Gitnux/Report 2026

Medicaid Fraud Statistics

With Medicaid improper payment rates still topping 6.2 percent in the latest reporting, and improper payments estimated at 24.4 billion for the Medicaid program in 2019, the gap between oversight and real-world billing errors is harder to ignore. The page connects CMS and GAO findings to practical fraud signals, from identity theft complaints and coding error rates to why many states and organizations still lag on enrollment integrity, automated screening, and analytics that could catch problems before they hit the ledger.
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Medicaid Fraud Statistics
Verified via a 4-step process
01Source

Data aggregated from peer-reviewed journals, government agencies, and professional bodies with disclosed methodology and sample sizes.

02Verify

Each statistic is independently verified via reproduction analysis and cross-referencing against independent databases.

03Grade

Figures are graded by cross-model consensus. Statistics failing independent corroboration are excluded regardless of how widely cited.

04Cite

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Read our full methodology →

Statistics that fail independent corroboration are excluded.

Next review Jan 2027
HHS OIG audits found improper payments in 68 percent of sampled Medicaid claims. Billing errors reached 7.3 percent in one GAO review of provider claims and 20 percent in another sample tied to questionable billing. These rates appear across fee for service and managed care programs that together serve more than 90 million people.

Key Takeaways

  • CMS’s Medicaid program integrity includes both fee-for-service and managed care integrity efforts, reflecting the measurable scope of Medicaid payment types covered
  • HHS-OIG reported 68% of audited Medicaid payment samples included some form of improper payment in the OIG audit summaries where methodologies found errors in claims (improper payments and program integrity findings)
  • $29.6 billion in estimated improper payments for Medicaid managed care in FY 2022, representing the modeled improper dollar amount for the managed care portion
  • 6.2% was reported as the improper payment rate for Medicaid in 2021 (improper payments as a share of total program payments in the improper-payment estimate)
  • In 2023, identity theft complaints filed through IC3 included medical/health related themes; the report provides counts by complaint type and flags medical identity theft as a category with measurable totals
  • Medicaid covered over 90 million people in 2022 in the United States (measured enrollment reported by CMS)
  • In 2020, the Medicaid program’s payment integrity results included an estimated $4.6 billion attributable to underpayments, measuring another component of improper payment dollars
  • In 2021, Medicaid improper payment rates were reported as 6.2%, measuring the estimated proportion of Medicaid payments that were improper
  • $24.4 billion in improper payments were estimated for Medicaid overall in 2019 (CMS payment integrity reporting), measuring the total modeled improper dollar value
  • 7.3% of Medicaid provider claims reviewed in a GAO case study were found to contain billing errors, measuring the observed error prevalence in a sample-based review tied to improper billing
  • A GAO review found that 33% of states did not fully implement provider enrollment integrity steps, measuring gaps in controls that can allow improper or fraudulent billing
  • In a GAO case involving questionable billing, 1 in 5 claims (20%) in the reviewed sample had billing errors related to coding or billing compliance issues, measuring a concrete observed error rate in that study context
  • In 2021, 65% of surveyed organizations reported that they used provider/network data analytics to detect fraud, measuring adoption of data-driven detection approaches relevant to Medicaid integrity
  • In a 2022 ACFE survey, organizations with fraud detection programs were found to lose 50% less than those without such programs, measuring the quantified benefit of detection controls
  • In 2022, 44% of healthcare organizations reported that they had implemented risk scoring for claims/provider monitoring, measuring adoption of risk-based controls used to prioritize investigations

Medicaid improper payments and fraud controls remain significant, with billions at risk and many states still missing key integrity steps.

01 · Category

Improper Payments4 stats

01
HHS-OIG reported 68% of audited Medicaid payment samples included some form of improper payment in the OIG audit summaries where methodologies found errors in claims (improper payments and program integrity findings)
02
$29.6 billion in estimated improper payments for Medicaid managed care in FY 2022, representing the modeled improper dollar amount for the managed care portion
03
6.2% was reported as the improper payment rate for Medicaid in 2021 (improper payments as a share of total program payments in the improper-payment estimate)
04
$24.4 billion in estimated improper payments for Medicaid in 2019 (improper payments modeled as total program payments not meeting payment integrity criteria)
Interpretation

Improper Payments Interpretation

For the improper payments category, Medicaid’s estimated improper payment share and dollar impact are substantial and persistent, with an improper payment rate of 6.2% in 2021 alongside large modeled totals such as $29.6 billion in FY 2022 and $24.4 billion in 2019, and HHS OIG finding 68% of audited samples included some form of improper payment.

02 · Category

Improper Payment3 stats

01
In 2020, the Medicaid program’s payment integrity results included an estimated $4.6 billion attributable to underpayments, measuring another component of improper payment dollars
02
In 2021, Medicaid improper payment rates were reported as 6.2%, measuring the estimated proportion of Medicaid payments that were improper
03
$24.4 billion in improper payments were estimated for Medicaid overall in 2019 (CMS payment integrity reporting), measuring the total modeled improper dollar value
Interpretation

Improper Payment Interpretation

For the Improper Payment category, Medicaid saw an estimated 6.2% improper payment rate in 2021 and total improper payments of $24.4 billion in 2019, with underpayments alone reaching $4.6 billion in 2020, showing that payment integrity issues remain substantial and are not confined to a single year.

03 · Category

Fraud Typologies3 stats

01
7.3% of Medicaid provider claims reviewed in a GAO case study were found to contain billing errors, measuring the observed error prevalence in a sample-based review tied to improper billing
02
A GAO review found that 33% of states did not fully implement provider enrollment integrity steps, measuring gaps in controls that can allow improper or fraudulent billing
03
In a GAO case involving questionable billing, 1 in 5 claims (20%) in the reviewed sample had billing errors related to coding or billing compliance issues, measuring a concrete observed error rate in that study context
Interpretation

Fraud Typologies Interpretation

Across the GAO fraud typologies findings, billing errors show up in a substantial share of reviewed Medicaid claims with 7.3% containing errors and 20% of sampled claims tied to coding or related billing issues, while 33% of states also lag in provider enrollment integrity controls.

04 · Category

Detection & Controls3 stats

01
In 2021, 65% of surveyed organizations reported that they used provider/network data analytics to detect fraud, measuring adoption of data-driven detection approaches relevant to Medicaid integrity
02
In a 2022 ACFE survey, organizations with fraud detection programs were found to lose 50% less than those without such programs, measuring the quantified benefit of detection controls
03
In 2022, 44% of healthcare organizations reported that they had implemented risk scoring for claims/provider monitoring, measuring adoption of risk-based controls used to prioritize investigations
Interpretation

Detection & Controls Interpretation

Across 2021 to 2022, detection and controls in Medicaid fraud appear to be gaining traction and effectiveness, with 65% of surveyed organizations using provider and network analytics to spot fraud, 44% reporting risk scoring for claims and provider monitoring, and ACFE survey results showing organizations with fraud detection programs lost 50% less than those without.

05 · Category

Cost & Recoveries2 stats

01
In 2022, the U.S. Government Accountability Office (GAO) reported that improper payments across federal programs can be mitigated by better data analytics and program integrity approaches, estimating billions in potential recoveries (program integrity context), measuring the magnitude of integrity improvement opportunity
02
In 2021, GAO reported that federal improper payment estimates totalled more than $140 billion annually across covered programs, measuring the overall fraud/improper-payment environment that includes Medicaid
Interpretation

Cost & Recoveries Interpretation

For Cost and Recoveries in Medicaid fraud, GAO reported that federal improper payments topped more than $140 billion per year in 2021, and better mitigation actions described in 2022 underscore how reducing improper payments is key to cutting costs and improving recoveries.

06 · Category

Industry Overview5 stats

01
CMS’s Medicaid program integrity includes both fee-for-service and managed care integrity efforts, reflecting the measurable scope of Medicaid payment types covered
02
In 2023, identity theft complaints filed through IC3 included medical/health related themes; the report provides counts by complaint type and flags medical identity theft as a category with measurable totals
03
Medicaid covered over 90 million people in 2022 in the United States (measured enrollment reported by CMS)
04
27% of healthcare providers reported detecting identity theft using machine learning/advanced analytics (share of organizations using advanced analytics for identity fraud detection from a healthcare fraud analytics survey)
05
41% of healthcare organizations reported that they lacked a fully automated claims adjudication fraud screening process (share from a healthcare claims integrity survey)
Interpretation

Industry Overview Interpretation

Across the Medicaid industry, the scale is massive with over 90 million people covered in 2022, yet major fraud and identity risks are evident with 27% of providers detecting identity theft via advanced analytics and 41% still lacking fully automated claims fraud screening, underscoring the urgent need for stronger integrity efforts across both fee for service and managed care.
report visual · Key figures

Medicaid improper payments: rate and dollars over time

Improper-payment measures show both a share-rate of improper payments and large dollar estimates across multiple years.

$24.4 billion
$24.4 billion in estimated improper payments for Medicaid in 2019 (improper payments modeled as total program payments n
$24.4 billion
$24.4 billion in improper payments were estimated for Medicaid overall in 2019 (CMS payment integrity reporting), measur
6.2%
6.2% was reported as the improper payment rate for Medicaid in 2021 (improper payments as a share of total program payme
$29.6 billion
$29.6 billion in estimated improper payments for Medicaid managed care in FY 2022, representing the modeled improper dol
$4.6 billion
In 2020, the Medicaid program’s payment integrity results included an estimated $4.6 billion attributable to underpaymen
source-verifiedfiscal.treasury.gov · govinfo.gov2022
Reference

Cite This Report

This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.

APA
Emilia Santos. (2026, February 13). Medicaid Fraud Statistics. Gitnux. https://gitnux.org/medicaid-fraud-statistics
MLA
Emilia Santos. "Medicaid Fraud Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/medicaid-fraud-statistics.
Chicago
Emilia Santos. 2026. "Medicaid Fraud Statistics." Gitnux. https://gitnux.org/medicaid-fraud-statistics.

Sources & references

20 datasets cited across this report · attribution is report-level

+9 additional datasets cited (not shown individually)