You've heard about how PAMA affects different groups - big labs, small labs, physician labs, and the labs of different medical specialties.
Here, I used the assumption that PAMA pricing was pushed all the way - that tomorrow's prices were set at the actual medians found in PAMA data.
My assumption was, we'd see a normal or Gaussian distribution around the average price cut. But no. For the whole population of providers (with >$50,000 Medicare lab income), the distribution of losses is very irregular.
I divided these into four groups:
- Group 1, Winners (N=82+80)
- Group 2, Average (N=1758)
- Group 3, Losers (N=984)
- Group 4, Big Losers (N=15+123)
Four Populations, One Fee Schedule:
Reading the Fully-Phased PAMA Impact
Nov 3, 2026 · @Bruce Quinn
Introduction
Suppose PAMA's private-payer medians were applied to
Medicare lab pricing in one stroke, with no 15%-a-year phase-in and no further
congressional delays. The intuitive answer is "everyone takes about a 16%
haircut," which is the aggregate figure CMS has reported. The intuitive
answer is wrong. Line up every provider with at least $50,000 in 2026 Medicare
lab revenue (4,855 NPIs, about $5.8 billion in baseline payments), sort them by
fully-phased percent change, and you do not get a bell curve. You get two tall
peaks, a small cluster hugging zero, and a tail of providers losing 40% or
more.
The $920 million aggregate cut works out to 15.8%, almost
exactly what CMS said. But that average describes almost nobody. The histogram
is a distribution of code portfolios, and code portfolios sort by
specialty with remarkable discipline. This post walks through four groups
descriptively, then asks, as a microeconomist would, what is really going on in
each.
One housekeeping note: the rows are NPIs, not consolidated
companies. That turns out to be a feature. The same corporation can land in
three groups under three NPIs, and that tells you something.
Orientation: The Shape of the Distribution
The histogram uses fifteen four-point bins from −46% to +6%,
with edge bars catching anything beyond. Two spikes dominate. The first, at
−18% to −14%, holds 1,758 providers, over a third of the population. The
second, at −30% to −26%, holds 994, about a fifth. Between them sit three
modest bins (310, 256, 724). To the right of the main peak the counts collapse
to 71, 82, and 80 in the three bins nearest zero. To the left of the second
peak the tail runs 290, 150, 123, and finally 15. Two providers actually gain.
We carved out four clusters for discussion. They are not
exhaustive; roughly 1,800 providers fall in the connective tissue between them.
Group 1, Winners (N=162): −6% to +2%. Essentially
untouched.
Group 2, Average (N=1,758): −18% to −14%. Close to
the headline CMS number.
Group 3, Losers (N=994): −30% to −26%. Nearly double
the headline.
Group 4, Big Losers (N=138): −46% to −38%. Since the
statutory 15%-per-year phase-in compounds to only −38.6% after three years,
this group is defined by cuts that take four or more years to fully unwind.
The dollars are as lopsided as the counts, in the opposite
direction. Group 1 holds $1.1 billion in baseline, 19% of the total, but
absorbs $6 million of the cut, under 1% of the pain. Group 2 holds $2.4 billion
and absorbs $398 million, almost exactly proportional. Group 3 holds $720
million but absorbs $200 million, 22% of the pain on 12% of the dollars. Group
4 is a rounding error in aggregate, $21 million, though not to the practices
inside it.
Group 1: The Winners Did Not Bargain Best
The 162 providers nearest zero split cleanly by bin.
The 80 in the −2% to +2% bin are the proprietary molecular
diagnostics industry. Several sit at exactly 0.00%.
The adjacent 82 at −6% to −2% have a different character: 34
clinical labs, but also 29 ophthalmology and optometry practices, which is
every eye-care provider in the eligible population, nearly all at a modeled
change of −2.00% to two decimal places. That is not twenty-nine negotiations
converging. That is one code with a −2% adjustment and a specialty that bills
little else on the CLFS. This bin also holds academic reference labs (Mayo,
Washington University, Johns Hopkins) and specialty molecular firms (Exagen,
Biodesix, Interpace, Assurex) that are lightly exposed to a commoditized code
or two.
Two providers gain outright: Caris at +44% and Pacific Edge at +33%, both proprietary molecular tests. It's rare but when the private median exceeds the Medicare rate, PAMA raises the rate, and the increase carries no phase-in cap.
Group 2: Mainstream Medicine Plus the Duopoly
The main peak is the clinical mainstream. Internal medicine
(474) and family practice (247) make up 41% of the group; hematology-oncology
and medical oncology add 275; endocrinology, rheumatology, nephrology, and
cardiology add 272. These are practices running routine chemistry, hematology,
and endocrine panels.
The 354 clinical labs are where the money is. Labcorp's
North Carolina NPI ($208 million, −17.7%) and New Jersey NPI ($146 million,
−16.0%), Quest's New Jersey ($113 million, −16.5%) and Florida ($106 million,
−16.9%) entities, Unilab, Sonora Quest, and a parade of other Labcorp and Quest
state entities all land within a point or two of −16.5%. The national labs are,
by construction, the "average" cut, and I argue below that this is a
mechanism rather than a coincidence.
What is absent is as telling as what is present. Zero pain
management or anesthesiology providers. Only 28 nurse practitioners and 19
urologists out of 1,758.
Group 3: A Specialty Roster - It's Not a Random Draw
The second peak looks nothing like the first. Nurse
practitioners (197) and physician assistants (90) make up 29%. Urology
contributes 131, most of the eligible urologists. Pain management,
interventional pain, and anesthesiology contribute 192. Podiatry contributes 38
of the 41 podiatrists in the study.
The 241 clinical labs are a distinctive cohort too:
HealthTrackRx ($49 million, −27.9%), CAP Diagnostics, Sierra Genomics, Genetic
Technological Innovations, Patients Choice of Indiana, and a long list of
Texas, California, Florida, and Arizona LLCs named Lone Star Tox Screen,
RealTox, QualiTox, DrugScan, Equaltox, Dominion. Many bunch at −29% to −30%,
the group's left edge. A pathologist recognizes the toxicology and PCR-panel
sector without being told.
One corporate detail deserves a pause. A Labcorp NPI in
North Carolina sits in Group 3 at −29.2% on $9.6 million, while the Labcorp
flagship sits in Group 2 at −17.7% and a small Labcorp NPI in New York sits in
Group 1 at −5%. Quest has an Oregon NPI in Group 1 at −6%. BioReference has a
Texas NPI at 0.0% and its New Jersey flagship at −19.7%. Same company, same
contracting department, same leverage, three groups. Whatever is sorting
providers, it is not bargaining power.
Group 4: Small Dollars, One-Code Portfolios
The 138 providers losing 38% or more total only $21 million
in baseline, but they lose roughly 40 cents on the dollar. Nurse practitioners
(41), physician assistants (22), pain and interventional pain (32),
anesthesiology (16), and PM&R (9) make up 87% of the group, mostly
individual practitioners with $50,000 to $150,000 baselines in Texas, Oklahoma,
Michigan, Florida, and New Jersey.
The exceptions are a dozen clinical labs, two of them surprising: Invitae ($753,000 under this NPI, −42.9%) and Baylor Miraca Genetics ($709,000, −39.9%) are germline genetics labs, not tox shops. Potential suspects: 81412 Ashkenazy panel fell from $2448 to $1591, and 81443 pan ethnic carrier panel fell from the same $2448 to even lower new rate, $1461.
The 1,800 in Between
The unclustered providers include the biggest single losers in dollars: Aegis ($33 million, −36%) and Millennium ($21 million, −35%), just outside the Big Loser cutoff. Myriad ($34 million, −25%), Silverpath, and Genview sit just right of the Loser peak. Prince Laboratories ($61 million, −9.7%) and Reliable Results ($33 million, −9%) sit between the Average peak and the Winners. This is where the large, diversified, multi-code operators live; their position is a weighted blend of the four archetypes.
What Is Going On: A Microeconomist's Reading
PAMA sets each code's price at the volume-weighted median of
private-payer payments for that code. Specialty never enters the formula. The
specialty sorting is therefore a second-order effect: specialties run
characteristic code portfolios, and the codes face characteristically different
commercial markets. The question is why those markets differ so much.
The Winners: When You Are the Only Seller, the Median Is Your List Price
For a sole-source proprietary test, the "private-payer median" is not the output of a market. It is the output of one lab's contracting book. If the lab simply does not below its Medicare rate, and that rate was itself set by crosswalk, gapfill, or ADLT pricing at a level the lab proposed, the median comes back at exactly the Medicare rate and the change is exactly 0.0%. The Medicare rate holds for 2026; the same rate except paid by Medicare Advantage commercial plans rather than the MAC, pegs the rate for 2027.
The eye-care cluster at −2.00% is the same story in a
different key: a single dominant code, few suppliers, a commercial price that
barely moved. Ophthalmologists receive $7M in Medicare lab payments, of which $6.2M is 88361, microfluidic tear osmolarity analysis used to diagnose and evaluate dry eye disease. It's about $22 and fell 2%. It has no CMS controls (no articles or LCDs).
The Average Group: The Duopoly's Contracts Become Everyone's Price
For routine chemistry, hematology, and endocrine codes, the
volume-weighted median is dominated by Labcorp and Quest because they bill the
overwhelming majority of commercial volume. Their discounted contract rates are
the median, and the median becomes the Medicare rate. The national labs land at
the average cut almost tautologically. In a sense they wrote it.
The 1,200 physician practices in Group 2 are price-takers in
a negotiation they never attended. An internist with an in-office analyzer did
not discount CPT 80053 to Aetna; Quest did. But the internist inherits Quest's
discount through Medicare. This externality is the heart of PAMA's design.
Diversified across dozens of commodity codes, these practices get the blended
commodity result, about −16%.
The Losers: A Prisoner's Dilemma in Which Medicare Was the Prize
Toxicology, PCR infectious-disease panels, and the urine,
wound, and nail-fungus molecular codes that dominate pain, urology, podiatry,
and advanced-practice billing face a fragmented commercial market with hundreds
of small labs competing for the same specimens. Payers have managed these codes
aggressively for a decade through lab benefit managers, prior authorization,
and narrow networks.
The structure is a classic prisoner's dilemma. Each lab,
chasing network access or referral flow, discounts. Each discount is
individually rational. Collectively, the discounting drags the median down 28%
to 30%, and PAMA then imports that median into Medicare, which for many of
these labs was the best-paying customer they had. The commercial price war
destroyed the Medicare price. Nobody intended it; nobody could have prevented
it alone.
A selection effect compounds this. PAMA counts only claims
actually paid by private payers. An out-of-network tox lab that bills $800,
gets denied, and writes it off contributes nothing. The in-network labs that
accepted $120 contribute everything. The median is a median of those who
capitulated.
The practitioners in Group 3 are riding the same codes. A
pain practice billing definitive drug testing under its own NPI, or a urology
group running PCR panels in-house, has a one- or two-code CLFS portfolio. Their
result is simply the code's result.
The Big Losers: Concentration Risk
Group 4 is Group 3 without diversification. An NP with
$80,000 in Medicare lab revenue has it in one or two codes, and if those were
the codes where the commercial market collapsed most completely, the practice
gets the full cliff.
The genetics labs are the puzzle. Invitae and Baylor Miraca
at −40% or worse does not fit the tox story. Either these NPIs carry a narrow
set of panel or cytogenetic codes that high-volume competitors undercut
dramatically, or the corporate flagships sit elsewhere and these are satellites
with unrepresentative portfolios. Either way, the lesson matches the pain
practices: in a per-code median system, a concentrated portfolio is an
undiversified bet on one commercial market.
The Timing Game
We do know: Because cuts are capped at 15% per year, the difference
between a −28% lab and a −43% lab does not appear in payment until 2029 or
2030. That is three to four years in which every actor in the losing groups has
the incentive and the time to respond: migrate toward codes with smaller
adjustments, restructure which NPI bills what, shift volume to the physician
fee schedule where possible, exit the worst codes, consolidate, or lobby for
another delay. Goodhart's Law [when a measure is treated like 'the target] applies in full. The fully-phased histogram projects
what happens if everyone holds still, and in the losing groups nobody will.
Conclusion
The fully-phased PAMA distribution is not a bell curve with
a mean of −16%. It is four economic regimes on one axis. The proprietary
molecular sector controls its own median and sits at zero. Mainstream medicine
inherits the national labs' discounts and sits at the headline average. The
toxicology and PCR-panel sector, with the specialties that bill those codes,
competed its commercial prices down and now watches Medicare follow, near −28%.
A thin tail of one-code portfolios absorbs 40% or more.
The most useful fact in the data may be the corporate one:
the same company occupies three groups under three NPIs. PAMA does not sort
providers by size, leverage, or sophistication. It sorts them by code, and the
codes sort by the structure of the commercial market each lives in. That is a
very different policy from the one Congress thought it wrote in 2014, when the
premise was that Medicare overpaid for lab tests across the board. What it
built instead is a transmission line that imports each commercial sub-market's
competitive structure, monopoly and price war alike, into the Medicare fee
schedule, one code at a time.
[claude fable, output #2]
