state-exclusions · CMS
state-exclusions · CMS
state-exclusions · CMS
state-exclusions · CMS
The OIG List of Excluded Individuals and Entities — the LEIE — is the federal registry that screening programs treat as the master list of providers barred from Medicare, Medicaid, and other federal health programs. But it is not the only list. Every state Medicaid agency runs its own exclusion program, on its own authority and its own clock. When the two lists disagree, the disagreement is the story: a provider barred by a state but absent from the federal file is invisible to anyone who screens federally and stops there.
This study quantifies that gap from production as observed July 14, 2026. The query joins Medicaid exclusion lists from 13 states against the federal OIG LEIE on the National Provider Identifier; the underlying state table contains 22,917 raw records.
The gap, in one number
In the July 14 observation, 64.4% of NPI-identified state-excluded providers were missing from the federal list: 3,188 of 4,949 across the 13 states carried no matching OIG LEIE record. Put the other way, the join found an OIG record for 1,761 of the 4,949.
The breakdown by state shows the pattern is not a single-state artifact. The three largest-sample states sit between 54% and 60%; the newer, smaller-sample states run higher still, and only Georgia and Montana — on very small matchable samples — come in lower.
| State | NPI-identified state-excluded | Not on federal LEIE | On both lists | Share invisible to federal screening |
|---|---|---|---|---|
| New York (OMIG) | 2,259 | 1,352 | 907 | 59.8% |
| Pennsylvania (DHS) | 973 | 568 | 405 | 58.4% |
| Ohio (ODM) | 673 | 363 | 310 | 53.9% |
| Iowa (Medicaid) | 313 | 263 | 50 | 84.0% |
| Maryland (MDH) | 264 | 222 | 42 | 84.1% |
| Washington (HCA) | 210 | 178 | 32 | 84.8% |
| North Carolina (DHHS) | 149 | 128 | 21 | 85.9% |
| Mississippi (DOM) | 138 | 106 | 32 | 76.8% |
| New Hampshire (DHHS) | 51 | 37 | 14 | 72.5% |
| North Dakota (HHS) | 47 | 28 | 19 | 59.6% |
| Montana (DPHHS) | 42 | 16 | 26 | 38.1% |
| Georgia (DCH-OIG) | 35 | 8 | 27 | 22.9% |
| Tennessee (TennCare) | 9 | 8 | 1 | 88.9% |
| All 13 states | 4,949 | 3,188 | 1,761 | 64.4% |
The denominator throughout is NPI-identified, in-force state exclusions. A state exclusion counts as in force when it carries no reinstatement date, or a reinstatement date still in the future — the same test the federal side uses. The join is on NPI only, never on name.
Why federal-only screening misses these providers
The gap is structural, not a data error. State Medicaid agencies exclude providers under state authority for Medicaid-specific reasons, and a federal exclusion does not automatically follow. The OIG may adopt a state action under its permissive §1128(b) authority — most commonly §1128(b)(4) for a state license revocation, surrender, or suspension — but that adoption is discretionary and lagged. Many state bars never cross over at all, and those that do can take months to a year to appear on the federal file.
A second mechanism is timing. An exclusion is a trailing record on both sides, but the two trailing records do not move together. A provider can be terminated from a state Medicaid program well before — or entirely without — a parallel federal action. The federal CCN- and enrollment-side machinery moves on its own cadence, a pattern we documented in the lag between a termination event and CMS deactivation.
An exclusion is only as good as the list you check. Screen the federal LEIE alone and nearly two in three NPI-identified state-barred providers come back clean.
The companion fact from the federal side reinforces the point. As we found in who actually gets barred from Medicare and why, the single largest basis on the federal LEIE is itself a downstream record of state licensing discipline — §1128(b)(4) license actions are 41% of the list. The federal file is, in large part, a lagging echo of state decisions. The state lists are where many of those decisions land first.
How the gap differs by state
New York sets the ceiling among the large-sample states: 1,352 of its 2,259 NPI-identified state-excluded providers — 59.8% — have no federal record. Pennsylvania (58.4%) and Ohio (53.9%) follow closely. These three states carry the bulk of the matchable population and agree within six points, which is what gives the pooled 64.4% figure its weight: it is not the artifact of one outlier.
The newer states ingested into the ring push the pooled figure higher. Iowa, Maryland, Washington, North Carolina, and Mississippi all sit between 77% and 86% invisible — every one a clear majority — though each rests on a smaller matchable sample than the three anchor states. The direction is consistent across every state with a meaningful denominator: a majority of NPI-identified state bars have no federal counterpart.
Georgia's 22.9% and Montana's 38.1% sit apart because their matchable samples are tiny — only 35 of Georgia's 1,369 in-force records, and 42 of Montana's 175, carry an NPI. With denominators that small, the percentages are unstable and should be read as illustrative, not as evidence that those states' providers are better represented federally.The July 14 study ring spans 13 states, from New York's 2,259 NPI-identified providers down to Tennessee's nine. It remains a loaded-coverage result, not a national estimate.
The providers with no NPI at all
In the July 14 observation, 15,487 in-force state exclusion records carried no NPI. Across the 13 states, 4,949 distinct NPIs sat inside 21,003 in-force records; the remainder named an excluded party with no identifier that maps to the federal list.
| State | In-force records | With no NPI | Distinct NPI-identified providers |
|---|---|---|---|
| New York | 8,916 | 6,640 | 2,259 |
| Pennsylvania | 4,914 | 3,714 | 973 |
| Ohio | 1,980 | 1,248 | 673 |
| Maryland | 1,605 | 1,340 | 264 |
| Georgia | 1,369 | 1,333 | 35 |
| Iowa | 1,149 | 794 | 313 |
| Washington | 244 | 34 | 210 |
| Mississippi | 193 | 53 | 138 |
| New Hampshire | 76 | 25 | 51 |
| North Dakota | 195 | 148 | 47 |
| Montana | 175 | 132 | 42 |
| North Carolina | 166 | 14 | 149 |
| Tennessee | 21 | 12 | 9 |
| All 13 states | 21,003 | 15,487 | 4,949 |
These records are excluded from the matchable denominator above, because matching them to the federal list would require a name match — and a name match is not a defensible identity assertion. We do not guess. But the practical implication is blunt: NPI-based federal screening cannot reach these parties at all, so they compound the gap rather than shrink it. The same limitation applies in reverse, and it is the reason the federal LEIE itself carries an NPI on only about one record in ten, as documented in the LEIE reference study.
What this means for screening compliance
A federal-LEIE-only screen is not a complete exclusion check, and the magnitude here puts a number on the shortfall: 64.4% of NPI-identified state-barred providers fall outside it. The OIG's own guidance is that a billing organization or contractor must screen against all applicable exclusion lists — federal and the relevant state Medicaid lists — before submitting claims or contracting, and on an ongoing basis. Billing for or contracting an excluded party in a federally billable role carries civil monetary penalty exposure under a "knew or should have known" standard.
The constructive read is that the two layers of lists do something neither does alone. The federal LEIE is national but lagging and NPI-sparse; the state lists are current and program-specific but jurisdictionally fragmented. Checked together, across frozen point-in-time snapshots, they close gaps in each other. Fonteum exposes both layers through a single NPI lookup — the state exclusion data and the federal OIG LEIE — so a "barred anywhere on the lists we hold" answer does not depend on which single list a screener happened to check. It is a screening aid: re-confirm any match against the primary source before acting. An absence becomes a no-match only when serving coverage reconciles to the latest comparable attested artifact; otherwise it is indeterminate and is not a clearance.
Methodology
Every figure is a direct join against two public, read-only Postgres tables as observed July 14, 2026: state_exclusions (22,917 raw records across 13 state Medicaid programs) and oig_leie_exclusions (the OIG monthly LEIE bulk download, release 2026-05-08, 68,055 records). The join key is the 10-digit NPI, trimmed of whitespace; a name is never used to assert a match.
A record is treated as in force when its reinstatement date is null or still in the future relative to the publish date — the same test the production exclusion lookup applies, and applied identically to both tables. The matchable denominator is the set of distinct, in-force, NPI-identified providers per state; records with no NPI are excluded from it and reported separately. The federally-invisible count is the subset of those NPIs with no row in oig_leie_exclusions. The exact SQL is in the reproducibility block below and the provenance methodology documents the source-provenance contract. Methodology version: exclusion-gap/v1.
Limitations
- Thirteen-state loaded coverage, not national coverage. The 64.4% figure describes the 13 state programs loaded in production on July 14, not all state Medicaid programs.
- NPI is the floor, not the ceiling. 15,487 in-force state records carry no NPI and cannot be matched to the federal list by identifier; they are reported separately, never guessed at by name.
- Snapshot, not cumulative. Both lists are point-in-time. These figures reflect production as observed July 14, 2026.
- Some states are small samples. Tennessee, Georgia, and Montana carry only 9, 35, and 42 NPI-identified records, so their per-state shares are illustrative, not stable; the newer mid-size states rest on smaller denominators than the three anchor states.
- A compliance signal, aggregate-only. Exclusion counts are an enforcement and screening signal, never a measure of care quality. No individual excluded party is named, surfaced, or attached to any provider profile in this study.
Sources
- OIG LEIE — online database and monthly downloads — the federal exclusion list and the comparison anchor.
- OIG — effect of an exclusion (screening duty, civil monetary penalties) — the obligation to screen all applicable lists.
- New York OMIG — Medicaid exclusions — the New York state source.
- Ohio Department of Medicaid — provider exclusion and suspension list — the Ohio state source.
- Georgia DCH — Office of Inspector General — the Georgia state source.
- Pennsylvania DHS — sanctioned providers — the Pennsylvania state source.
- Fonteum — state Medicaid exclusion data, loaded coverage — 22,917 raw records across 13 states in the July 14 production observation.
- 42 U.S.C. § 1320a-7 (Social Security Act § 1128) — the federal exclusion statute, including the permissive §1128(b)(4) license-action authority.
Frequently asked questions
- What is the federal–state exclusion gap?
- It is the share of providers excluded by a state Medicaid program that carry no matching record on the federal OIG List of Excluded Individuals and Entities (LEIE). In the July 14, 2026 production observation, 3,188 of 4,949 NPI-identified state-excluded providers — 64.4% — were absent from the federal list.
- Why would a provider be excluded by a state but not by the federal OIG?
- State Medicaid agencies run their own exclusion programs and act on their own authority and timeline. A state can bar a provider for a Medicaid-specific reason — a state license action, a state fraud referral, an administrative termination — without an OIG exclusion ever following. The OIG can adopt many of these under its permissive §1128(b) authority, but adoption is discretionary and lagged, so a large standing set of state bars never reaches the federal list.
- How many state-excluded providers does federal-only screening miss?
- Among providers with an NPI in the July 14, 2026 13-state production observation, 3,188 of 4,949 — 64.4% — had no OIG LEIE record. New York accounted for 1,352 of them, Pennsylvania 568, and Ohio 363.
- Does the gap change if you count federal exclusions that were later reinstated?
- No. The OIG removes reinstated parties from the published LEIE, so the federal file is already a current-active snapshot. The 64.4% figure is identical whether or not an in-force filter is applied on the federal side.
- What about state exclusions with no NPI?
- A further 15,487 in-force state exclusion records carry no NPI at all. They cannot be matched to the federal list by identifier, so NPI-based federal screening cannot reach them either. They are excluded from the matchable denominator and reported separately rather than guessed at by name.
- Which states are included, and why not all 50?
- The July 14, 2026 observation includes New York, Ohio, Georgia, Pennsylvania, North Carolina, Maryland, Washington, Iowa, Mississippi, Montana, New Hampshire, North Dakota, and Tennessee. Production contains 22,917 raw records across those 13 states.
- Can I reproduce these numbers?
- Yes. Every figure is a direct join between the public state_exclusions and oig_leie_exclusions tables on NPI. The exact SQL is published in the reproducibility block below; each count resolves to specific rows in specific frozen snapshots, and no match is ever inferred from a name.
Who uses this data
The source data behind this study is public
Compliance teams, journalists, and researchers work from the same federal source families cited above — queried by NPI or facility identifier through Fonteum’s open dataset pages and API. Every figure traces to a frozen, downloadable snapshot you can reproduce yourself.
Datasets used
Reproducibility
Every claim, reproducible
The SQL
-- The federal–state exclusion gap — fully reproducible query.
--
-- Question: how many providers excluded by a STATE Medicaid program are
-- invisible to FEDERAL-only screening — i.e. carry no record on the OIG LEIE?
--
-- Sources:
-- public.state_exclusions — State Medicaid exclusion lists (13 loaded
-- states as observed 2026-07-14).
-- Public, read-only.
-- public.oig_leie_exclusions — OIG List of Excluded Individuals/Entities,
-- federal monthly bulk download, release
-- 2026-05-08, 68,055 active records (7,025 with
-- an NPI). Public, read-only.
--
-- Join key: NPI only (10-digit, btrim). We never match on name — a name match
-- is not a defensible identity assertion, so rows with no NPI are excluded from
-- the matchable denominator and reported separately (see no-NPI query below).
--
-- "In force" mirrors the production exclusion lookup (src/lib/exclusions): a row
-- is in force when reinstatement_date IS NULL OR reinstatement_date > today.
-- Applied to BOTH tables. Audit date basis: DATE '2026-07-14'.
--
-- Every headline figure in the study resolves to one of the rows below.
-- audit-claim: federal-gap-vector
WITH se_inforce AS (
SELECT state,
nullif(btrim(npi), '') AS npi
FROM public.state_exclusions
WHERE reinstatement_date IS NULL OR reinstatement_date > DATE '2026-07-14'
),
fed_inforce AS (
-- Distinct federal NPIs in force. (The LEIE drops reinstated parties from the
-- published file, so this set equals "any LEIE row by NPI" — the 64.4% gap is
-- identical whether or not the in-force filter is applied on the federal side.)
SELECT DISTINCT btrim(npi) AS npi
FROM public.oig_leie_exclusions
WHERE nullif(btrim(npi), '') IS NOT NULL
AND (reinstatement_date IS NULL OR reinstatement_date > DATE '2026-07-14')
),
state_npi AS ( -- distinct NPI-identified, in-force provider per state
SELECT DISTINCT state, npi FROM se_inforce WHERE npi IS NOT NULL
),
per_state AS (
SELECT s.state,
count(*) AS matchable_providers,
count(*) FILTER (WHERE f.npi IS NULL) AS federally_invisible
FROM state_npi s
LEFT JOIN fed_inforce f USING (npi)
GROUP BY s.state
),
overall_npi AS ( SELECT DISTINCT npi FROM se_inforce WHERE npi IS NOT NULL ),
overall AS (
SELECT 'ALL'::text AS state,
count(*) AS matchable_providers,
count(*) FILTER (WHERE f.npi IS NULL) AS federally_invisible
FROM overall_npi o
LEFT JOIN fed_inforce f USING (npi)
),
u AS ( SELECT * FROM per_state UNION ALL SELECT * FROM overall )
SELECT
state,
matchable_providers, -- NPI-identified denominator
federally_invisible, -- NOT on the federal LEIE
(matchable_providers - federally_invisible) AS on_federal_too, -- caught by both
round(100.0 * federally_invisible / nullif(matchable_providers, 0), 1)
AS pct_invisible
FROM u
ORDER BY state;
-- state matchable invisible on_federal_too pct_invisible
-- ALL 4,949 3,188 1,761 64.4
-- NY 2,259 1,352 907 59.8
-- PA 973 568 405 58.4
-- OH 673 363 310 53.9
-- IA 313 263 50 84.0
-- MD 264 222 42 84.1
-- WA 210 178 32 84.8
-- NC 149 128 21 85.9
-- MS 138 106 32 76.8
-- NH 51 37 14 72.5
-- ND 47 28 19 59.6
-- MT 42 16 26 38.1 (small sample — see study)
-- GA 35 8 27 22.9 (small sample — see study)
-- TN 9 8 1 88.9 (small sample — see study)
-- Rows with NO NPI — excluded from the matchable denominator above and reported
-- separately. These in-force state exclusions cannot be matched to the federal
-- list by identifier at all, so federal NPI-based screening cannot reach them.
-- audit-claim: state-record-vector
SELECT
coalesce(state, 'ALL') AS state,
count(*) FILTER (WHERE inforce) AS inforce_rows,
count(*) FILTER (WHERE inforce AND npi IS NULL) AS inforce_no_npi_rows,
count(DISTINCT npi) FILTER (WHERE inforce AND npi IS NOT NULL) AS inforce_distinct_npi
FROM (
SELECT state,
nullif(btrim(npi), '') AS npi,
(reinstatement_date IS NULL OR reinstatement_date > DATE '2026-07-14') AS inforce
FROM public.state_exclusions
) se
GROUP BY ROLLUP (state)
ORDER BY state NULLS LAST;
-- state inforce_rows inforce_no_npi_rows inforce_distinct_npi
-- NY 8,916 6,640 2,259
-- PA 4,914 3,714 973
-- OH 1,980 1,248 673
-- MD 1,605 1,340 264
-- GA 1,369 1,333 35
-- IA 1,149 794 313
-- WA 244 34 210
-- MS 193 53 138
-- NH 76 25 51
-- ND 195 148 47
-- MT 175 132 42
-- NC 166 14 149
-- TN 21 12 9
-- ALL 21,003 15,487 4,949
-- Raw source universes. These totals are deliberately separate from the
-- in-force, NPI-identified denominator above.
-- audit-claim: source-universes
SELECT
(SELECT count(*) FROM public.state_exclusions) AS state_rows,
(SELECT count(DISTINCT state) FROM public.state_exclusions) AS states,
(SELECT count(*) FROM public.oig_leie_exclusions) AS leie_rows,
(SELECT count(*) FROM public.oig_leie_exclusions
WHERE nullif(btrim(npi), '') IS NOT NULL) AS leie_rows_with_npi;
-- state_rows 22,917 · states 13 · leie_rows 68,055 · leie_rows_with_npi 7,025The snapshot
| dataset_id | state-exclusions |
| snapshot_date | 2026-07-14 |
The JOINs
join key: state_exclusions.npi = oig_leie_exclusions.npi -- 10-digit NPI, btrim, never a name match in_force = reinstatement_date IS NULL OR reinstatement_date > DATE '2026-07-14' -- applied to both tables matchable = distinct in-force state NPI (non-empty); rows with no NPI excluded and reported separately federally_invisible = matchable NPI with NO row in oig_leie_exclusions on the same NPI share = federally_invisible / matchable -- 3,188 / 4,949 = 64.4%
The pipeline version
| methodology_version | exclusion-gap/v1 |
Reproduce this
Run the exact query against the frozen 2026-07-14.
Cite this study
Citation-ready for researchers and AI.
Check the chain
The cited snapshot identifies the federal file. Where an attestation is present, its file hash can be re-derived; figures are not individually signed.
state-exclusions · 2026-07-14Not suppliedInspect supplied artifact- FINANCIAL DISTRESS · JUN 2026Medicaid Exclusion List Blind Spots: State Bars the Feds MissOf 4,949 providers with an active state Medicaid exclusion across the 13 state programs Fonteum ingests, 3,188 — 64.4% — have no record on the federal OIG LEIE. Adding the SAM.gov debarment list recovers only 191: 2,997 stay invisible to both federal lists. And 198 are barred across two or more states at once.
- FINANCIAL DISTRESS · JUN 2026The OIG exclusion list, explained: who gets barred from Medicare, and whyThe OIG List of Excluded Individuals and Entities (LEIE) holds 68,055 active exclusions spanning 1977–2026. The most common reason to be barred from Medicare is not fraud — it is losing a state license: §1128(b)(4) license actions are 41% of the list. And only 10.3% of records carry an NPI, so the list is mostly non-clinicians.
- ACCESS · APR 2026A March spike in Medicare enrollment deactivations thinned provider supply in shortage areasMedicare enrollment deactivations in PECOS ran 28% above the trailing-twelve-month average in March 2026 — and the spike was not uniform. Deactivations in HRSA-designated shortage areas grew 41% against trend, versus 19% elsewhere. The places least able to absorb a departure lost providers fastest.
- CARE QUALITY · JUN 2026Nursing Home Survey Results: How Fast Deficiencies Get FixedAcross 410,723 corrected CMS nursing home health deficiencies, the mean time from survey to documented correction is 32.4 days — but the harm-level citations, Severity G and above, close faster, in 28.5 days. The more severe the finding, the quicker the fix. Texas and Illinois correct in about two weeks; Washington, D.C. takes nine.
- WORKFORCE · JUN 2026PECOS Lookup: Who Is Enrolled in Medicare? (2026 Data)413,539 nurse practitioner enrollments make NPs the single most common clinician type in Medicare's provider-enrollment file — 13.9% of all 2.98 million PECOS records, nearly triple the largest physician specialty. Together, NPs and physician assistants are one in five enrollments. Advanced-practice providers now anchor the Medicare workforce.
Federal source citations
Fonteum LLC · June 15, 2026 · All figures trace to the frozen federal-data snapshot cited above.