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Lots of proposals to halt fraud in Minnesota; little consensus on best strategy
Lawmakers propose measures including a statewide inspector general, increased Attorney General staff, and automatic audits to address a $300 million Medicaid fraud scheme, officials said.
- Early in the session, the Legislature moved to advance bipartisan anti-fraud measures after committee testimony on March 9, 2026.
- Following revelations about nonprofit schemes, investigators uncovered widespread Medicaid fraud, prompting lawmakers to propose urgent reforms, prosecutors say.
- Legislative proposals detail creating a statewide inspector general and automatic audits for large providers, with actions from DHS including provider freezes and claim reviews, as part of the package.
- Pressure to show change grew as CMS moved to claw back nearly $260 million, while counties warn human-services costs are shifting onto property taxes.
- Officials warn that long-term fixes require major technology investment, with the Association of Minnesota County employees testifying that systems rely on 1989 'Oregon Trail' technology and estimating costs over $500 million.
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Pine Journal+14 Reposted by 14 other sources
Minnesota lawmakers looking at more fraud fixes, updating county technology
ST. PAUL — Lawmakers are looking at more anti-fraud measures this week, including updating decades-old county technology used to administer Medicaid and SNAP benefits. Several Association of Minnesota County employees testified Monday, March 9, before the House Ways and Means Committee, asking for an update to the 1989 technology used to administer several social service programs — frequently referred to as “Oregon Trail” technology. “We can’t s…
Star TribuneReposted by 
Chippewa Herald
Chippewa HeraldLots of proposals to halt fraud in Minnesota; little consensus on best strategy
Democrats and Republicans opened the legislative session at the state Capitol with dozens of ideas to tackle Medicaid fraud in social services programs.
·Minneapolis, United States
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Total News Sources17
Leaning Left1Leaning Right8Center4Last UpdatedBias Distribution61% Right
Bias Distribution
- 61% of the sources lean Right
61% Right
C 31%
R 61%
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