 Actually Represents

A major complication in any revaluation is that 88305 covers an extraordinarily heterogeneous universe of pathology. A straightforward gastrointestinal biopsy, a small skin specimen, and a diagnostically challenging tissue sample can all fall under the same CPT code even though the professional effort required may differ greatly.

That is why a defense of 88305 based on difficult cases is simultaneously correct and incomplete. Some 88305 cases certainly require 25 minutes. Some require considerably longer. The question for Medicare valuation, however, is not whether an 88305 can take 25 minutes. It is whether 25 minutes is a credible representation of the typical physician intraservice work across millions of services.

This distinction matters because the existing number has more historical pedigree than might initially be assumed. The 25-minute figure is not merely an untouched artifact from the original Harvard RBRVS work three decades ago. The 88305 family was reconsidered, pathologists were resurveyed, and the RUC explicitly accepted 25 minutes of intraservice time in 2010 while retaining the existing work RVU.

That makes the current conflict particularly revealing. The fee-schedule system asked physicians how long the work takes and obtained 25 minutes. A later CMS-sponsored Urban Institute pilot observed a median of only about two minutes, although in a small and nonrepresentative sample. Maryland then applied the fee-schedule time to actual claims and found numerous impossible provider-days. Now the national Medicare data show very high-volume individual provider NPIs whose annual service counts translate into multiple full-time professional years under anything close to the historical time assumption.

None of these observations, individually or collectively, proves that the correct answer is two minutes, five minutes, ten minutes, or fifteen minutes. They do make the status quo increasingly difficult to defend simply by pointing back to the earlier survey.

Why the Commercial Community Should Pay Attention (Private Equity)

The obvious audience for the 88305 debate includes pathologists, CAP, CMS, and the AMA RUC. But the economic audience is wider.

Routine surgical pathology has become a meaningful investment sector. Large national laboratories, regional pathology groups, dermatopathology operations, gastrointestinal pathology businesses, and physician-office laboratories have all attracted strategic buyers and private-equity capital. In many of these businesses, 88305 is not peripheral revenue. It is part of the economic foundation.

A substantial change in 88305 professional valuation could therefore affect acquisition models, practice EBITDA, laboratory staffing economics, and the value attributed to high-throughput pathology platforms. The risk would not be distributed evenly. Businesses whose economics depend heavily on enormous volumes of relatively routine 88305 specimens would logically be more exposed to a major reduction than practices whose revenue is diversified across more complex surgical pathology, molecular testing, consultation, and other services.

The policy dispute consequently has a commercial dimension that may be easy to miss when reading a few paragraphs in the Federal Register. CMS has not yet proposed a specific new work RVU for 88305. But once an almost billion-dollar code enters the potentially misvalued-code process because empirical utilization appears inconsistent with its assigned physician time, anyone valuing a pathology business should at least know that the issue exists.

The Larger RUC Question

The significance of 88305 may ultimately extend beyond pathology. The traditional RUC methodology relies substantially on specialty surveys, clinical vignettes, and comparisons with services that already have established relative values. That creates an internally coherent system: one code is judged relative to another, which is judged relative to another.

What the Maryland analysis introduces is an external test. Instead of asking whether 88305 seems appropriately valued relative to some other service, it asks whether all the assigned minutes can coexist within the ordinary limits of a day.

The national CMS utilization data offer another version of the same test. If an individual provider NPI legitimately accumulates 40,000, 50,000, or nearly 60,000 units of a code in one year, what does that imply about the plausibility of the time attached to each unit?

This does not mean claims data should replace professional judgment. Claims files have their own artifacts and can mislead when modifiers, global services, reassignment, or dates are misunderstood. But the choice need not be between physician surveys and administrative data. A more persuasive valuation system could use both: professional judgment to characterize complexity and intensity, and empirical utilization to test whether the resulting assumptions remain compatible with real-world practice.

Bottom Line

CPT 88305 is nearly a billion-dollar annual Medicare service, and a substantial share of that business is concentrated in very high-volume laboratories and provider practices. The top 15 clinical-laboratory rows alone report more than 1.2 million services. The top 15 individual-provider rows report another 537,000.

The public-use data are not precise enough to convert those service counts into literal pathologist working hours. Professional, technical, and global billing distinctions matter. But the discrepancy is large enough that this caveat does not make the underlying question disappear.

Maryland has already shown that Medicare’s 25-minute assumption can generate provider-days longer than 24 hours. The national CY2024 data now show the same tension across an entire year: some individual provider NPIs report enough 88305 services to represent several full professional years of work under anything close to the historical time assumption.

The question facing CMS is therefore not whether pathologists perform important work, or whether some 88305 cases are difficult and time consuming. Both are obvious. The more precise question is whether 25 minutes remains a plausible typical value for the incremental physician work represented by each of the millions of 88305 services Medicare purchases every year.

The answer will matter directly to pathology. But the precedent may matter much more widely. If CMS begins routinely testing RUC-derived physician times against actual clinical throughput, 88305 may be remembered less as an isolated pathology payment dispute than as an early example of a new way Medicare decides whether its own valuation system still describes the medicine being practiced.

Blog 4 of 5; We Discover the Source of the CMS 88305 Data: Mesta et al., June 2026!


50-word summary

CMS’s July 2026 CY2027 Physician Fee Schedule proposal reproduced striking Maryland data suggesting CPT 88305 may be overvalued -- without naming the source. 

Discoveries in Health Policy has discovered that the trail leads to Maryland Health Care Commission officials Mesta, Chappel, and Jacobs in Health Affairs

Their open-access article adds useful detail—and methodological questions that pathologists will find worth raising now.

150-word summary

CMS’s July 2026 CY2027 Physician Fee Schedule proposal drew attention by reporting Maryland claims data that make the 25-minute physician-time assumption for CPT 88305 look implausible. CMS called the submitter only an “interested party.” The underlying work can now be traced to the Maryland Health Care Commission and an open-access Health Affairs Forefront article by Shankar Mesta, Andre Chappel, and Douglas Jacobs. The article reproduces CMS’s extraordinary 88305 findings—1,763 provider-days exceeding eight nominal hours, 587 exceeding 24 hours, and about 37 hours when other services are included—and adds methodological detail. It also exposes questions commenters should raise before the September deadline: handling of professional versus technical components, pathology date-of-service conventions, provider attribution, and the small, nonrepresentative Urban Institute study behind the famous two-minute estimate. Brett Matsumoto’s 2020 American Economic Review critique of “impossible hours” analyses provides useful ammunition for demanding claims-level sensitivity tests before CMS acts this fall. 

This blog: Authored by Chat GPT 5.6.

Source:

https://www.healthaffairs.org/content/forefront/states-all-payer-claims-databases-can-help-cms-more-accurately-value-services


Found: The Maryland Source Behind CMS’s 88305 Challenge

An open-access Health Affairs article fills in the backstory to CMS’s extraordinary “37-hour workday” data—and gives both sides of the 88305 debate material worth putting into the public record now

The 88305 story in the July 2026 proposed CY2027 Medicare Physician Fee Schedule is becoming more interesting, not less.

CMS devoted several paragraphs of the proposed rule to striking Maryland claims data suggesting that the long-standing physician-time assumption for CPT 88305 may substantially exceed real-world practice. CMS reported 1,763 provider-days on which nominal 88305 intraservice time exceeded eight hours, including 587 days on which 88305 alone added up to more than 24 hours. When other billed services were added, CMS reported an average nominal workload of about 2,217 minutes—roughly 37 hours—on those high-volume days. CMS also highlighted an older Urban Institute study that measured a median 88305 intraservice time of only two minutes, versus the 25 minutes carried in the Medicare Physician Fee Schedule.

What CMS did not do was identify the nominator by name. Throughout the discussion, the Federal Register refers simply to an “interested party” or “the nominator.”

The College of American Pathologists has subsequently identified that nominator as the Maryland Health Care Commission (MHCC). But there is another piece of the paper trail that appears to have received relatively little attention: on June 5, 2026—more than a month before the proposed rule—three MHCC officials, Shankar Mesta, Andre Chappel, and Douglas Jacobs, published an open-access Health Affairs Forefront article laying out essentially the same analysis in considerably more detail.

Read Mesta, Chappel and Jacobs in Health Affairs

The article is titled “How States’ All-Payer Claims Databases Can Help CMS More Accurately Value Services.” Mesta is MHCC’s chief of Cost and Quality; the article expressly states that the authors serve at MHCC and that MHCC submitted the analysis to CMS through the Potentially Misvalued Codes process. Maryland’s own website also lists a February 2026 report carrying the same potentially-misvalued-code analysis. Thus, strictly speaking, the formal CMS source was the MHCC nomination, while Mesta et al. is the contemporaneous public exposition of that work. (Health Affairs)

For anyone preparing comments on 88305 before the September 14, 2026 deadline, the Health Affairs article is worth retrieving now. (Centers for Medicare & Medicaid Services)

Mesta et al. tells considerably more of the story

CMS summarizes the Maryland numbers rather dryly. Mesta and colleagues provide the argument behind them.

The article begins with an explicit criticism of Medicare’s traditional dependence on surveys performed through the AMA Relative Value Scale Update Committee. It cites a GAO finding that the median RUC survey contained only 52 responses and had a median response rate of 2.2 percent. The authors argue that empirical data should increasingly be used to test whether survey-derived physician times remain plausible in current practice. (Health Affairs)

Their proposed test is wonderfully simple. Take claims attributed to a provider on a given day, multiply each service by the intraservice physician time embedded in the PFS, and add the minutes. The calculation assumes the PFS times are correct. Therefore, when that assumption generates a 20-, 30-, or 40-hour workday, something in the model deserves another look.

Importantly, Maryland did not blindly screen the entire fee schedule. It began with 60 codes previously studied empirically by the Urban Institute and 326 surgical codes evaluated by RAND—services for which empirical studies had already suggested shorter times than the PFS. Maryland then looked in its 2023 all-payer claims database for billing patterns that could independently test those discrepancies. That selection method makes the study a useful confirmatory exercise, but not an unbiased census of overvaluation throughout the PFS. (Health Affairs)

And 88305 was not merely one of the results. It was the spectacular outlier.

Nearly 2,000 work-days exceed 8 hours - for 88305 alone.

Maryland found 1,763 provider-days above eight nominal hours of 88305 alone, versus only 40 such days for 88307 and much smaller numbers for the other nominated services. On 587 occasions, 88305 itself exceeded 24 nominal hours. When other services were added, Mesta et al. report an average of about 37 hours. (Health Affairs)

The article also makes a point CMS softens. Mesta and colleagues observe that gastroenterologists and dermatologists appeared frequently among these high-volume billers. They explicitly say this is not evidence of fraud or inappropriate billing. But they go on to speculate that the relatively favorable valuation may have encouraged some specialists to establish laboratories and capture pathology revenue themselves, potentially creating an incentive toward excess biopsy utilization. CMS reports the GI and dermatology finding but does not reproduce that more provocative inference. (Health Affairs)

That distinction is worth preserving. The claims analysis can test whether a time assumption is plausible. By itself, it does not establish unnecessary biopsies, self-referral abuse, or improper billing.

One curious difference between CMS and Health Affairs

There is also a small but potentially meaningful discrepancy between the two presentations.

Mesta’s exhibit labels its second-stage calculation as average intraservice time of all codes on the high-volume days. Thus, the Health Affairs table gives 37 hours for 88305, 23 hours for 15734, 12 hours for 19318, 30 hours for 19380, and so forth. (Health Affairs)

CMS describes its calculations somewhat differently. The proposed rule says that for 88305 the 37 hours included other codes and pre-service time as well. For several surgical codes, CMS consequently reports substantially larger totals than the Health Affairs exhibit—for example, about 32 rather than 23 hours for 15734, 41 rather than 30 hours for 19380, and 52 rather than 38 hours for partial hepatectomy.

This may simply reflect additional calculations contained in MHCC’s underlying nomination letter that were not reproduced in the Health Affairs table. But commenters would be justified in asking CMS to state precisely which time elements were used in each calculation and to release or summarize the analytic specifications sufficiently for replication.

For 88305, the distinction does not rescue a 37-hour result. It matters because CMS is considering a valuation policy, and reproducibility matters.

There are real questions to ask about the Maryland method

The strength of the Maryland result is its sheer magnitude. If an assumption routinely produces impossible workdays, it is difficult simply to shrug at it.

But an impossible calculated workday does not tell by itself which assumption is wrong. The embedded PFS time may be wrong. The claims may be attributed to a provider in a way that does not correspond to personal physician work. Component billing may be misunderstood. The date attached to the claim may not be the day the pathologist actually reviewed the slide. Several effects can coexist.

This is where commenters opposed to a major 88305 revaluation should concentrate their effort. The best response is not that claims-based reality checks are conceptually illegitimate. It is to show specifically where the Maryland calculation does—or does not—translate claims into physician work correctly.

One obvious question is professional versus technical component billing. Surgical pathology can be billed globally, as a professional component with modifier 26, or as a technical component. A technical-only 88305 unit clearly cannot be assigned 25 minutes of pathologist interpretation. The published Health Affairs article says Maryland multiplied the “quantity of services submitted by a rendering provider” by PFS time, but it does not explain in the article how component modifiers, split billing, duplicate global/component representations, or other claims mechanics were normalized. That does not prove Maryland got this wrong; it identifies something that needs to be shown.

A second issue is particularly important in pathology: date of service. CMS’s own billing guidance states that the technical component of surgical pathology is dated to specimen collection. For a globally billed pathology service, Medicare permits the provider to report either the date the professional interpretation is completed or the date the technical component was performed. A professional-component-only claim uses the date the review and interpretation was completed. (Centers for Medicare & Medicaid Services)

That means a pathology claims file can potentially place multiple global services on a specimen-collection date even when the microscopic interpretations were not literally all performed on that calendar day. For an analysis whose unit of observation is the provider-day, that is not a trivial issue. Commenters should ask whether MHCC distinguished global, PC and TC claims and whether it tested the result using only claims whose date of service most closely corresponds to actual professional interpretation.

CAP has now raised these same categories of concern publicly. Its August 5 response argues that the Maryland analysis does not adequately account for Medicare billing rules, reassignment requirements, date-of-service conventions, and limitations of claims data in representing pathology intraservice work. (College Of American Pathologists)

Those objections should not remain merely in a CAP press release. To the extent they can be quantified, they belong in the formal CMS comment record.

And then there is the famous “two minutes

The 25-versus-2-minute comparison is powerful rhetorically, but the two-minute number deserves some context.

The source is a 2016 CMS-sponsored Urban Institute report, Stephen Zuckerman et al., “Collecting Empirical Physician Time Data: Piloting an Approach for Validating Work Relative Value Units.” Its table really does show 88305 with a PFS intraservice time of 25 minutes and a median empirical time of 2 minutes—a ratio of 12.5 to 1. CMS cites this Urban report directly in the proposed rule.

Read the Urban Institute report

But this was a pilot, not a national 88305 time-and-motion survey. Urban approached nearly 20 potential organizations and ultimately collected direct-observation data at only three sites; the authors explicitly describe them as a convenience sample that “should not necessarily be viewed as representative.” Service volumes were low for many studied codes. Urban itself also singled out 88305 as clinically heterogeneous: one code can represent one or multiple tissue samples, with very different work depending on tissue source and the nature of the request.

Thus, two different propositions should not be conflated:

The current 25-minute assumption can generate implausible aggregate workloads. Maryland supplies striking evidence for that proposition.

The correct national typical 88305 time is two minutes. The Urban pilot is much weaker evidence for that much more specific proposition.

A commenter could accept the first proposition enthusiastically while challenging the second.

Matsumoto: useful ammunition for commenters

Anyone preparing a technical critique of the Maryland method should also retrieve Brett Matsumoto’s 2020 letter-to-editor in the American Economic Review, “Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Comment.”

Read Matsumoto in the American Economic Review

Matsumoto was responding to a 2017 paper by Hanming Fang and Qing Gong. Fang and Gong had taken Medicare utilization data, assigned physician times to services, and found roughly 2,300 physicians whose claims implied more than 100 hours of Medicare work per week. (American Economic Association) [Firewall]   "Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked."

Matsumoto showed why some of those fantastic numbers could be artifacts of claims architecture rather than superhuman physicians. Aggregated public Medicare data can count separately billed portions of a service in ways that make the apparent service count misleading. His most dramatic examples involved global surgery and ophthalmology, where postoperative-only services could create extraordinarily inflated apparent procedure counts. He therefore turned to detailed claims data and adjusted for billing features including professional and technical components and other modifiers. (American Economic Association)

Matsumoto is not an 88305 paper, and his cataract-billing examples do not automatically invalidate Maryland’s pathology findings. That would be an overreach.

But he provides almost a ready-made methodological question for CMS:

Before converting an “impossible hours” calculation into a national RVU change, has CMS verified the result using claims-level information capable of distinguishing the billing components and attribution rules that created the apparent service count?

That is excellent ammunition for a comment letter.

Fang and Gong’s 2020 reply is also worth reading. They acknowledged the service-overcounting issue but found that their qualitative conclusions survived their corrections. They also made the important observation that regulators themselves possess much richer claims data than outside researchers and therefore need not remain trapped by limitations of aggregated public files. (AEA Publications)

That seems particularly apt here. CMS has the Medicare claims. It can perform the PC-only, global-only, modifier-specific and date-of-service sensitivity analyses itself.

A simple example [BQ].  Dr. Wilson bills CMS for 6000 units of 88305 in this database - about 2000 hours of work-time per RUC.  However, he may have supervised a lab that did 5500 units of technical component (blocks, slides) for outside third-parties, which were immediately shipped out by Dr. Wilson.  Dr. Wilson actually signs out 500 units of 88305 -26 (professioinal) per year, only 10 per week.  Simple views of public CMS data will attribute "6000" units of 88305 to Wilson, cobbled together whether they be technical billing lines, professional billing lines, or global billing lines.

Another pathology paper points in Maryland’s direction

There is also an interesting 2017 paper from the American Journal of Clinical Pathology: Daniel Cloetingh, Rodney Schmidt and Christina Kong, “Comparison of Three Methods for Measuring Workload in Surgical Pathology and Cytopathology.”

Read the AJCP workload study

This was not a Medicare payment study and should not be presented as one. It compared alternative methods for measuring actual pathology workload at Stanford. But its findings are remarkably relevant to the present debate.

The authors concluded that RVUs tend to favor subspecialties with high volumes of small specimens. They specifically found GI and GU workload lower when measured with the Royal College of Pathologists complexity system than when measured with RVUs, observing that both fields have large numbers of 88305 biopsies. They went further and stated that RVUs tend to overestimate workload in GI practices rich in small, mostly uncomplicated biopsy specimens. At the same time, they emphasized the enormous heterogeneity concealed inside 88305: a simple GI mucosal biopsy and a medical renal core biopsy can carry the same 88305 code despite radically different interpretive complexity. (OUP Academic)

That paper supports neither “25 minutes is right” nor “2 minutes is right.” It supports the deeper proposition that 88305 is an unusually crude container for heterogeneous pathology work, and that high-volume small-biopsy practice can look disproportionately productive when workload is measured by RVUs.

Put the arguments into the record now

CMS has not yet cut 88305 because of the Maryland analysis. In July it asked whether these services should be changed for CY2027 or in future rulemaking, and whether changes should affect physician time alone or corresponding work RVUs as well.

That makes the next several weeks important.

The Mesta article is open access, unusually readable, and written by the officials responsible for the Maryland analysis. It adds context that the Federal Register does not. Organizations intending to comment on 88305 should retrieve it, cite it, and respond to its actual methodology rather than only to CMS’s abbreviated version.

Whether CMS itself will formally cite Mesta et al. in the November final rule cannot be known. But the odds that CMS will have to grapple with the Maryland analysis are obviously high. If commenters believe there are defects in component handling, provider attribution, pathology dates of service, case-mix assumptions, or reliance on the Urban two-minute estimate, the time to put those criticisms into the administrative record is now. If CMS ultimately relies on the Maryland evidence, significant methodological objections placed before the agency will require a reasoned response in the final-rule process.

Conversely, supporters of revaluation have plenty of material here too. Mesta’s 1,763 high-volume provider-days, the 587 nominal 24-hour days, Urban’s two-minute pilot result, and the independent pathology workload literature make it difficult to maintain that the existing 25-minute assumption should simply be accepted because it has been there for years.

The emerging debate is therefore becoming considerably better than a simple fight between CMS and organized pathology. The interesting question is now empirical:

How long does contemporary 88305 professional work really take—and can Medicare construct a valuation that recognizes both the extraordinary speed of high-volume routine biopsy practice and the genuine complexity hidden inside the same code?

That is a question worth answering before somebody simply changes 25 minutes to another number.

###

Regardless of the fine print (BQ).  Regardless of the argumentation chosen, you still have an 88305 H&E and four immunostains some of which are negative) tallying about 4x20 or 80 minutes, about an hour-and-a-half of pathologist time - suggesting per RUC that 2-3 such cases and half the pathologists' workday is shot.   

50-word summary

CMS’s July 2026 CY2027 Physician Fee Schedule proposal reproduced striking Maryland data suggesting CPT 88305 may be overvalued without naming the source. The trail leads to Maryland Health Care Commission officials Mesta, Chappel, and Jacobs in Health Affairs. Their open-access article adds useful detail—and methodological questions worth raising now.

150-word summary

CMS’s July 2026 CY2027 Physician Fee Schedule proposal drew attention by reporting Maryland claims data that make the 25-minute physician-time assumption for CPT 88305 look implausible. CMS called the submitter only an “interested party.” The underlying work can now be traced to the Maryland Health Care Commission and an open-access Health Affairs Forefront article by Shankar Mesta, Andre Chappel, and Douglas Jacobs. The article reproduces CMS’s extraordinary 88305 findings—1,763 provider-days exceeding eight nominal hours, 587 exceeding 24 hours, and about 37 hours when other services are included—and adds methodological detail. It also exposes questions commenters should raise before the September deadline: handling of professional versus technical components, pathology date-of-service conventions, provider attribution, and the small, nonrepresentative Urban Institute study behind the famous two-minute estimate. Brett Matsumoto’s 2020 American Economic Review critique of “impossible hours” analyses provides useful ammunition for demanding claims-level sensitivity tests before CMS acts this fall. 


Source:

https://www.healthaffairs.org/content/forefront/states-all-payer-claims-databases-can-help-cms-more-accurately-value-services


Friday, August 21, 2026

88305: Blog 3 of 5: National and Busy-Individual Usage for 88305 in Medicare Part B

In summer rulemaking, CMS proposed surgical biopsy billion-dollar-code 88305 as a mispriced code.  Blog #1 here.    I also had Chat GPT research the policy history of the odd surg path coding system (it took 26 minutes!).  Blog #2 here.

In this third blog, I looked at provider-by-provider Medicare Part B data for 88305.  Find it here.  CY2024.

Note; See the same scope of data reviewed and written solely by AI - Blog 5 here.

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17,430 different providers paid for 88305.   $931M.

576 were Clinical Laboratories, paid $226M or about 20% of all dollars.  All the other dollars went to entities enrolled as providers (pathologists, dermatologists, etc.)

13,680 rows were pathologists.  1719 were dermatologists.  904 were gastroenterologists.  Just 33 were urologists (Medicare pays for prostate biopsies as a blanket lab fee, not per core).

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Average services per bene were 2.0.   For gastroenterologists, 2.6.  About 30 of 900 gastroenterologists billed 5-10 services per patient. 

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CLINICAL LAB DEMOGRAPHICS

The top 15 of 576 clinical labs received 34% of clin lab payments and performed 1.2M services.  At 0.3 hr per service (20 minutes), that is 400,000 hours of pathologist time or about 200 man-years of at-the-microscope pathologist diagnosis time.  That's $379,812 of income ($77M) per pathologist man-years.  (But that money-per-pathologist must also pay techs, overhead, etc).  The top 15 labs logged 9 to 23 pathologist man-years per entity and billed 50,000 to 120,000 of 88305 services (in total 1.2M) to CMS.

'PHYSICIAN" DEMOGRAPHICS

The top 15 of 16853 providers were paid $32M, or 4.5% of the total.  They performed 537,000 services.  At 0.3 hr per service, that is 177,000 microscope hours or about 90 pathologist-years.  It's $362,676 of income per fictional (2000 hr) pathologist ($32M for 90 pathologists).

The top 15 entities logged 4 to 10 pathologist-years per entity and billed 24,000 to 58,000 88305 services to CMS.  (In total, 537,000 services).   

What we show in the "provider" table is entities or NPIs that billed Medicare.  I doubt any single pathologist signed out 60,000 services (20,000 hours or 10 man-years or 2.5 actual years 24/7).  What may have been an underlying group practice of some kind may appear to be "a pathologist" or "a dermatologist" in the Medicare public display files.

Data below. Click to enlarge.  8 of the top 15 pathologists were in Florida, 1 in Texas. 4 of the top labs were in Florida, 4 in Texas.  

Labs click to enlarge



Providers click to enlarge



  


Thursday, August 20, 2026

FDA Approves De Novo Software that Makes Diagnosis on Brain MRI: NeuroPacs

August 7, we published a blog on software diagnosis in radiology and asked how fast it might come to pathology.   Here.  And we've already updated that once, August 14.  Here.

Below, FDA approves de novo software that auto classifies MRIs as Parkinson disease vs several other disorders.  Brave new world.

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AI Corner

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A few weeks ago, this blog reviewed DeepHealth SMART-B, an FDA-cleared breast-ultrasound system that detects and characterizes lesions and generates draft findings and impressions for radiologist review. That clearance prompted a broader discussion of the outlook for report generation in pathology—already visible in several U.S. research-use-only products and in some software cleared for clinical use in Europe.

Here is another timely example from a different corner of diagnostic medicine. FDA has granted De Novo classification to neuropacs, machine-learning software that analyzes diffusion MRI and produces a diagnostic classification report for Parkinson disease and two related parkinsonian disorders.

Neuropacs is not a general-purpose report-writing system, and it does not produce an open-ended neurological diagnosis from any patient with tremor. Its authorized use is considerably narrower. But that is precisely why it matters. It demonstrates that clinically consequential AI-generated reporting may arrive first as a tightly constrained, validated diagnostic work product—not as an eloquent narrative written by a large language model.

AI review follows.

Another FDA Signal: Neuropacs Turns Diffusion MRI Into a Parkinsonian-Syndrome Classification Report

The short version

On April 3, 2026, FDA granted De Novo classification to neuropacs, developed by Automated Imaging Diagnostics, a subsidiary of Neuropacs Corp. FDA created a new Class II device category called a “Parkinsonian syndrome diagnostic aid,” under product code SHO and 21 CFR 882.2000. The regulatory record is DEN240071.

The software receives diffusion-weighted MRI data from patients aged 40 or older and generates a classification report intended to help neurologists and neuroradiologists distinguish among:

  • Parkinson disease, or PD;

  • multiple system atrophy, parkinsonian variant, or MSAp; and

  • progressive supranuclear palsy, or PSP.

The underlying system uses an advanced diffusion-MRI technique known as free-water imaging, followed by a machine-learning classifier. The published model calculates imaging features across numerous brain regions and produces disease probabilities and a final classification.

This is a much more restricted claim than “AI diagnoses Parkinson’s.” FDA requires the software to be used as supplemental information alongside a conventional neurological assessment and other clinical testing. The labeling states that other causes of parkinsonism—including dementia with Lewy bodies, vascular parkinsonism, drug-induced parkinsonism, and corticobasal degeneration or syndrome—should first be excluded. Patient-management decisions must not be based solely on the software output. Those boundaries are explicit in the FDA classification order.

Still, the regulatory milestone is significant. The software analyzes a medical image and returns not merely a measurement or highlighted region, but a disease-oriented classification report. It therefore occupies some of the same conceptual territory as the emerging report-generation systems in radiology and pathology.

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Why this differential diagnosis is difficult—and important

“Parkinsonism” is a clinical syndrome rather than a single disease. Slowness, rigidity, gait abnormalities, tremor, and postural instability can occur in Parkinson disease, but also in several less common neurodegenerative disorders.

MSA may initially resemble Parkinson disease but is often associated with prominent autonomic dysfunction and a different prognosis. PSP can also initially resemble PD but may later become recognizable through characteristic eye-movement abnormalities, early falls, axial rigidity, speech problems, and other features. Both disorders generally have different treatment expectations and usually respond less consistently to levodopa than typical PD.

The distinction matters for prognosis, counseling, treatment planning, selection for procedures such as deep-brain stimulation, and enrollment in disease-specific clinical trials. Yet even experienced movement-disorder specialists may need longitudinal follow-up before the diagnosis becomes clear.

Conventional MRI can identify certain characteristic findings in established MSA or PSP, but those signs are not uniformly present, especially early in disease. Dopamine-transporter SPECT imaging—commonly known by the DaTscan brand—can help distinguish neurodegenerative parkinsonism from conditions such as essential tremor. However, an abnormal dopamine-transporter scan does not reliably distinguish PD from MSA or PSP because all three can involve degeneration of the dopaminergic system.

Neuropacs is aimed at this second, more difficult question: once neurodegenerative parkinsonism is under consideration, does the pattern of brain microstructural injury look more like PD, MSAp, or PSP?

How the software works

The approach begins with a diffusion-weighted MRI scan acquired on a 3-Tesla scanner. According to the company, the analysis requires at least 30 diffusion-gradient directions and can work with qualifying scans from Siemens, GE HealthCare, and Philips systems. The published clinical protocol required less than ten minutes of additional MRI acquisition.

Diffusion MRI measures the movement of water through tissue. Conventional diffusion-tensor methods combine several contributors to that signal. Free-water imaging instead uses a two-compartment model to distinguish water moving relatively freely in the extracellular space from diffusion occurring within or around brain tissue.

That separation may reveal subtle microstructural changes before they become obvious as gross atrophy on an ordinary anatomical MRI.

In the pivotal published model, free-water and free-water-corrected fractional-anisotropy measurements were calculated across 132 brain regions and tracts. These included areas in the basal ganglia, thalamus, cortex, brainstem, cerebellum, corpus callosum, and sensorimotor pathways. Age and sex were also included in the principal feature set, although a sensitivity analysis found that removing them did not materially reduce performance.

A linear support-vector-machine model then performed a two-stage classification:

  1. PD versus atypical parkinsonism, meaning MSAp or PSP; and

  2. if atypical parkinsonism was predicted, MSAp versus PSP.

Examples in the published study display disease-probability estimates followed by a final classification. FDA’s order more generally describes the output as a “classification report.”

The company says that the software is delivered through a secure cloud workflow and can integrate with existing picture-archiving and communication systems. In practical terms, an eligible MRI study can be routed for remote analysis and the resulting report returned to the imaging or neurological workflow. Additional technical descriptions are available on the company’s AIDP product page.

The principal clinical study

The central evidence is a 2025 prospective, multicenter cohort study published in JAMA Neurology: Vaillancourt et al., “Automated Imaging Differentiation for Parkinsonism”.

The prospective portion was conducted from July 2021 through January 2024 at 21 Parkinson Study Group centers in the United States and Canada. Investigators screened 316 patients, of whom 249 met the study criteria:

  • 99 with Parkinson disease;

  • 53 with MSAp; and

  • 97 with PSP.

For the prospective cohort, the reference diagnosis required unanimous agreement among three neurologists specializing in movement disorders. One was the examining site neurologist, while two off-site experts independently reviewed videotaped examinations, clinical scales, and conventional MRI information. The Neuropacs analysis was performed after the clinical assessment and was not used to establish the reference diagnosis.

The researchers also incorporated a retrospective training cohort of 396 patients: 211 with PD, 98 with MSA, and 87 with PSP.

Altogether, the primary model used 500 patients for training—104 prospective patients plus all 396 retrospective patients. An independent test set consisted of the remaining 145 prospective patients: 60 with PD, 27 with MSA, and 58 with PSP.

The independent test-set performance was strong:

Diagnostic comparisonAUROCSensitivitySpecificity
PD vs. atypical parkinsonism0.96187.1%88.3%
MSAp vs. PSP0.98389.7%96.2%
PD vs. MSAp0.98396.7%85.2%
PD vs. PSP0.98498.3%91.4%

The analysis was repeated with a second diffusion scan and produced similar results. The investigators also conducted 49 additional train-test splits and analyses that held out entire clinical sites. Performance declined modestly in some of the more demanding site-holdout analyses but remained generally strong, with AUROCs ranging from approximately 0.87 to 0.96.

A neuropathology analysis provided another encouraging result. Among 49 patients with postmortem diagnoses, the imaging classification agreed with pathology in 46, or 93.9%. The last clinical diagnosis agreed with pathology in 81.6%. However, the autopsy set was heavily weighted toward PSP: it contained 39 PSP brains but only five PD and five MSA brains.

An important caution about “96% accurate”

The company’s public materials sometimes describe the system as having “over 96% accuracy” or “up to 98% precision.” The underlying publication more carefully reports AUROC, sensitivity, specificity, positive predictive value, and negative predictive value.

These terms are not interchangeable.

An AUROC of 0.98 is an excellent discrimination result, but it does not mean that the device will provide the correct diagnosis in exactly 98% of ordinary clinical patients. Actual predictive performance depends on the classification threshold, the prevalence of each disease in the tested population, the patient-selection rules, and the clinical setting.

The principal study deliberately assembled substantial numbers of MSA and PSP cases. That was appropriate for developing and testing the classifier, but it does not reproduce the prevalence encountered in a general neurology practice, where PD is much more common. Positive and negative predictive values may therefore be different in routine use.

The most defensible summary is that the study produced AUROCs of approximately 0.96 to 0.98 in its independent prospective test set, with sensitivity and specificity varying by diagnostic comparison.

Strong evidence, but not yet every kind of evidence

The study is considerably stronger than the typical single-center retrospective AI paper. It was prospective, multicenter, adequately powered, tested on scanners from all three major manufacturers, included an independent test set, performed repeat-scan analyses, and included both site-holdout and neuropathology evaluations.

Several limitations nevertheless matter.

First, the principal reference standard remained an expert clinical diagnosis rather than neuropathology. Clinical diagnosis is unavoidable in most living-patient studies, but it is imperfect—especially early in disease.

Second, requiring unanimous agreement among three expert movement-disorder neurologists created a rigorous reference standard but also selected relatively classifiable cases. The patients in greatest need of a diagnostic aid may be precisely those for whom expert reviewers disagree. The authors appropriately identified evaluation in clinically ambiguous cases as a future research need.

Third, the study was conducted largely in specialist movement-disorder centers. Community neurology and general radiology practices may encounter different referral patterns, imaging quality, comorbidities, and diagnostic uncertainty.

Fourth, the study did not include all disorders that can cause parkinsonism. That limitation is reflected in FDA’s labeling, which requires clinicians to rule out several alternative conditions before using the Neuropacs classification.

Fifth, the autopsy findings are promising but still based on a small and unbalanced pathology cohort. The result is particularly preliminary for PD and MSA, with only five brains in each category.

Finally, the pivotal study established diagnostic discrimination. It did not establish that use of the software changes treatment, reduces other testing, shortens the time to a stable diagnosis, improves patient outcomes, or lowers total cost. Those are clinical-utility and health-economic questions that frequently become important after FDA authorization.

The study was supported by the National Institutes of Health. Relevant commercial relationships were disclosed: David Vaillancourt reported a licensed patent and support from Automated Imaging Diagnostics, and Angelos Barmpoutis reported being a co-founder and shareholder of Neuropacs. The disclosures do not negate the results, but they are part of a complete reading of the evidence.

De Novo classification: more than a one-product event

Neuropacs did not enter an existing FDA category through the usual 510(k) substantial-equivalence process. FDA instead granted a direct De Novo request and created a new generic device type: the Parkinsonian syndrome diagnostic aid.

FDA placed the device in Class II, concluding that its risks could be managed through general controls and new special controls. The identified risks are straightforward but consequential: false-positive or false-negative classifications, inappropriate treatment, delayed diagnosis, misinterpretation, and overreliance on the software output.

The special controls require:

  • clinical validation under anticipated conditions of use;

  • diagnostic-accuracy and reproducibility testing against a clinically relevant reference standard;

  • objective performance measures;

  • software verification, validation, and hazard analysis;

  • a technical description of model inputs and outputs;

  • disclosure of the population used for model development;

  • labeling of limitations and unvalidated subpopulations;

  • instructions for incorporating the output into the diagnostic workflow; and

  • a clear warning that the device is not a stand-alone diagnostic.

FDA also determined that future devices in this category will require premarket notification. In other words, the De Novo decision does not merely authorize Neuropacs. It creates a potential 510(k) pathway for later competitors that can demonstrate substantial equivalence while satisfying the special controls.

The FDA database indicates that no predetermined change-control plan was authorized with this De Novo. Material future algorithm changes therefore may require additional regulatory evaluation rather than being automatically covered by a preauthorized update plan.

How does Neuropacs relate to alpha-synuclein testing?

The timing is particularly interesting because laboratory testing for abnormal alpha-synuclein is moving toward clinical use at the same time.

Parkinson disease and MSA are synucleinopathies, while PSP is primarily a tauopathy. Alpha-synuclein seed-amplification assays can detect misfolded alpha-synuclein in cerebrospinal fluid and, through other methods, in tissue such as skin. These tests address a molecular question: is pathological alpha-synuclein present?

Neuropacs addresses a different question: what pattern of neurodegeneration is visible across the brain, and does that pattern more closely resemble PD, MSAp, or PSP?

Those are not redundant measurements.

A newly published Annals of Neurology study examined this relationship directly: Chiu et al., “Diffusion MRI and α-Synuclein Seed Amplification Status in Parkinson’s Disease”.

The investigators evaluated 462 participants with early clinically diagnosed PD from the Parkinson’s Progression Markers Initiative. Of these, 421 were alpha-synuclein SAA-positive and 41 were SAA-negative. Neuropacs’ underlying AIDP method classified 427 participants, or 92.4%, as PD and 35, or 7.6%, as having an atypical parkinsonian pattern.

SAA positivity was associated with worse olfaction and one focal free-water difference in the superior cerebellar peduncle, but it did not correspond to broad differences across the diffusion-MRI measurements. In other words, molecular evidence of alpha-synuclein aggregation did not simply map onto the global neurodegenerative patterns measured by the MRI method.

That finding supports a complementary-biomarker model:

  • SAA may provide evidence about pathological protein biology.

  • Diffusion MRI may provide evidence about the anatomical pattern and extent of neurodegeneration.

  • Clinical examination continues to define the patient’s syndrome and functional state.

The Annals analysis should not be treated as a second pivotal validation study. All participants entered as clinical PD cases, and the 35 atypical imaging classifications were not shown to be confirmed reclassifications by pathology. It is better viewed as evidence that molecular and imaging biomarkers capture partly different dimensions of disease.

This distinction may become increasingly important as neurodegenerative medicine moves from traditional syndrome labels toward biological classification and staging systems.

What Neuropacs has to do with AI-generated reports

DeepHealth SMART-B and Neuropacs are not identical regulatory precedents.

SMART-B performs lesion detection and characterization and generates draft radiology findings and impressions. Neuropacs performs quantitative image processing and generates a constrained disease-classification report. It does not appear to be an unconstrained narrative-report generator, and its public evidence does not suggest that it composes a complete neurological consultation note.

Nevertheless, both products illustrate the same larger transition.

Earlier medical-imaging AI generally returned a heat map, contour, score, measurement, or alert. A human specialist then had to translate that output into the professional diagnostic work product.

These newer systems move further down the chain. They assemble analytical outputs into something closer to the assessment that enters the clinical record:

  • SMART-B: image findings and a draft impression;

  • Neuropacs: disease probabilities and a final diagnostic classification;

  • emerging pathology systems: cancer detection, grading, tumor measurements, biomarker quantification, and structured report fields.

The key step is not necessarily elegant prose. A report can be clinically transformative even if it consists of validated structured fields, probabilities, and a templated conclusion. Indeed, that constrained architecture may be easier to validate and regulate than free-form language generation.

Neuropacs reinforces a central observation from this blog’s updated review of AI-generated pathology reports: the first widely useful AI reports may come from a modular system in which validated image analysis establishes the facts and a controlled reporting layer packages them for specialist review.

Lessons for pathology

Several features of the Neuropacs authorization may foreshadow the FDA pathway for more ambitious pathology-reporting systems.

First, narrow claims may win before general claims. Neuropacs does not diagnose every cause of parkinsonism. A pathology system may similarly begin with a tightly bounded specimen type and diagnostic question—such as prostate core biopsies—rather than “autonomous surgical pathology.”

Second, structured reports may precede generative prose. A system that reliably outputs tumor presence, Gleason patterns, Grade Group, tumor length, percentage involvement, perineural invasion status, and uncertainty flags may be closer to authorization than one that writes unrestricted paragraphs.

Third, explicit workflow position matters. FDA specifies that Neuropacs is adjunctive, must be interpreted with other clinical evidence, and should not independently determine management. Similar labeling is likely for early pathology-report generation: the pathologist remains the reviewer and signer.

Fourth, the reference standard becomes a central problem. Neuropacs used three-expert consensus and a smaller pathology-confirmed subset. Pathology algorithms may have the apparent advantage of expert slide review, but difficult cases, interobserver variability, ancillary studies, sampling limitations, and diagnostic evolution still complicate “ground truth.”

Fifth, report design is itself a safety control. Probabilities, uncertainty, excluded diagnoses, warnings, and links back to the supporting image regions can reduce misinterpretation. A polished paragraph without provenance may be less safe than a structured report that visibly exposes its evidentiary basis.

Sixth, regulatory clearance is not reimbursement. FDA’s order establishes safety and effectiveness for the authorized use; it does not create Medicare coverage or payment. The public materials reviewed here do not identify a dedicated national coverage policy or product-specific reimbursement pathway for Neuropacs. Adoption will depend on whether providers can incorporate the software cost into existing imaging economics, obtain separate payment, or demonstrate enough clinical and operational value to justify institutional purchase.

The larger significance

Neuropacs is not autonomous neurology. It does not evaluate the complete patient, establish every differential diagnosis, decide treatment, or replace a movement-disorder specialist. The FDA labeling goes out of its way to prevent that interpretation.

But it is also more than another AI heat map.

The software takes a routinely recognizable form of clinical data, performs a technically sophisticated analysis invisible to ordinary visual inspection, and returns a disease-level classification report for physician use. FDA has created a dedicated regulatory category around that function.

That makes Neuropacs another marker of where diagnostic AI is heading. The decisive transition may not be from human-written reports to machine-written prose. It may be from algorithms that provide isolated measurements to systems that assemble a bounded, reviewable diagnostic conclusion.

Radiology is already crossing that boundary. Neuropacs shows it occurring in neurodegenerative diagnosis. Pathology is likely to follow through the same route: validated image features, disciplined diagnostic logic, structured report generation, traceable evidence, and specialist sign-off.

The resulting first-generation reports may look less like ChatGPT and more like an exceptionally sophisticated synoptic report. They may also arrive sooner—and carry more clinical consequence—than the phrase “AI report generation” initially suggests.

Key links


88305: Blog 2 of 5: The Ancient History of Surg Path Coding (88305 1960s?)

Here's a challenge I gave to Chat GPT 5.6.  What's the origin of the coding system for surgical pathology - biopsies 88305, etc.   CPT produces Surg Path Levels "I" to "VI," scattered between 88300 and 88309.

The levels are different than Tier II genetic procedure levels, where one is to use a level ("I" to "IX") only if your specific gene is named there.  For Surg Path levels, CPT says use the level that is the closest match to the specimen you examined.

But where did this system come from?  Does anybody know?  Chat GPT thought for a remarkable 26 minutes before printing the answer below.

(I also asked Claude Opus, which answer was directionally similar but less detailed).

(See an article on CMS proposed revaluation of 88305 here.)

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The short answer is: the recognizable surgical-pathology ladder—88300, 88302, 88304, 88305, 88307 and 88309—is securely documented in the fourth edition of CPT in 1977

Its immediate precursor probably arose in California coding revisions between 1972 and 1974. Its deeper institutional ancestry goes back to physician relative-value studies begun in 1952.

So there are really three dates:

  • Conceptual ancestry: 1952–56.

  • Familiar pathology code family: demonstrably 1977, probably designed around 1972–74.

  • Nationwide dominance: 1983 onward.

Wednesday, August 19, 2026

88305: Blog 1 of 5: CMS Proposes Review of Code 88305. Chat GPT Writes White Paper Report.

 In July, when CMS released the proposed policies for physician fee schedule aka Part B, it included a proposal to review the valuation of code 88305, one of the most frequently used pathology codes.  The proposal came over the transom from State of Maryland.

  • Below, summaries of a white paper report written by Chat GPT on the topic.  
  • Find the 20-page AI report HERE.





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50-Word Summary

CMS’s 2026 scrutiny of CPT 88305 challenges a 25-minute pathologist time assumption re-surveyed and affirmed by the RUC in 2010. Maryland claims data suggest that assumption can produce impossible workdays. Historical radiology and pathology practice-expense resets show Medicare has previously rebased payment when older resource models no longer matched practice.

250-Word Summary

CMS’s 2026 review of CPT 88305 may become an unusually important test of how Medicare values pathology. The code’s 25-minute intraservice physician-time assumption is not merely a Harvard-era relic. In 2009 the RUC declined simply to defer to the original Harvard valuation, required further review, and in 2010 examined fresh survey data. That survey supported 25 minutes, while the RUC deliberately retained the existing 0.75 work RVU.

The new challenge comes from the Maryland Health Care Commission. Using claims data, Maryland multiplied billed 88305 services by Medicare’s assigned physician time and found numerous physician-days producing implausibly long, even greater-than-24-hour, nominal workdays. The issue is therefore not whether individual difficult cases can require 25 minutes, but whether 25 minutes remains credible as a typical value across real-world throughput.

The same “multiples dilemma” appears in immunohistochemistry. RUC assumptions of roughly 25 minutes for an initial stain and substantial time for each additional stain can imply around two hours or more for a modest multi-antibody panel, even when several slides are plainly negative.

A historical sidebar shows that Medicare has confronted analogous technological obsolescence before. In radiology, CMS and the RUC removed film-era practice-expense inputs and substituted digital PACS resources, causing major budget-neutral redistribution. In pathology, CMS later sharply revalued the 88305 technical component as modern laboratory production and throughput changed. The 2026 question is whether similar empirical reality checks will now reach physician work itself. If so, 88305 could become a precedent for testing RUC-derived times against actual clinical productivity across specialties.

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In Part B, 88305 is in the neighborhood of 15M claims and $900M.

Tuesday, August 18, 2026

Chat GPT Reviews History of McDermott Plus Consulting - After News from Politico

We're waiting for confirmation of a news item in Politico that McDermott Plus is closing in August 2026.

While we wait, Chat GPT ran a internet search for information about the history of the firm.  This article is AI-written.  It can be used as an example of current AI ability to understand a task, do research, organize it, and write it up.  It should not be taken as ground truth.

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McDermott+: A 12-Year Experiment in Health Policy, Reimbursement and Washington Advocacy

On August 18, Politico reported that McDermott+, the health policy consulting and lobbying organization affiliated with McDermott Will & Schulte, will close at the end of August, with dozens of employees entering the Washington job market. Assuming the report is correct, the closure will bring to an end a distinctive 12-year experiment in combining health policy consulting, reimbursement strategy, data analytics and conventional Washington lobbying under one roof.

For many people in health policy, McDermott+ was sufficiently familiar that its unusual corporate structure could be easy to overlook. It looked and sounded like part of the McDermott law firm, occupied the same Washington address, shared personnel and frequently worked alongside McDermott lawyers. But it was not a law practice.

A deliberate spinout — but never an independent one

McDermott Will & Emery formally launched McDermott+Consulting, or McDermottPlus, in April 2014. The announcement described it as a “separate and distinct, wholly-owned subsidiary” of the law firm. Its original menu was unusually broad: 

  • congressional and executive-branch lobbying, 
  • budget-impact and cost-effectiveness modeling, 
  • political communications, 
  • public- and private-payer coverage, coding and pricing strategy, and 
  • healthcare data analysis. 
  • The firm explicitly promoted the ability to use project fees and retainers rather than limiting engagements to traditional law-firm hourly billing to the tenth of the hour. (KSL)

Thus, McDermott+ was less a conventional corporate spinout than a closely held consulting affiliate. That distinction remained important. McDermott’s current legal notices state explicitly that McDermottPlus LLC is wholly owned by McDermott Will & Schulte and does not provide legal advice or legal services. (McDermott) Earlier McDermott+ publications similarly cautioned that communications with the consulting company did not carry attorney-client privilege.

The arrangement nevertheless allowed extremely close integration. A client could be working with McDermott+ consultants on reimbursement economics, CMS policy or lobbying and, when a question required legal analysis, bring in lawyers from the parent firm. A later McDermott case study on Medicare coverage of over-the-counter COVID-19 tests describes exactly that sequence: McDermott+ organized and advocated for a coalition, then drew on McDermott lawyers to develop the legal theory supporting a potential CMS coverage pathway. (McDermott)

The practice existed before the name

The intellectual roots of McDermott+ predated the 2014 corporate launch.

McDermott already had a prominent Washington health-policy and reimbursement practice spanning Medicare payment, coverage, coding, FDA regulation and congressional advocacy. Paul Radensky, MD, JD, and Eric Zimmerman were conspicuous participants in that world. For example, both appeared on the agenda of CMS's 2013 annual Clinical Laboratory Fee Schedule meeting, with Zimmerman representing McDermott and the Coalition for 21st Century Medicine and Radensky appearing for McDermott separately. (Centers for Medicare & Medicaid Services)

The creation of McDermott+ essentially gave that kind of work a larger nonlegal platform.

At the 2014 launch, Radensky and Zimmerman were both identified as principals. Zimmerman said the objective was a “one-stop shop” combining lobbying, analytics and policy work; Radensky emphasized the growing need for quantitative analysis and for strategies that could move new technologies through complex government regulatory and payment systems. (KSL)

Zimmerman was later explicitly described by McDermott+ as a co-founder. (McDermott+)

Paul Radensky and the reimbursement side of McDermott+

For many in the diagnostics, medical-device and biotechnology communities, however, Paul Radensky became one of the people most closely identified with McDermott+.

His background was unusual even by Washington health-policy standards: an MD from the University of Pennsylvania, internal-medicine training and a fellowship in liver disease, followed by a Harvard JD. His practice joined regulatory law to the highly specialized mechanics of obtaining Medicare coverage, coding and payment for new medical technologies. McDermott credits him with work leading to national and local Medicare coverage decisions, Coverage with Evidence Development protocols and reimbursement strategies for pharmaceuticals, biologics, devices and clinical laboratory technologies. (McDermott)

That expertise helped give McDermott+ a character different from that of a general K Street shop. A client might arrive not because a bill was moving through Congress but because a diagnostic needed a coding pathway, a medical device faced an unfavorable Medicare payment methodology, a laboratory test needed a coverage strategy, or a manufacturer needed to understand the interaction among FDA status, Medicare benefit categories, CPT or HCPCS coding and CMS payment rules.

Radensky was particularly visible in diagnostics. McDermott+ work during the period included laboratory payment policy under PAMA, advanced diagnostics, medical devices, drug reimbursement and Medicare coverage. His representative activities also included the Coalition for 21st Century Medicine and coalitions involving diabetes testing and other diagnostic technologies. (McDermott+)

Radensky subsequently stepped back from his former partner status. McDermott's current website lists him as Counsel, while still stating that he serves as a principal of McDermott+; the McDermott+ site also continued to list him among its professionals in August 2026. (McDermott) In other words, the public record suggests a gradual change in role rather than a disappearance from the organization.

From reimbursement boutique to broader health-policy operation

McDermott+ also expanded well beyond the product-reimbursement work for which Radensky was known.

By 2018, four years after its founding, the firm said it had grown to ten consultants and had deliberately recruited former executive-branch officials, congressional staff and experienced policy consultants. That year it added Mara McDermott, formerly a senior federal-affairs executive for America’s Physician Groups, and Rachel Stauffer, who had worked on Capitol Hill and in the Office of the National Coordinator for Health IT. (McDermott+)

Over time, the roster became a recognizable cross-section of Washington healthcare expertise. Debbie Curtis brought 24 years of congressional experience, including work for Rep. Pete Stark and the House Ways and Means Health Subcommittee. Rodney Whitlock had worked for Rep. Charlie Norwood, Sen. Chuck Grassley and the Senate Finance Committee. Jeffrey Davis had spent eight years at HHS before working at the American College of Emergency Physicians. (McDermott+)

Others brought expertise in Medicare Advantage, Medicaid, hospital prospective payment systems, medical devices, health economics, CMMI models and claims-data analysis. By August 2026, the public professional roster included roughly two dozen names spanning policy, lobbying, reimbursement and analytics. (McDermott+)

The resulting organization could operate at several levels of the healthcare-policy system simultaneously.

For manufacturers, McDermott+ offered product-level market-access work involving coverage, coding and payment. For hospitals and health systems, it worked on Medicare payment systems, rural-hospital policy and broader federal reimbursement issues. For plans and other organizations, it developed expertise in Medicare Advantage and Part D. For provider organizations and investors in delivery-system reform, it became active in accountable care and CMMI payment models. And for associations, coalitions and corporations, it offered traditional congressional and agency advocacy.

That breadth became the firm's defining proposition. Its website in August 2026 still described McDermott+ as combining consulting, policy and lobbying with data analytics and specialized knowledge of reimbursement, coding, coverage and quality reporting. (McDermott+)

A lobbying shop, but not only a lobbying shop

McDermott+ nevertheless became a substantial registered federal lobbying operation.

One recent academic analysis using OpenSecrets data found that McDermott+ reported about $4.39 million in federal lobbying revenue from 33 clients in 2024. Of that amount, approximately $1.11 million came from seven hospital-industry clients, placing McDermott+ among the larger firms lobbying for hospitals that year. Those figures capture disclosed lobbying revenue, not the company's separate consulting, analytics or reimbursement-strategy business. (JAMA Network)

Its work also illustrates how lobbying could be combined with technical policy expertise. McDermott+ represented hospital coalitions, technology companies, diagnostics firms and other healthcare interests before Congress and executive agencies. Zimmerman, for example, has served as Washington representative for Trinity Health, rural-hospital coalitions, diabetes-testing interests and the Coalition for 21st Century Medicine. (McDermott+)

Coalitions became another recurring feature of the model. During the COVID-19 pandemic, Radensky and Zimmerman led an effort bringing together five competing suppliers of at-home testing products to seek Medicare coverage. In another case, a McDermott+ team worked with a coalition of more than 25 organizations around Medicare direct contracting and what became the ACO REACH model. (McDermott)

Those engagements captured what McDermott+ could do that a reimbursement boutique, analytics shop or lobbying firm alone might have found harder: combine the technical policy argument, its economic implications, stakeholder organization and the Washington campaign required to move it.

It also became a health-policy publisher

A quieter part of the McDermott+ story was its development into a significant public-facing source of health-policy information.

The McDermottPlus Check-Up began providing regular Washington health-policy summaries by 2019. The organization added the Health Policy Breakroom podcast, regulatory commentary, election and policy previews, Medicare data tools and interactive dashboards. By 2026, its website included dedicated products for Medicare data analytics, NTAP strategy, Medicare Advantage and Part D, physician and hospital payment dashboards and a premium information service called McDermott+ Insider. (McDermott+)

In April 2024, co-founder Eric Zimmerman appeared on the Health Policy Breakroom specifically to mark McDermott+'s tenth anniversary and discuss its first decade. (McDermott+)

The public-content operation mattered partly because it kept McDermott+ visible well beyond its paying clients. Hospital executives, laboratory-policy specialists, trade-association staff, Washington lawyers and reimbursement consultants routinely encountered its summaries of proposed and final CMS rules even if they were not currently working with the firm.

That makes the reported shutdown unusually conspicuous. As recently as August 7, 2026, the McDermott+ website was still publishing its weekly Check-Up, and in early August it had posted analyses of the FY 2027 inpatient final rule and other major Medicare regulations. (McDermott+)

A changing parent organization

The closure also occurs against a changed backdrop at the parent law firm.

McDermott Will & Emery merged with New York-based Schulte Roth & Zabel effective August 1, 2025, creating McDermott Will & Schulte, a firm of roughly 1,750 lawyers across more than 20 offices. McDermott brought particular strength in healthcare, while Schulte was especially known for private capital and investment-fund work. (Reuters)

There is not yet enough public information to attribute the reported McDermott+ closure to that merger or any other factor.  The parent firm continues to maintain a major healthcare practice, and several McDermott+ principals have simultaneously held roles at the law firm.

An unusual niche in Washington healthcare

McDermott+ lasted from the early years of Affordable Care Act implementation through MACRA and alternative payment models, PAMA laboratory reform, Medicare Advantage expansion, COVID-19 emergency policy, the Inflation Reduction Act and another major shift in federal health policy after the 2024 election.

Its enduring distinction was not any single one of those subjects. It was the attempt to place several professions that normally sit beside one another — health lawyers, former Hill staff, CMS and HHS veterans, reimbursement specialists, clinicians, lobbyists, economists and data analysts — inside one small organization.

For some clients, McDermott+ was essentially a Washington lobbying firm. For others, it was a Medicare reimbursement consultancy. For still others, it was a source of payment modeling, policy intelligence, coding strategy or coalition management.

And because the organization remained wholly owned by one of the country's best-known healthcare law firms, it occupied an unusual space between Big Law and K Street without being quite either one.

If the reported August 2026 shutdown proceeds as described, that hybrid organization will disappear. Much of its expertise almost certainly will not. In Washington health policy, where former agency officials, congressional staff, lawyers and consultants regularly reassemble in new combinations, the more consequential story may be where the McDermott+ people — and the functions they performed — turn up next.