hrsa-uds · CMS
hrsa-uds · CMS
hrsa-uds · CMS
hrsa-uds · CMS
hrsa-uds · CMS
Every state runs a different experiment in who gets covered, and the country's community health centers are where you can read the result. A community health center — formally a Federally Qualified Health Center (FQHC), funded under Section 330 of the Public Health Service Act — is required to take every patient who walks in, insured or not. The Health Resources and Services Administration (HRSA) funds the program and collects an annual report from every grantee through the Uniform Data System (UDS). The 2024 UDS counts 32,387,774 patients across 1,359 awardees and 16,334 sites, broken out by what insurance, if any, each patient carries. Read those counts and a single fact governs the program — and a sharp geographic divide sits underneath it.
Two-thirds of health-center patients are uninsured or on Medicaid
In 2024, 66.2% of community-health-center patients were uninsured or covered by Medicaid — the program is the safety net's safety net. Of the 32.4 million people health centers served, 15,598,866 were enrolled in Medicaid (48.2%) and 5,857,356 were uninsured (18.1%). Together those two groups are 21,456,222 patients, against which private insurance and Medicare cover the remaining third.
| Primary coverage | Patients | Share |
|---|---|---|
| Medicaid | 15,598,866 | 48.2% |
| Uninsured | 5,857,356 | 18.1% |
| Medicaid or uninsured (safety-net) | 21,456,222 | 66.2% |
| All other (private, Medicare, etc.) | 10,931,552 | 33.8% |
Source: HRSA Uniform Data System, grant_year 2024, 1,359 awardees. Shares are computed from unrounded patient totals.
This is the defining feature of the Health Center Program. Hospitals report their uninsured exposure as uncompensated care; health centers report it as their core caseload. The two-thirds figure is not a tail risk for these organizations — it is the middle of their distribution. And it holds at the awardee level, not just in the aggregate: 1,021 of the 1,359 awardees — 75% — drew a majority of their patients from the uninsured-or-Medicaid population, and 76 of them served a panel that was majority-uninsured outright.
The coverage mix flips from one state to the next
The safety-net share is stable everywhere; its composition is not. In Texas, 33.6% of health-center patients were uninsured and 29.8% were on Medicaid; in California, 10.1% were uninsured and 72.0% were on Medicaid. Both states' centers serve a roughly two-thirds safety-net population — but the coverage backing that population is almost a mirror image.
| State | Patients | Uninsured | On Medicaid |
|---|---|---|---|
| Texas | 1,859,052 | 33.6% | 29.8% |
| California | 5,787,948 | 10.1% | 72.0% |
Source: HRSA Uniform Data System, grant_year 2024. Texas and California health-center awardees.
The absolute counts make the divide concrete. Texas health centers served 624,613 uninsured patients in 2024; California's served 582,340 — so Texas, with barely a third of California's total health-center caseload, carried more uninsured patients than California in raw numbers. A health center takes the patient in front of it. Whether that patient is recorded as Medicaid or uninsured was decided upstream, in the state's coverage rules, before they reached the clinic door.
A community health center takes the patient in front of it, insured or not. Whether that patient counts as Medicaid or uninsured is decided long before they reach the door — in the state's coverage rules, not the clinic's.
Rank every state and the two shares move in opposite directions
Across the 48 states and territories with at least 100,000 health-center patients, the uninsured share runs from 8.6% to 43.5% — a fivefold spread — and it tracks Medicaid inversely. The states where health centers report the highest uninsured share are, with few exceptions, the states where they report the lowest Medicaid share.
| State | Uninsured | On Medicaid |
|---|---|---|
| Utah | 43.5% | 18.6% |
| Texas | 33.6% | 29.8% |
| Tennessee | 32.7% | 27.8% |
| Nebraska | 32.7% | 38.5% |
| Minnesota | 31.8% | 42.8% |
| North Carolina | 29.9% | 28.8% |
| Nevada | 29.7% | 37.3% |
Source: HRSA Uniform Data System, grant_year 2024, the seven states with the highest uninsured share among those with at least 100,000 health-center patients.
The tail of the same ranking is the photographic negative. Where Medicaid is broad, the uninsured share collapses toward single digits.
| State | On Medicaid | Uninsured |
|---|---|---|
| California | 72.0% | 10.1% |
| Puerto Rico | 61.4% | 9.8% |
| Oregon | 61.1% | 8.9% |
| Connecticut | 58.4% | 15.3% |
| Wisconsin | 57.8% | 16.8% |
| Hawaii | 55.9% | 9.2% |
| Illinois | 55.5% | 19.0% |
Source: HRSA Uniform Data System, grant_year 2024, the seven states with the highest Medicaid share among those with at least 100,000 health-center patients.
Measured across all 48 geographies, the correlation between a state's uninsured share and its Medicaid share is −0.52 — a clear inverse, though not a perfect one. Utah is the instructive exception: its 43.5% uninsured share leads the country despite a Medicaid share that is far from the lowest, a reminder that local eligibility rules, enrollment practices, and the populations health centers reach all shape the mix. This study reports the descriptive pattern. It does not assign it a single cause.
The same finding, read as a workforce
Behind the coverage figures is a workforce of 152,677 full-time-equivalent employees — and the load they carry is heaviest where coverage is thinnest. The 1,359 awardees reported 152,677 total FTE, of which 51,330 were clinical, spread across 16,334 service-delivery sites. Divide the 32.4 million patients by total staffing and the program runs at roughly 212 patients per FTE.
| Footprint | 2024 |
|---|---|
| Awardees (grantees) | 1,359 |
| Service-delivery sites | 16,334 |
| Total FTE staff | 152,677 |
| Clinical FTE | 51,330 |
| Patients per FTE | 212 |
Source: HRSA Uniform Data System, grant_year 2024.
A center whose patients are mostly on Medicaid bills a payer for the visit; a center whose patients are mostly uninsured leans on its Section 330 grant and a sliding fee scale to cover the same care. The coverage mix above is therefore also a financing map: the states with the highest uninsured shares are the states where the federal grant, rather than Medicaid reimbursement, does the most work to keep the doors open.
The same patients, measured at the exam table
UDS also records how health centers perform on 14 clinical-quality measures, and the program reports them at scale: 84.2% of adult patients were screened for tobacco use and offered cessation help in 2024. These are the program's own patient-weighted rates — the share of eligible patients who received each service — aggregated across the awardees that reported the measure. This 2024 release carries no HRSA national benchmark in the national_avg field, so the figures below are reported as-is, not graded against a target.
| Clinical measure | Reported rate | Awardees reporting |
|---|---|---|
| Tobacco screening and cessation | 84.2% | 1,354 |
| Statin therapy for cardiovascular disease | 78.2% | 1,356 |
| Depression screening and follow-up | 73.7% | 1,358 |
| Cervical cancer screening | 55.4% | 1,356 |
| Colorectal cancer screening | 42.7% | 1,353 |
| Childhood immunization status | 27.5% | 887 |
Source: HRSA Uniform Data System, grant_year 2024. Patient-weighted national rate (sum of numerators over sum of denominators) across reporting awardees.
The measures with the widest reporting — tobacco, depression, and cardiovascular screening — sit highest because they are services every primary-care visit can deliver. The two lowest, colorectal-cancer screening and childhood immunization, depend on referrals, recall systems, and follow-up that are harder to sustain for a population that is uninsured or moves between coverage. Childhood immunization is also the thinnest-reported measure, with only 887 of 1,359 awardees submitting a rate. The point is not a verdict on any clinic; it is that the same coverage pressure that fills the safety net also shapes which preventive services reach the people inside it.
What one row actually is
Each row in the awardee table is one grantee's annual UDS report: its state, its patient counts by insurance, its staffing, and its site count, for a single grant year. Counting and dividing those rows is the entire method here. The data HRSA publishes is aggregate by construction — it reports how many patients an awardee served and how they were covered, never which patients — and this release carries no NPI and no facility identifier on any site row. No count or share in this study names, ranks, or scores any individual clinic, site, or patient. The unit of analysis is the program and the geography, not the person.
Methodology
All figures are aggregations over the public HRSA Uniform Data System tables — hrsa_uds_awardees (1,359 grantees), hrsa_uds_sites (16,334 sites), and hrsa_uds_quality_measures (18,046 rows across 14 clinical measures) — for grant_year = 2024, the single most recent annual reporting period in this snapshot. Snapshot release 2026-06-15; public, read-only; authority Health Resources and Services Administration (data.hrsa.gov); license US-Government-Works.
A patient is counted as safety-net if uninsured or enrolled in Medicaid. UDS reports patients by primary medical insurance, and Medicaid and uninsured are two disjoint buckets in that tally, so the safety-net total is their sum with no double-count. Every share is computed from unrounded patient totals — the sum of numerators over the sum of denominators — rather than by averaging rounded per-awardee percentages; reported Medicaid and uninsured shares may therefore not add to the combined safety-net share by a tenth of a point. State figures roll the awardee rows up by state and are shown only for the 48 states and territories with at least 100,000 health-center patients, so small-denominator noise does not lead the ranking. The inverse relationship is the Pearson correlation between each state's uninsured share and its Medicaid share across those 48 geographies. Because these are direct counts and ratios over a published aggregate table, every figure is exact as of the snapshot rather than estimated. Methodology version: community-health-center-safety-net/v1. The source-provenance contract is documented in the provenance methodology.
Limitations
- Annual, self-reported program data. Each health center compiles and submits its own UDS report; HRSA reviews submissions for completeness and consistency but the figures are program-reported counts, not an independent audit of medical records. A small number of awardees leave individual fields blank.
- Aggregate and geography-level only. Every figure is a count or share at the awardee, state, or national level. No individual clinic, site, or patient is named, ranked, or scored.
- No NPI or entity link in this release. The 2024 UDS site table carries no NPI and no CCN, so these figures cannot be joined to a specific provider, Medicare enrollment, or quality record. This study makes no provider-level claim.
- A coverage measure, not a quality or performance measure. The uninsured and Medicaid shares describe the population a center serves and the policy environment around it — not how well it delivers care. A high uninsured share is not a finding about clinic performance.
- Descriptive, not causal. The inverse relationship between uninsured and Medicaid share is a measured association across states. This study does not model why a given state's mix sits where it does, and the −0.52 correlation is imperfect — Utah is a visible exception.
- Snapshot, not a trend. Figures reflect grant_year 2024 in the 2026-06-15 snapshot. HRSA revises and extends the series; this study does not measure change over time.
- Insurance categories are point-in-time. UDS records a patient's primary insurance as reported for the year; coverage that churned during the year is not captured as a transition.
Sources
- HRSA — Uniform Data System (UDS) — the annual health-center program reports behind every figure in this study, published by the Health Resources and Services Administration.
- HRSA — Health Center Program — the Section 330 program under which Federally Qualified Health Centers are funded and required to serve all patients regardless of ability to pay.
- HRSA — UDS resources and reporting manual — HRSA's definitions for the patient, insurance, staffing, and site measures aggregated here.
The companion dataset page for HRSA UDS lists the full schema and refresh cadence, and the HRSA shortage-area data maps where this safety-net demand concentrates. This is the coverage-side companion to the rural care deserts where clinicians are scarcest and to the hospitals that give the most free care to the uninsured; for the facilities most at risk of leaving those communities without care see which rural hospitals are closest to closure, for the oversupply mirror see where Medicare providers cluster past local demand, and for who is enrolled to bill the public programs in the first place, the changing shape of Medicare enrollment.
Frequently asked questions
- What is a community health center, and what is the HRSA UDS?
- A community health center — formally a Federally Qualified Health Center, or FQHC — is a primary-care organization funded under Section 330 of the Public Health Service Act and required to serve everyone regardless of ability to pay. The Health Resources and Services Administration (HRSA) funds the program and collects an annual report from every awardee through the Uniform Data System (UDS): patient counts by insurance, staffing, sites, and clinical-quality measures. This study reads the 2024 UDS, covering 1,359 awardees, 16,334 sites, and 32,387,774 patients.
- What share of community-health-center patients are uninsured or on Medicaid?
- Two-thirds. In 2024, 66.2% of the 32.4 million people who used a community health center were either uninsured or covered by Medicaid — 48.2% on Medicaid and 18.1% uninsured. Private insurance and Medicare cover the rest. That two-thirds safety-net share is the defining feature of the program: health centers exist to be the primary-care home for people the rest of the system does not reach.
- Why is the uninsured share so much higher in Texas than in California?
- Because the coverage that backs a low-income patient is set by state policy, not by the clinic. A health center treats whoever walks in; whether that patient is recorded as Medicaid or as uninsured depends on whether the state's Medicaid program covers them. In states with broad Medicaid eligibility, most low-income health-center patients are enrolled in Medicaid and the uninsured share is low. Where eligibility is narrower, the same population shows up as uninsured. Texas centers report 33.6% of patients uninsured and 29.8% on Medicaid; California centers report 10.1% uninsured and 72.0% on Medicaid. This study reports the descriptive pattern; it does not model the cause.
- Does a high uninsured share mean a health center is failing?
- No. The uninsured share is a measure of the community a center serves, not of how well it serves them. Health centers are funded precisely to care for uninsured patients — a high uninsured share reflects local coverage policy and the population walking through the door, not clinic performance. The 76 awardees whose patient panel was majority-uninsured in 2024 are concentrated in states with narrower Medicaid eligibility.
- Does this study name any clinic, site, or patient?
- No. Every figure is a count or share at the awardee, state, or national level. The 2024 UDS release this study reads carries no NPI and no facility identifier (CCN) on any site row, so there is no individual provider to name, rank, or score. The unit of analysis is the program and the geography, never a named clinic or person.
- Is the UDS data audited or self-reported?
- Self-reported. Each health center compiles its own UDS report annually and submits it to HRSA, which reviews submissions for completeness and internal consistency. The figures are program-reported counts, not an independent audit of medical records, and a small number of measures are blank for some awardees. This study treats UDS as the authoritative program record while flagging its self-reported nature as a limitation.
- Can I reproduce these figures?
- Yes. Every number aggregates the public HRSA UDS tables (hrsa_uds_awardees, hrsa_uds_sites, hrsa_uds_quality_measures) for grant_year 2024, snapshot release 2026-06-15. The exact SQL — the national mix, the awardee-level concentration, the state flip, the Texas-versus-California pair, and the no-entity-link check — is published in the reproducibility block below. License: US-Government-Works.
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
-- Who pays at America's community health centers — the safety-net coverage
-- mix at HRSA-funded Federally Qualified Health Centers (FQHCs), 2024.
-- Fully reproducible query.
--
-- Question: of the people who use a federally funded community health center,
-- what share are uninsured or covered by Medicaid (the "safety-net" share),
-- and how does that mix vary by state? The lead finding is the STATE FLIP:
-- community health centers everywhere serve a roughly two-thirds safety-net
-- population, but in some states that shows up as uninsured patients and in
-- others as Medicaid patients. Texas: 33.6% uninsured vs 29.8% Medicaid.
-- California: 10.1% uninsured vs 72.0% Medicaid.
--
-- Sources (public.* — HRSA Uniform Data System, snapshot release 2026-06-15):
-- public.hrsa_uds_awardees -- 1,359 Health Center Program awardees
-- (grantees), grant_year = 2024. total_patients, medicaid_patients,
-- uninsured_patients, total_fte, clinical_fte, total_sites, state.
-- public.hrsa_uds_sites -- 16,334 service-delivery sites.
-- public.hrsa_uds_quality_measures -- 18,046 rows, 14 clinical measures.
-- Authority: Health Resources and Services Administration (HRSA), data.hrsa.gov.
-- Tier-1 research-only. License: US-Government-Works (17 U.S.C. Sec. 105).
-- methodology_version = 'community-health-center-safety-net/v1'.
--
-- Universe: this study reads grant_year = 2024 only — a single annual reporting
-- period, point-in-time, not a trend. UDS is annual, self-reported program
-- data; figures are aggregate at the awardee/state/national level. This
-- release carries NO NPI and NO CCN on any site row, so there is no
-- provider-identity or entity link — every number is a count or share of an
-- aggregate, and no individual awardee, site, or clinician is named.
--
-- Safety-net definition: a patient is "safety-net" if uninsured OR enrolled in
-- Medicaid. UDS reports patient counts by primary medical insurance; Medicaid
-- and uninsured are two of those categories. The two groups are disjoint in
-- the UDS primary-insurance tally, so safety_net = medicaid + uninsured.
-- ============================================================================
-- (1) NATIONAL coverage mix, 2024. Shares are computed from unrounded patient
-- totals (sum of numerators / sum of denominators), never from rounded
-- per-awardee percentages.
-- ============================================================================
SELECT
count(*) AS awardees,
sum(total_patients) AS total_patients,
sum(medicaid_patients) AS medicaid_patients,
sum(uninsured_patients) AS uninsured_patients,
sum(medicaid_patients) + sum(uninsured_patients) AS safety_net_patients,
round(100.0 * sum(medicaid_patients) / nullif(sum(total_patients),0), 1) AS medicaid_pct,
round(100.0 * sum(uninsured_patients) / nullif(sum(total_patients),0), 1) AS uninsured_pct,
round(100.0 * (sum(medicaid_patients) + sum(uninsured_patients))
/ nullif(sum(total_patients),0), 1) AS safety_net_pct
FROM public.hrsa_uds_awardees
WHERE grant_year = 2024;
-- awardees 1,359 · total_patients 32,387,774
-- medicaid 15,598,866 (48.2%) · uninsured 5,857,356 (18.1%)
-- safety_net 21,456,222 (66.2%)
-- (Medicaid and uninsured shares are rounded independently; the precise
-- combined safety-net share over unrounded totals is 66.2%.)
-- ============================================================================
-- (2) AWARDEE-LEVEL concentration. How many of the 1,359 awardees draw a
-- MAJORITY of their patients from the safety-net (uninsured + Medicaid)
-- population, and how many serve a majority-UNINSURED panel?
-- ============================================================================
SELECT
count(*) AS awardees,
count(*) FILTER (
WHERE (medicaid_patients + uninsured_patients)::numeric
/ nullif(total_patients,0) >= 0.5) AS majority_safety_net,
count(*) FILTER (
WHERE uninsured_patients::numeric
/ nullif(total_patients,0) >= 0.5) AS majority_uninsured
FROM public.hrsa_uds_awardees
WHERE grant_year = 2024;
-- awardees 1,359 · majority_safety_net 1,021 (75.1%) · majority_uninsured 76
-- ============================================================================
-- (3) STATE coverage mix — the FLIP. Ordered by uninsured share, descending.
-- Limited to states/territories with >= 100,000 health-center patients so
-- small-denominator noise does not lead the ranking. Uninsured share and
-- Medicaid share move in opposite directions across states.
-- ============================================================================
SELECT
state,
count(*) AS awardees,
sum(total_patients) AS patients,
round(100.0 * sum(uninsured_patients) / nullif(sum(total_patients),0), 1) AS uninsured_pct,
round(100.0 * sum(medicaid_patients) / nullif(sum(total_patients),0), 1) AS medicaid_pct
FROM public.hrsa_uds_awardees
WHERE grant_year = 2024
GROUP BY state
HAVING sum(total_patients) > 100000
ORDER BY uninsured_pct DESC;
-- Highest uninsured share:
-- UT 43.5% / 18.6% Medicaid · TX 33.6% / 29.8% · TN 32.7% / 27.8%
-- NE 32.7% / 38.5% · MN 31.8% / 42.8% · NC 29.9% / 28.8% · NV 29.7% / 37.3%
-- Highest Medicaid share (tail of the same ranking):
-- CA 72.0% / 10.1% uninsured · PR 61.4% / 9.8% · OR 61.1% / 8.9%
-- CT 58.4% / 15.3% · WI 57.8% / 16.8% · HI 55.9% / 9.2% · IL 55.5% / 19.0%
-- WA 55.1% / 13.5%
-- ============================================================================
-- (4) HEADLINE pair: Texas vs California, 2024. Same ~two-thirds safety-net
-- reliance, opposite coverage composition. Note the absolute count:
-- Texas's health centers serve MORE uninsured patients than California's
-- (624,613 vs 582,340) despite California serving 3x the total patients.
-- ============================================================================
SELECT
state,
sum(total_patients) AS patients,
sum(uninsured_patients) AS uninsured,
sum(medicaid_patients) AS medicaid,
round(100.0 * sum(uninsured_patients) / nullif(sum(total_patients),0), 1) AS uninsured_pct,
round(100.0 * sum(medicaid_patients) / nullif(sum(total_patients),0), 1) AS medicaid_pct
FROM public.hrsa_uds_awardees
WHERE grant_year = 2024 AND state IN ('TX','CA')
GROUP BY state;
-- CA 5,787,948 patients · 582,340 uninsured (10.1%) · 4,168,857 Medicaid (72.0%)
-- TX 1,859,052 patients · 624,613 uninsured (33.6%) · 553,082 Medicaid (29.8%)
-- ============================================================================
-- (5) SPREAD + inverse relationship across the 48 states/territories with
-- >= 100,000 patients: min/max uninsured share and the Pearson correlation
-- between a state's uninsured share and its Medicaid share.
-- ============================================================================
WITH s AS (
SELECT
state,
100.0 * sum(uninsured_patients) / nullif(sum(total_patients),0) AS u,
100.0 * sum(medicaid_patients) / nullif(sum(total_patients),0) AS m
FROM public.hrsa_uds_awardees
WHERE grant_year = 2024
GROUP BY state
HAVING sum(total_patients) > 100000
)
SELECT
count(*) AS states_over_100k,
round(min(u), 1) AS min_uninsured_pct, -- ME 8.6
round(max(u), 1) AS max_uninsured_pct, -- UT 43.5
round(corr(u, m)::numeric, 2) AS corr_uninsured_medicaid -- -0.52
FROM s;
-- states_over_100k 48 · min 8.6 (ME) · max 43.5 (UT) · corr -0.52
-- ============================================================================
-- (6) Footprint + workforce context. Sites, FTE staffing, patients per FTE.
-- ============================================================================
SELECT
(SELECT count(*) FROM public.hrsa_uds_sites WHERE grant_year = 2024) AS sites,
sum(total_sites) AS reported_sites,
round(sum(total_fte), 0) AS total_fte,
round(sum(clinical_fte), 0) AS clinical_fte,
round(sum(total_patients)::numeric / nullif(sum(total_fte),0), 0) AS patients_per_fte
FROM public.hrsa_uds_awardees
WHERE grant_year = 2024;
-- sites 16,334 · total_fte 152,677 · clinical_fte 51,330 · patients_per_fte 212
-- ============================================================================
-- (7) CLINICAL-QUALITY context — patient-weighted national rate per measure
-- (sum of numerators / sum of denominators) across reporting awardees.
-- national_avg is null for every row in this release, so no HRSA benchmark
-- comparison is possible; rates are reported as-is, not graded.
-- ============================================================================
SELECT
measure_name,
round(100.0 * sum(numerator) / nullif(sum(denominator),0), 1) AS weighted_rate_pct,
count(*) FILTER (WHERE rate IS NOT NULL) AS awardees_reporting
FROM public.hrsa_uds_quality_measures
WHERE grant_year = 2024
GROUP BY measure_name
ORDER BY weighted_rate_pct DESC NULLS LAST;
-- Tobacco screening & cessation 84.2% (1,354 awardees)
-- Statin therapy, cardiovascular 78.2% (1,356)
-- Depression screening & follow-up 73.7% (1,358)
-- Cervical cancer screening 55.4% (1,356)
-- Colorectal cancer screening 42.7% (1,353)
-- Childhood immunization status 27.5% ( 887 — thinnest-reported measure)
-- ============================================================================
-- (8) LIMITATIONS check — this release carries no provider identity. Confirm
-- that the site table holds ZERO non-null NPI and ZERO non-null CCN, so no
-- entity/provider link is possible from this data.
-- ============================================================================
SELECT
count(*) AS site_rows,
count(npi) FILTER (WHERE npi IS NOT NULL AND npi <> '') AS rows_with_npi,
count(ccn) FILTER (WHERE ccn IS NOT NULL AND ccn <> '') AS rows_with_ccn
FROM public.hrsa_uds_sites
WHERE grant_year = 2024;
-- site_rows 16,334 · rows_with_npi 0 · rows_with_ccn 0
-- (UDS in this release is aggregate program data — no NPI, no CCN, no entity
-- link. national_avg and grant_amount_usd are likewise null in this snapshot.)The snapshot
| dataset_id | hrsa-uds |
| snapshot_date | 2026-06-15 |
| sha256 | |
| doi | 10.5072/fonteum/community-health-center-safety-net-2024 |
| slsa_provenance_url |
The JOINs
period: grant_year = 2024 -- single annual UDS reporting period, 1,359 awardees
national mix: sum(medicaid)+sum(uninsured) over sum(total_patients) -- 66.2% safety-net (48.2% Medicaid + 18.1% uninsured)
shares computed from unrounded patient totals, never rounded per-awardee % -- sum of numerators / sum of denominators
state mix: GROUP BY state HAVING sum(total_patients) > 100000 -- 48 states/territories above the 100k floor
safety_net = medicaid_patients + uninsured_patients (disjoint UDS categories) -- two of the UDS primary-insurance buckets, no double-count
headline pair: state IN ('TX','CA') -- TX 33.6% uninsured / 29.8% Medicaid; CA 10.1% / 72.0%
inverse: corr(uninsured_pct, medicaid_pct) across states > 100k = -0.52 -- Pearson, 48 geographies
no entity link: hrsa_uds_sites has 0 non-null NPI and 0 non-null CCN this release -- aggregate program data only, no provider namedThe pipeline version
| git_sha | |
| slsa_provenance | |
| methodology_version | community-health-center-safety-net/v1 |
Reproduce this
Run the exact query against the frozen 2026-06-15.
Cite this study
Citation-ready for researchers and AI.
Check the chain
Each figure is snapshot-attested — re-derive the hash from the federal file.
hrsa-uds · 2026-06-15SHA-256 a3f1c9…7e6b- ACCESS · JUN 2026America's care deserts are rural: two-thirds of U.S. health-care shortage areasTwo-thirds of America's active health-care shortage areas are rural: 13,999 of the 21,133 designated Health Professional Shortage Areas — 66.2% — sit in rural communities, against 6,069 non-rural ones. The rural skew holds across primary care (66.0%), mental health (65.3%), and dental health (67.4%) alike, spanning 25,281 federal designations in 60 jurisdictions.
- FINANCIAL DISTRESS · JUN 2026Hospital charity care, by the numbers: who actually gives the most free careNonprofit hospitals — tax-exempt in exchange for community benefit — deliver charity care worth just 1.53% of their patient revenue, the lowest share of any ownership type, below for-profit hospitals (3.00%) and less than half the government rate (3.76%), across $27.68 billion in free care in the federal HCRIS cost reports.
- FINANCIAL DISTRESS · JUN 2026Rural hospital closures, by the numbers: which hospitals are most at riskRural Critical Access Hospitals — the small facilities at the center of the closure crisis — run a 50.4% financial-distress rate, against 39.2% for urban hospitals, across 6,019 Medicare hospitals in the federal HCRIS cost reports. Their average operating margin is −8.93%, and 682 are losing money on patient care.
- ACCESS · JUN 2026Where Medicare providers cluster: home health and DME market saturation, 2025In Los Angeles County, 1,847 home health agencies serve Medicare's fee-for-service population — the most of any U.S. county, at 2.12 per 1,000 beneficiaries, nearly ten times the national rate of 0.22. CMS publishes this market-saturation map for program-integrity monitoring, not as proof of fraud.
- WORKFORCE · JUN 2026Who is enrolled in Medicare? The nurse practitioner is now the most common clinician413,539 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 Research · June 15, 2026 · All figures trace to the frozen federal-data snapshot cited above.