What You Need to Know About AI Making Healthcare Decisions

Ladies, while we've been watching the daily news cycle, a quiet but potentially game-changing shift is happening to Medicare that could disproportionately affect us. It's time we paid attention.

You know that feeling when you're scrolling through headlines about celebrity breakups and political drama, and then you stumble across something that makes you stop cold? That happened to me recently when I came across a story buried in the tech news about something called the "WISeR Model"—a new Medicare pilot program that will use artificial intelligence to decide whether certain healthcare services are "appropriate" or not.

My first thought? This sounds important. Why isn't anyone talking about this?

My second thought, after digging deeper into the research? This could be a really big problem for women.

What Exactly Is the WISeR Model?

Let's start with the basics, because this story is complicated enough without getting lost in government jargon. WISeR stands for "Wasteful and Inappropriate Service Reduction Model," and it's a new pilot program from the Centers for Medicare and Medicaid Services (CMS) that launches January 1, 2026.

Here's what's happening: For the first time, Original Medicare (the traditional fee-for-service Medicare that most of us are familiar with) will require prior authorization for certain medical services in six states: Arizona, New Jersey, Ohio, Oklahoma, Texas, and Washington. Prior authorization means your doctor has to get approval from Medicare before providing certain types of care.

But here's the kicker—instead of having human reviewers make these decisions, Medicare is contracting with private technology companies that will use artificial intelligence and machine learning algorithms to determine whether your healthcare is "necessary" or represents "waste, fraud, and abuse."

The official line from CMS Administrator Dr. Mehmet Oz is that "CMS is committed to crushing fraud, waste, and abuse, and the WISeR Model will help root out waste in Original Medicare" and will "streamline" the process. The government says they're targeting $5.8 billion in potentially unnecessary healthcare spending, according to the Medicare Payment Advisory Commission.

On paper, it might sound reasonable. Who doesn't want to eliminate waste and fraud? But when you start digging into the details—and especially when you look at the data about how women use healthcare differently than men—a more troubling picture emerges.

The Numbers Don't Lie: Women Use Healthcare Differently

Let's talk about some facts that might surprise you, even though they probably won't when you really think about it.

Women live longer. At age 65, women have a life expectancy of 19.7 years compared to 17 years for men. This means we represent a much larger share of older Medicare beneficiaries—nearly two-thirds (63%) of Medicare beneficiaries ages 85 and older are women.

Women use more healthcare services. Study after study confirms this pattern. We have more doctor visits, more diagnostic tests, and yes, higher healthcare costs overall. Research specifically on Medicare shows that women are more likely than men to use inpatient services, skilled nursing facilities, home health services, and hospice care.

Women face unique healthcare challenges. We're more likely to live alone as we age, which affects our healthcare needs. We're more likely to have conditions like osteoporosis, autoimmune diseases, and depression. We also tend to have more complex healthcare needs as we age, requiring more coordination between different specialists and services.

Now, here's where it gets interesting—and concerning. The WISeR model is specifically targeting services that have been flagged as potentially "inappropriate" or "unnecessary." The list includes things like:

• Skin and tissue substitutes
• Electrical nerve stimulator implants
• Knee arthroscopy for knee osteoarthritis
• Various cardiac and pain management procedures

Look at that list and think about your own health journey, or that of the women in your life. How many of us have dealt with chronic pain that took years to diagnose properly? How many of us have been told our symptoms were "just stress" or "part of getting older"? How many of us have had to fight to get treatments that ultimately improved our quality of life?

The AI Problem: When Algorithms Inherit Our Biases

Here's where this story gets really problematic. Artificial intelligence sounds futuristic and objective, but AI is only as good as the data it learns from. And unfortunately, healthcare data has a long, documented history of being biased against women.

Let me share some eye-opening research findings:

AI models are already missing women's health issues. A recent study from University College London found that AI tools designed to predict liver disease from blood tests were twice as likely to miss the disease in women compared to men. Another study from the London School of Economics on AI tools used by healthcare systems found that Google's AI model described men's health issues more severely than women's, even when the medical notes were identical except for gender.

Healthcare algorithms perpetuate existing discrimination. Research published in PLOS Digital Health has documented that cardiovascular disease prediction models are often trained on predominantly male datasets, even though heart disease presents differently in women. Women are already more likely to be misdiagnosed or experience delays in diagnosis for heart conditions, and AI trained on biased data will likely perpetuate these problems.

Women's concerns are already dismissed at higher rates. Here's a statistic that probably won't shock you but should outrage you: According to the 2020 KFF Women's Health Survey, women are almost twice as likely as men to say a healthcare provider dismissed their concerns (21% vs. 12%). Among women who had negative experiences with providers, 20% believe it was because of their gender.

Now imagine these existing biases being baked into an AI system that has financial incentives to deny care.

The Financial Incentive Problem

This is where the WISeR model gets particularly troubling. The private technology companies that will be running these AI systems don't get paid a flat fee for their services. Instead, they get paid based on how much money they save Medicare by reducing "unnecessary" services.

Think about that for a minute. The companies making decisions about your healthcare get paid more when they deny more claims.

This creates what economists call "perverse incentives." In a system where women already use more healthcare services, already face more skepticism about their symptoms, and are already more likely to have their concerns dismissed, an AI system with financial incentives to cut costs could be devastating.

Consider this scenario: You're dealing with chronic pain that's affecting your quality of life. Your doctor recommends a nerve stimulator implant—one of the procedures specifically targeted by the WISeR model. An AI system, trained on data that reflects decades of women's pain being undertreated and underdiagnosed, flags your case as potentially "inappropriate." The company reviewing your case gets paid more if they deny it.

What are the odds that AI system will give you the benefit of the doubt?

The Data Behind the Concern

Let's look at some more numbers that illustrate why women should be particularly concerned about this shift:

Women have less financial cushion. According to KFF's analysis of Medicare beneficiaries, half of all Black women have $19,300 or less in savings—seven times lower than White women. Half of Hispanic women have even less, with median savings of just $16,350. When you're operating with limited financial resources, having medical care denied or delayed can be devastating.

Women are more likely to experience medical discrimination. According to the same KFF survey, nearly four in ten (38%) Black women say they've been treated poorly by healthcare providers because of their race/ethnicity. Women ages 18-25 are particularly likely to say they've had negative experiences with providers, with 47% reporting they believe age discrimination played a role.

Women's health conditions are more likely to be dismissed. Research published in medical journals consistently shows that women wait longer for pain treatment, are more likely to have their symptoms attributed to emotional or psychological causes, and face longer delays in receiving diagnoses for everything from heart disease to autoimmune conditions.

All of these existing disparities could be amplified by an AI system that learns from historically biased data and has financial incentives to cut costs.

What's Particularly Concerning About Traditional Medicare

Here's something that makes this shift even more significant: Traditional Medicare has historically been the "safe haven" for people who wanted to avoid the hassles of managed care.

Unlike Medicare Advantage plans, which have always required prior authorization for many services, Original Medicare has traditionally operated on a "fee-for-service" model where your doctor could provide medically necessary care without jumping through administrative hoops.

Many women specifically chose to stay in Original Medicare because they valued this freedom and wanted their healthcare decisions to be made by their doctors, not insurance company bureaucrats. The WISeR model fundamentally changes this relationship.

As one group of 17 Democratic lawmakers wrote in a letter criticizing the program: "Many patients choose Traditional Medicare because they know their care will be determined by their doctors and not by insurance companies." The WISeR model blurs this line by inserting private companies with AI systems—and financial incentives to cut costs—into the decision-making process.

The Bigger Picture: A Pattern of Concern

The WISeR model doesn't exist in a vacuum. It's part of a broader push to use technology to cut government healthcare spending. The program aligns with goals outlined in Project 2025, which identified Medicare and Medicaid as primary drivers of the federal deficit and called for using AI to detect "waste, fraud, and abuse."

While nobody wants actual waste or fraud, the challenge is that "waste" is often in the eye of the beholder—especially when the beholder is an AI system trained on biased data and operated by a company with financial incentives to cut costs.

We're already seeing this pattern in other areas. Medicare Advantage plans, which do use prior authorization extensively, have been criticized for inappropriately denying care. A 2022 report from the Department of Health and Human Services found that Medicare Advantage plans sometimes deny care that should be covered, and beneficiaries often don't appeal these denials even when they might be successful.

What This Means for You

If you live in one of the six pilot states (Arizona, New Jersey, Ohio, Oklahoma, Texas, or Washington), this change will affect you directly starting in January 2026. But even if you don't live in these states, you should pay attention—if the pilot is deemed "successful," it will likely be expanded nationwide.

Here's what you need to know:

Your doctor will need approval before providing certain services. If your doctor recommends one of the targeted procedures, they'll need to request prior authorization from the AI system. This could delay your care while the system processes the request.

Denials may be more common. Because the companies running these systems have financial incentives to cut costs, and because AI systems can reflect historical biases against women's healthcare needs, you may be more likely to face denials or delays.

You still have appeal rights. If your care is denied, you maintain all your traditional Medicare appeal rights. But appeals take time, and many people don't pursue them even when they might be successful.

Final decisions are supposed to be made by humans. CMS has stated that while AI will support the review process, final decisions to deny care will be made by licensed clinicians. However, if those clinicians are working for companies with financial incentives to cut costs, this may be cold comfort.

What We Should Be Doing

So what can we do about this? Here are some concrete steps:

Stay informed. This story isn't getting the coverage it deserves, but that doesn't mean it's not important. Follow reliable healthcare journalism sources and advocacy organizations that focus on Medicare issues.

Know your rights. Understand your appeal rights under Medicare and don't hesitate to use them if you believe care has been inappropriately denied.

Advocate for transparency. We need to demand transparency about how these AI systems work, what data they're trained on, and how they're being tested for bias. Healthcare AI should be subject to the same rigorous oversight as other medical technologies.

Support organizations fighting for healthcare equity. Organizations like the Medicare Rights Center, the National Women's Law Center, and various patient advocacy groups are working to ensure that AI in healthcare doesn't perpetuate discrimination.

Contact your representatives. Let your senators and representatives know that you're concerned about AI bias in healthcare and want oversight of these programs.

Document everything. If you do face a denial or delay that you believe was inappropriate, document everything. Your experience could be crucial evidence in evaluating whether these systems are working fairly.

The Broader Conversation We Need to Have

The WISeR model raises fundamental questions about the future of healthcare that go far beyond this one program:

• How do we ensure that AI systems designed to cut healthcare costs don't disproportionately harm women and other vulnerable populations?
• What oversight and transparency requirements should exist for AI systems that make healthcare decisions?
• How do we address the historical biases in healthcare data that AI systems learn from?
• What safeguards do we need to ensure that cost-cutting incentives don't override good medical judgment?

These aren't easy questions, and there are legitimate concerns about healthcare costs and fraud that need to be addressed. But we can't allow the pursuit of efficiency to come at the expense of equity and access to care.

Why This Matters More Than Ever

Here's why I'm particularly concerned about this program launching now: We're at a critical moment in healthcare AI. The decisions we make about how to implement AI in healthcare today will set precedents that last for decades.

If we allow AI systems with built-in biases and problematic financial incentives to make healthcare decisions without adequate oversight, we risk entrenching and amplifying existing healthcare disparities. But if we demand transparency, accountability, and equity from the beginning, we have an opportunity to use AI to actually improve healthcare for everyone.

The WISeR model, as currently designed, seems to lean toward the former rather than the latter. But it doesn't have to stay that way.

The Bottom Line

Ladies, I know we're all tired. We're tired of having to fight for our healthcare. We're tired of being dismissed and disbelieved. We're tired of having to prove that our pain is real and our concerns are valid.

But this is a fight we can't afford to sit out.

The WISeR model represents a fundamental shift in how Medicare works, and early indicators suggest it could disproportionately impact women. We represent the majority of older Medicare beneficiaries, we use more healthcare services, and we already face significant barriers to getting our healthcare needs taken seriously.

This isn't the time to let this issue slip by unnoticed while we're distracted by other news. This is the time to pay attention, ask questions, and demand better.

Our healthcare—and our daughters' and granddaughters' healthcare—may depend on it.