Medicare/Medicaid Fraud Crackdown

We see you, we hear you and what you do affects us all

🚨 Medicare Fraud Crackdown: What You Need to Know

In a sweeping move, CMS (Centers for Medicare & Medicaid Services) announced a major initiative to combat Medicare fraud, following the revelation of a $14.6 billion nationwide takedown. Dr. Mehmet Oz, the new CMS Administrator, is pushing for an aggressive modernization of oversight systems, framing this as a necessary response to increasingly sophisticated fraud networks—especially those allegedly backed by foreign actors.

🛠️ “Modern Tools” for a Digital Arms Race

Dr. Oz emphasized that traditional fraud detection isn’t enough anymore. CMS is now embracing:

• AI-powered fraud detection that flags suspicious billing in real time

• Behavioral analytics to identify high-risk services and provider patterns

• Cybersecurity war rooms, modeled after DOJ’s new "healthcare data fusion center"

“There are modern tools being used to attack us, and we need even more modern ways, including AI... The oversight has to be unrelenting.” — Dr. Oz

📅 What's Rolling Out and When

• January 1, 2026: The new WISeR model (Wasteful and Inappropriate Services Reduction) launches in six states: Arizona, New Jersey, Ohio, Oklahoma, Texas, and Washington.

• Ongoing: CMS is already using a Fraud Prevention System that processes 15 million Medicare claims daily and recommends denials based on risk scoring.

• Potential Expansion: If successful, the program could be applied to Medicaid and other federal programs.

🎯 Who’s Likely to Be Targeted?

This initiative doesn’t name individuals—it targets behaviors, procedures, and patterns:

• Medical services under scrutiny include:

  • Skin and tissue substitutes

  • Electrical nerve stimulator implants

  • Arthroscopic knee surgeries for osteoarthritis

• Risk profiles may include:

  • High-volume billers of flagged procedures

  • Providers with unusual geographic or billing patterns

  • Clinics or practitioners deviating from “clinical norms”

Patients receiving these services could experience delays, denials, or increased documentation requests—even if care is legitimate.

🔍 Public Transparency: What We’ll Actually See

While CMS has released some public information on its AI and fraud strategy (see ai.cms.gov), full transparency remains limited:

• Algorithms and decision criteria are not publicly disclosed

• CMS claims final decisions will still involve human clinicians

• “Gold Card” exemptions may apply to compliant providers—but qualifying criteria remain vague

The public is encouraged to report fraud, which subtly shifts enforcement pressure onto everyday citizens and providers, a move some critics see as a tactic to blur accountability.

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🧠 Why This Matters

This isn't just about rooting out fraud—it’s about the rising influence of algorithmic oversight in healthcare. As modern tools tighten their grip on billing behaviors, the boundaries between protection and surveillance are becoming increasingly thin.

People need to know what to look for:

• Unusual delays in services

• New pre-authorization requirements

• Shifts in what Medicare will or won’t cover

• Requests to “self-report” on others

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🧩 What Else Is Happening Behind the Scenes

1. Private Tech Firms Are Now Gatekeepers

The WISeR model is the first CMS initiative where private technology companies—not healthcare providers—are the official participants. These firms will:

• Use AI to assess whether services meet Medicare’s coverage rules

• Be financially rewarded based on how much “waste” they prevent

• Employ licensed clinicians to make final determinations—but the tech does the heavy lifting

This means corporate algorithms are now shaping access to care, even if CMS insists that coverage policies haven’t changed.

2. “Gold Card” Exemptions Could Create Two Tiers of Providers

Providers with a strong compliance record may eventually be exempt from these reviews. But:

• The criteria for exemption are vague

• It could create a two-tiered system: one for “trusted” providers, and one under constant scrutiny

• Smaller or under-resourced clinics may struggle to meet the exemption threshold

3. Patients May Not Know Why They’re Denied

Even though CMS says decisions will be made by clinicians, the algorithms that flag claims are not transparent. Patients might:

• Be denied care without understanding the rationale

• Face delays due to prior authorization bottlenecks

• Be caught in appeals processes with little recourse

4. This Doesn’t Apply to Medicare Advantage—Yet

WISeR only affects Original Medicare, not Medicare Advantage plans. But:

• CMS has hinted that similar tech-driven oversight could expand

• Medicare Advantage already uses prior authorization extensively, so this could normalize even more automation across the board

Meanwhile back at the ranch

While Dr. Oz and CMS are publicly pledging to protect “those in the twilight of life” and “those in the shadows,” the One Big Beautiful Bill Act (OBBBA)—a rebranded version of the Build Back Better Act—is poised to do the opposite for millions of those very people.

🧨 What the OBBBA Actually Does

According to the Congressional Budget Office and multiple policy analyses:

• Cuts over $930 billion from Medicaid over the next decade

• Eliminates enhanced ACA tax credits, making coverage unaffordable for millions

• Imposes new work requirements for Medicaid recipients aged 19–64, even if they’re already working or caregiving

• Requires eligibility re-verification every six months, increasing red tape and coverage loss

• Slashes funding to rural hospitals, especially in non-expansion states, risking closures

The result? Up to 17 million more people uninsured by 2034, including:

• Seniors in long-term care

• People with disabilities

• Low-income families

• Rural residents with no alternative providers

🧠 The Rhetorical Bait-and-Switch

Dr. Oz’s quote about caring for “those in the twilight of life” is lifted from a famous line by Hubert Humphrey. But while he invokes moral duty, the legislative machinery behind him is systematically dismantling the very safety nets that uphold that duty.

It’s a classic case of compassion in the microphone, austerity in the margins.

🧭 Final Thought: “Modernization” at the Expense of Humanity

Fraud prevention is vital—but we must ask: prevention for whom, and at what cost?

The Medicare Fraud Crackdown is being heralded as a necessary technological evolution. Yet beneath the sleek veneer of “modern tools” and AI oversight lies a deeper reckoning: systems that once promised care are being remade into engines of suspicion, prediction, and exclusion. As we applaud efforts to safeguard public funds, we cannot ignore that the very people this system claims to protect—elders, the disabled, rural patients—are the same ones being algorithmically filtered, flagged, and forgotten.

At the same time, legislation like the OBBBA strips billions from the programs that make care possible, creating a bitter paradox: surveillance is expanding, while access is shrinking.

We stand at a crossroads where public trust is being coded into black-box systems and moral duty is being outsourced to machine logic. If healthcare is to remain a human right—not a risk score—we must not just monitor fraud; we must monitor power.

This moment demands vigilance, not just from watchdogs in Washington, but from all of us who believe that dignity should never be debugged or denied.

On one hand: AI surveillance, “war rooms,” and moral appeals to protect the vulnerable.

On the other: A legislative bulldozer quietly gutting the programs that serve them.

• WE SEE YOU, WE HEAR YOU AND WHAT YOU DO AFFECTS US ALL

.🧠 Final Thought

This isn’t just a fraud crackdown—it’s a paradigm shift in how healthcare decisions are made. The language of “modernization” and “efficiency” masks a deeper transformation: one where data models, not doctors, increasingly shape what care is deemed necessary.

More information on the State level breakdown: Joint Economic Committee with links to the CBO, district level breakdowns, factsheet information and more on estimates of people who are affected.