{
  "study": {
    "slug": "community-health-center-safety-net-2024",
    "title": "Where the uninsured land: coverage at America's community health centers, 2024",
    "standfirst": "66.2% of the 32.4 million patients at America's community health centers were uninsured or on Medicaid in 2024. But the mix flips by state: Texas centers reported 33.6% of patients uninsured against 29.8% on Medicaid; California centers, 10.1% uninsured and 72.0% on Medicaid.",
    "desk": "access",
    "article_type": "Original Research",
    "published": "2026-06-15",
    "issue": 74,
    "doi": "10.5072/fonteum/community-health-center-safety-net-2024",
    "url": "https://fonteum.com/research/community-health-center-safety-net-2024",
    "methodology_version": "community-health-center-safety-net/v1"
  },
  "data_as_of": "2026-06-15",
  "datasets": [
    {
      "slug": "hrsa-uds",
      "name": "HRSA UDS",
      "publisher": "HRSA — Uniform Data System",
      "upstream_url": null
    }
  ],
  "key_findings": [
    {
      "number": "66.2%",
      "finding": "of the 32,387,774 patients community health centers served in 2024 were uninsured or covered by Medicaid — 15.6 million on Medicaid (48.2%) and 5.86 million uninsured (18.1%). The HRSA Health Center Program is the safety net's safety net",
      "dataset": "hrsa-uds"
    },
    {
      "number": "33.6% vs 10.1%",
      "finding": "the uninsured share of community-health-center patients in Texas versus California in 2024. Both states' centers serve a roughly two-thirds safety-net population — but in Texas the coverage gap shows up as uninsured patients, in California as Medicaid",
      "dataset": "hrsa-uds"
    },
    {
      "number": "8.6%–43.5%",
      "finding": "range of the uninsured patient share across the 48 states and territories with at least 100,000 health-center patients — Maine lowest, Utah highest, a fivefold spread. Uninsured share and Medicaid share move in opposite directions (correlation −0.52)",
      "dataset": "hrsa-uds"
    },
    {
      "number": "1,021 of 1,359",
      "finding": "Health Center Program awardees — 75% — drew a majority of their patients from the uninsured-or-Medicaid population in 2024; 76 awardees served a majority-uninsured panel",
      "dataset": "hrsa-uds"
    },
    {
      "number": "16,334",
      "finding": "service-delivery sites operated by 1,359 awardees, staffed by 152,677 full-time-equivalent employees (51,330 of them clinical) — about 212 patients per FTE. This UDS release carries no NPI and no facility identifier, so figures are aggregate only",
      "dataset": "hrsa-uds"
    }
  ],
  "faqs": [
    {
      "q": "What is a community health center, and what is the HRSA UDS?",
      "a": "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."
    },
    {
      "q": "What share of community-health-center patients are uninsured or on Medicaid?",
      "a": "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."
    },
    {
      "q": "Why is the uninsured share so much higher in Texas than in California?",
      "a": "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."
    },
    {
      "q": "Does a high uninsured share mean a health center is failing?",
      "a": "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."
    },
    {
      "q": "Does this study name any clinic, site, or patient?",
      "a": "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."
    },
    {
      "q": "Is the UDS data audited or self-reported?",
      "a": "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."
    },
    {
      "q": "Can I reproduce these figures?",
      "a": "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."
    }
  ],
  "citation": {
    "apa": "Fonteum Research. (2026, June 15). Where the uninsured land: coverage at America's community health centers, 2024. Fonteum Research, Issue 74. https://doi.org/10.5072/fonteum/community-health-center-safety-net-2024",
    "url": "https://fonteum.com/research/community-health-center-safety-net-2024"
  },
  "reproducible_sql": "-- Who pays at America's community health centers — the safety-net coverage\n-- mix at HRSA-funded Federally Qualified Health Centers (FQHCs), 2024.\n-- Fully reproducible query.\n--\n-- Question: of the people who use a federally funded community health center,\n-- what share are uninsured or covered by Medicaid (the \"safety-net\" share),\n-- and how does that mix vary by state? The lead finding is the STATE FLIP:\n-- community health centers everywhere serve a roughly two-thirds safety-net\n-- population, but in some states that shows up as uninsured patients and in\n-- others as Medicaid patients. Texas: 33.6% uninsured vs 29.8% Medicaid.\n-- California: 10.1% uninsured vs 72.0% Medicaid.\n--\n-- Sources (public.* — HRSA Uniform Data System, snapshot release 2026-06-15):\n--   public.hrsa_uds_awardees           -- 1,359 Health Center Program awardees\n--     (grantees), grant_year = 2024. total_patients, medicaid_patients,\n--     uninsured_patients, total_fte, clinical_fte, total_sites, state.\n--   public.hrsa_uds_sites              -- 16,334 service-delivery sites.\n--   public.hrsa_uds_quality_measures   -- 18,046 rows, 14 clinical measures.\n--   Authority: Health Resources and Services Administration (HRSA), data.hrsa.gov.\n--   Tier-1 research-only. License: US-Government-Works (17 U.S.C. Sec. 105).\n--   methodology_version = 'community-health-center-safety-net/v1'.\n--\n-- Universe: this study reads grant_year = 2024 only — a single annual reporting\n--   period, point-in-time, not a trend. UDS is annual, self-reported program\n--   data; figures are aggregate at the awardee/state/national level. This\n--   release carries NO NPI and NO CCN on any site row, so there is no\n--   provider-identity or entity link — every number is a count or share of an\n--   aggregate, and no individual awardee, site, or clinician is named.\n--\n-- Safety-net definition: a patient is \"safety-net\" if uninsured OR enrolled in\n--   Medicaid. UDS reports patient counts by primary medical insurance; Medicaid\n--   and uninsured are two of those categories. The two groups are disjoint in\n--   the UDS primary-insurance tally, so safety_net = medicaid + uninsured.\n\n-- ============================================================================\n-- (1) NATIONAL coverage mix, 2024. Shares are computed from unrounded patient\n--     totals (sum of numerators / sum of denominators), never from rounded\n--     per-awardee percentages.\n-- ============================================================================\nSELECT\n  count(*)                                                              AS awardees,\n  sum(total_patients)                                                  AS total_patients,\n  sum(medicaid_patients)                                               AS medicaid_patients,\n  sum(uninsured_patients)                                              AS uninsured_patients,\n  sum(medicaid_patients) + sum(uninsured_patients)                     AS safety_net_patients,\n  round(100.0 * sum(medicaid_patients)  / nullif(sum(total_patients),0), 1) AS medicaid_pct,\n  round(100.0 * sum(uninsured_patients) / nullif(sum(total_patients),0), 1) AS uninsured_pct,\n  round(100.0 * (sum(medicaid_patients) + sum(uninsured_patients))\n        / nullif(sum(total_patients),0), 1)                            AS safety_net_pct\nFROM public.hrsa_uds_awardees\nWHERE grant_year = 2024;\n--  awardees 1,359 · total_patients 32,387,774\n--  medicaid 15,598,866 (48.2%) · uninsured 5,857,356 (18.1%)\n--  safety_net 21,456,222 (66.2%)\n--  (Medicaid and uninsured shares are rounded independently; the precise\n--   combined safety-net share over unrounded totals is 66.2%.)\n\n-- ============================================================================\n-- (2) AWARDEE-LEVEL concentration. How many of the 1,359 awardees draw a\n--     MAJORITY of their patients from the safety-net (uninsured + Medicaid)\n--     population, and how many serve a majority-UNINSURED panel?\n-- ============================================================================\nSELECT\n  count(*)                                                             AS awardees,\n  count(*) FILTER (\n    WHERE (medicaid_patients + uninsured_patients)::numeric\n          / nullif(total_patients,0) >= 0.5)                           AS majority_safety_net,\n  count(*) FILTER (\n    WHERE uninsured_patients::numeric\n          / nullif(total_patients,0) >= 0.5)                           AS majority_uninsured\nFROM public.hrsa_uds_awardees\nWHERE grant_year = 2024;\n--  awardees 1,359 · majority_safety_net 1,021 (75.1%) · majority_uninsured 76\n\n-- ============================================================================\n-- (3) STATE coverage mix — the FLIP. Ordered by uninsured share, descending.\n--     Limited to states/territories with >= 100,000 health-center patients so\n--     small-denominator noise does not lead the ranking. Uninsured share and\n--     Medicaid share move in opposite directions across states.\n-- ============================================================================\nSELECT\n  state,\n  count(*)                                                             AS awardees,\n  sum(total_patients)                                                  AS patients,\n  round(100.0 * sum(uninsured_patients) / nullif(sum(total_patients),0), 1) AS uninsured_pct,\n  round(100.0 * sum(medicaid_patients)  / nullif(sum(total_patients),0), 1) AS medicaid_pct\nFROM public.hrsa_uds_awardees\nWHERE grant_year = 2024\nGROUP BY state\nHAVING sum(total_patients) > 100000\nORDER BY uninsured_pct DESC;\n--  Highest uninsured share:\n--    UT 43.5% / 18.6% Medicaid · TX 33.6% / 29.8% · TN 32.7% / 27.8%\n--    NE 32.7% / 38.5% · MN 31.8% / 42.8% · NC 29.9% / 28.8% · NV 29.7% / 37.3%\n--  Highest Medicaid share (tail of the same ranking):\n--    CA 72.0% / 10.1% uninsured · PR 61.4% / 9.8% · OR 61.1% / 8.9%\n--    CT 58.4% / 15.3% · WI 57.8% / 16.8% · HI 55.9% / 9.2% · IL 55.5% / 19.0%\n--    WA 55.1% / 13.5%\n\n-- ============================================================================\n-- (4) HEADLINE pair: Texas vs California, 2024. Same ~two-thirds safety-net\n--     reliance, opposite coverage composition. Note the absolute count:\n--     Texas's health centers serve MORE uninsured patients than California's\n--     (624,613 vs 582,340) despite California serving 3x the total patients.\n-- ============================================================================\nSELECT\n  state,\n  sum(total_patients)                                                  AS patients,\n  sum(uninsured_patients)                                              AS uninsured,\n  sum(medicaid_patients)                                               AS medicaid,\n  round(100.0 * sum(uninsured_patients) / nullif(sum(total_patients),0), 1) AS uninsured_pct,\n  round(100.0 * sum(medicaid_patients)  / nullif(sum(total_patients),0), 1) AS medicaid_pct\nFROM public.hrsa_uds_awardees\nWHERE grant_year = 2024 AND state IN ('TX','CA')\nGROUP BY state;\n--  CA 5,787,948 patients · 582,340 uninsured (10.1%) · 4,168,857 Medicaid (72.0%)\n--  TX 1,859,052 patients · 624,613 uninsured (33.6%) ·   553,082 Medicaid (29.8%)\n\n-- ============================================================================\n-- (5) SPREAD + inverse relationship across the 48 states/territories with\n--     >= 100,000 patients: min/max uninsured share and the Pearson correlation\n--     between a state's uninsured share and its Medicaid share.\n-- ============================================================================\nWITH s AS (\n  SELECT\n    state,\n    100.0 * sum(uninsured_patients) / nullif(sum(total_patients),0) AS u,\n    100.0 * sum(medicaid_patients)  / nullif(sum(total_patients),0) AS m\n  FROM public.hrsa_uds_awardees\n  WHERE grant_year = 2024\n  GROUP BY state\n  HAVING sum(total_patients) > 100000\n)\nSELECT\n  count(*)                       AS states_over_100k,\n  round(min(u), 1)               AS min_uninsured_pct,   -- ME 8.6\n  round(max(u), 1)               AS max_uninsured_pct,   -- UT 43.5\n  round(corr(u, m)::numeric, 2)  AS corr_uninsured_medicaid  -- -0.52\nFROM s;\n--  states_over_100k 48 · min 8.6 (ME) · max 43.5 (UT) · corr -0.52\n\n-- ============================================================================\n-- (6) Footprint + workforce context. Sites, FTE staffing, patients per FTE.\n-- ============================================================================\nSELECT\n  (SELECT count(*) FROM public.hrsa_uds_sites WHERE grant_year = 2024)  AS sites,\n  sum(total_sites)                                                     AS reported_sites,\n  round(sum(total_fte), 0)                                             AS total_fte,\n  round(sum(clinical_fte), 0)                                          AS clinical_fte,\n  round(sum(total_patients)::numeric / nullif(sum(total_fte),0), 0)    AS patients_per_fte\nFROM public.hrsa_uds_awardees\nWHERE grant_year = 2024;\n--  sites 16,334 · total_fte 152,677 · clinical_fte 51,330 · patients_per_fte 212\n\n-- ============================================================================\n-- (7) CLINICAL-QUALITY context — patient-weighted national rate per measure\n--     (sum of numerators / sum of denominators) across reporting awardees.\n--     national_avg is null for every row in this release, so no HRSA benchmark\n--     comparison is possible; rates are reported as-is, not graded.\n-- ============================================================================\nSELECT\n  measure_name,\n  round(100.0 * sum(numerator) / nullif(sum(denominator),0), 1)         AS weighted_rate_pct,\n  count(*) FILTER (WHERE rate IS NOT NULL)                              AS awardees_reporting\nFROM public.hrsa_uds_quality_measures\nWHERE grant_year = 2024\nGROUP BY measure_name\nORDER BY weighted_rate_pct DESC NULLS LAST;\n--  Tobacco screening & cessation        84.2% (1,354 awardees)\n--  Statin therapy, cardiovascular       78.2% (1,356)\n--  Depression screening & follow-up     73.7% (1,358)\n--  Cervical cancer screening            55.4% (1,356)\n--  Colorectal cancer screening          42.7% (1,353)\n--  Childhood immunization status        27.5% (  887 — thinnest-reported measure)\n\n-- ============================================================================\n-- (8) LIMITATIONS check — this release carries no provider identity. Confirm\n--     that the site table holds ZERO non-null NPI and ZERO non-null CCN, so no\n--     entity/provider link is possible from this data.\n-- ============================================================================\nSELECT\n  count(*)                                                             AS site_rows,\n  count(npi) FILTER (WHERE npi IS NOT NULL AND npi <> '')              AS rows_with_npi,\n  count(ccn) FILTER (WHERE ccn IS NOT NULL AND ccn <> '')              AS rows_with_ccn\nFROM public.hrsa_uds_sites\nWHERE grant_year = 2024;\n--  site_rows 16,334 · rows_with_npi 0 · rows_with_ccn 0\n--  (UDS in this release is aggregate program data — no NPI, no CCN, no entity\n--   link. national_avg and grant_amount_usd are likewise null in this snapshot.)",
  "license": "U.S. Government Works (federal sources; 17 U.S.C. §105)",
  "generated_by": "Fonteum — https://fonteum.com",
  "notes": "Aggregate, source-traced figures frozen to the snapshot above. Reproduce by running reproducible_sql against the cited federal dataset; no per-entity records are included."
}