The AI freakout of the past few weeks has centered on nothing less than the risk of human extinction — on the possibility that artificial intelligence could wipe us all out. But the reality is, AI programs are already having a direct and sinister effect on people’s physical health: UnitedHealth Group, the largest health insurer in the US, has been accused of using AI programs to deny payments to people, despite their doctors saying the care was necessary, and is facing a class-action lawsuit. 

Humana and Cigna are facing their own litigation over similar allegations. Meanwhile, Medicare has launched its own AI tool that will help the government determine whether to approve prior authorizations, and doctors are sending the federal government reports of patients at their offices who are in tears because they can’t get the medicine to manage their chronic pain.   

The claims in the legal complaints are harrowing: Families are desperate for an elderly loved one who recently experienced a serious fall to be allowed to stay in a nursing home. Doctors are flummoxed when a patient who may need months of rehab is cut off by an algorithm after a couple of weeks. 

This is AI’s threat to people’s health right now. 

While the current conversation may be fixated on something more Hollywood, private insurers and the Trump administration are already deploying AI programs to vet people’s health insurance claims — and the evidence is growing that these programs are not always doing a good job and are instead putting people’s health at risk. Until these lawsuits are settled or policymakers can figure out a way to regulate how insurers use this new technology, it will be up to each of us to make sure that an AI program isn’t being used to cheat us out of insurance benefits that we’re entitled to.

“The type of care that clinicians deliver is very sensitive to the patient’s unique circumstances. That may not really show up as a number. There’s not a numeric value that tells you the completeness and connection of a patient’s social network,” said Mika Hamer, a health services researcher at the University of Maryland. “There really are a lot of factors that really can’t be quantified and so aren’t really suitable to go into these models. If we start to rely exclusively on the models, I think we run the risk of losing that human touch.”

Patients say private health insurers are using AI to deny claims

Insurers and patients fighting over medical claims is nothing new: Policyholders want the most coverage they can get and payers have a business incentive to pay as little as they can. Health insurers have also used algorithms for decades: Plug in somebody’s age, their weight, whether or not they smoke, and one of the old-fashioned algorithms could spit out a rough estimate of how much medical care they would need before they died. Simple — and comparatively transparent. 

When you submitted a claim or sought prior authorization, there was supposed to be a human doctor who could review all of the relevant information on behalf of the insurer and make the final decision, in theory with the patient’s best interests in mind. It didn’t always work that way in practice, of course, but that was the idea.

What’s different right now, according to Daniel Schwarcz, a law professor at the University of Minnesota who has looked at health insurers’ AI use, is that these newer programs can make very specific predictions about someone’s future health based on the information that’s fed into them, and those predictions are being used in the process of approving or denying medical claims. And exactly what went into making those predictions — and whether it is the AI or the human who ultimately holds the final authority — is often opaque from the outside.

“The reason we want human review is we want human substantive judgment. We want AI to be supporting that,” Schwarcz said. “But the difficulty is distinguishing between AI supporting meaningful human processing and AI basically replacing the human with the human just passively defaulting to the AI judgment. It’s just incredibly hard to distinguish between those two in practice, particularly in rules or regulations.”

And those questions are at the heart of the lawsuits brought against three major insurers in the past few years about their use of AI in processing claims.

In May 2022, Gene Lokken, then 91 years old, fell in his home. He was taken to the nearby hospital in Tomahawk, Wisconsin, and treated for a broken leg and a broken ankle. Less than a week later, he was placed in the health system’s hospice care because, according to the lawsuit filed by his family, he was “very weak, not communicative, and in constant pain.”

But a month later, after receiving skilled nursing care, Lokken started to improve. By late June, his doctor had removed his splint and placed his leg in a removable boot. In July, he started physical therapy to get up and walk again. And for a while, his Medicare Advantage plan sold by UnitedHealth covered all of the services he needed.

Until July 20. Around that time, according to the lawsuit, UnitedHealth denied any more services at the nursing facility where Lokken had been for the past two months. It insisted that he could be safely discharged and more time at the nursing care facility “was not medically necessary.”

The insurer’s decision left Lokken and his physician “dumbfounded.” The physical therapist notes from the time said Lokken was still suffering paralysis and weakness after only a couple weeks of rehab. His family appealed, but UnitedHealth continued to deny the claims, asserting that because Lokken could feed himself and did not require help to clean himself, he did not need nursing care and could go home. 

From July 2022 to July 2023, Lokken remained at the nursing home, but his family had to pay between $12,000 and $14,000 monthly to keep him there. And on July 17, 2023, Lokken died — having never left the facility.

The lawsuit alleges that the decision to stop covering Lokken’s nursing-home stay was largely made by an AI algorithm, called nH Predict, which UnitedHealth follows so unquestioningly that employees were allegedly at risk of being disciplined or fired if their claims decisions went against the AI’s projections. The complaint alleges that the AI model would typically start denying claims after two weeks of nursing home care — and the attorneys have more examples than Lokken.

Glennette Kell required emergency surgery after a fall in late August 2023 and was referred to a nursing home rehab center. By mid-September, UnitedHealth was denying her claims for nursing care, despite the fact that, according to the lawsuit, she still could not walk. Kell had to pay $10,000 of her own money to cover the rest of her bills. Darlene Buckner suffered a heart attack in October 2023 and underwent triple-bypass surgery. She was readmitted to the hospital in late November because she was experiencing complications, but less than two weeks later, UnitedHealth allegedly denied any further treatment at the hospital because it was deemed medically unnecessary. At the time, according to the class-action lawsuit, Buckner was experiencing “an open infected wound near her heart from the open-heart surgery, she was on blood thinners, and was receiving antibiotics through an IV.” 

UnitedHealth, in its responses to the plaintiffs, has asserted that federal laws and regulations already require all claims decisions ultimately be made by a human doctor, not an AI program, and raised several other technical legal objections (such as saying the plaintiffs have not fully exhausted their administrative appeal options). The plaintiffs, however, allege that UnitedHealth employees “are instructed not to deviate” from the AI model’s projections, and then tell patients the AI-generated information is proprietary when they or their doctor try to inquire about why their claims are being denied. 

And, to be clear, UnitedHealth is not the only insurer being sued for using AI programs to deny claims. Humana is facing its own lawsuit brought by other Medicare Advantage patients who allege the same nH Predict program also led to their claims being wrongfully denied. Joanne Barrows, then 86, fell in November 2021 and went to a rehab nursing facility after her hospital stay. And just two weeks later, Humana began denying her claims for further care, according to the complaint, leaving her and her doctor “bewildered” because she was under doctor’s orders not to put any weight on her leg.

And the third lawsuit, filed against Cigna, alleges the company used a different AI algorithm that allowed its doctors to deny claims in huge batches — hundreds or thousands at a time — if they did not meet certain predetermined criteria. One patient, Suzanne Kisting-Leung, had claims denied for two ultrasounds done by her doctor to check for ovarian cancer, putting her on the hook for more than $700 in medical bills because, the lawsuit alleges, Cigna’s AI program determined that the scans were not medically necessary. The plaintiffs say that their claims were instantly rejected, without their medical files ever being opened. As for the law that human doctors have to make the final call? According to the lawsuit, the algorithm “enable[s] its doctors to automatically deny payments in batches of hundreds or thousands at a time for treatments that do not match certain pre-set criteria, thereby evading the legally required individual physician review process.”

These people, many of them elderly, had no idea AI was being used to make decisions about their coverage — until it was too late.

“From their perspective, you might as well have been speaking Esperanto. They just had no idea what it was that was being said to them when they were being told. They usually heard about it for the first time when they were being told that they needed to leave,” Glenn Danas, one of the attorneys in the class-action litigation against United, Humana, and Cigna, told me. “They just had no idea what was going on or why this was being done to them.”

AI is now making decisions for traditional Medicare claims too

It’s not just private insurers either. The Trump administration is now pushing traditional Medicare and Medicaid to use AI to adjudicate insurance claims too. In June 2025, nearly two years after those lawsuits had been filed against Cigna, Humana, and UnitedHealth, the US Department of Health and Human Services announced it would deploy a new program called the WISeR (Wasteful and Inappropriate Service Reduction) model to make prior authorization decisions for about a dozen procedures for the people on traditional Medicare in six states — “leveraging enhanced technologies, such as Artificial Intelligence (AI) and Machine Learning (ML), along with human clinical review to ensure timely and appropriate Medicare payment for select items and services.” It would be a pilot program, before federal officials decide whether to take the program nationwide.

It was a quiet, massive change for traditional Medicare, which covers about half of the 66 million Americans on the program. (Medicare Advantage plans, in which private companies administer Medicare benefits under slightly different parameters and which were the subject of the earlier AI-related class-action litigation, cover the rest.) People on traditional Medicare had historically not been required to get prior authorization for most services; now they would be, and a novel AI program would play a significant role in which claims get approved and which ones don’t.

From the start, physician and patient advocates warned about the potentially adverse consequences of the WISeR program; the Center for Medicare Advocacy said the program would likely “complicate, delay and even outright deny necessary care.” According to media reports and internal government documents, that’s exactly what has happened since the model went live in January. 

The Washington Post first reported in March that physicians and their patients were experiencing approval delays or denials for medical services that should have been covered. One glitch led to a denial of payment for services that had been approved. Doctors noticed that certain procedures seemed to give the AI model problems — such as two competing treatments for incontinence — and were weighing whether or not to stop offering one of those services altogether. The Post reported on one Arizona patient who had been receiving steroid injections for chronic back pain before being denied multiple times after the AI program’s launch. The pain became so severe, he said, that he could not exercise at all.

Then this month, the Electronic Frontier Foundation released a trove of documents it received in response to a Freedom of Information Act lawsuit related to the WISeR model. The documents revealed aggressive denials — one company using the AI model had actually denied more prior authorization requests than it had approved — and there were delays even when the care was ultimately approved. One review took 83 days when the model was supposed to make a decision within 72 hours.

The direct feedback from doctors in the federal documents obtained by EFF was devastating.

“We have patients calling our offices crying in pain because their procedures are being delayed while awaiting approvals or guidance tied to this model,” one doctor wrote. “A 3-4 day delay for necessary pain procedures is already difficult for vulnerable patients, but when providers cannot obtain answers for weeks, the situation becomes unacceptable.”

According to the federal documents, the Trump administration was already discussing ways to expand the program. Despite the outcry from doctors and patients, and growing concern among their representatives in Congress, it doesn’t look like WISeR is going away.

How can we make sure AI doesn’t take over insurance claims?

AI is becoming a part of healthcare — it is already happening. And many of those uses could be truly beneficial. Anthropic recently announced an initiative to apply the theoretical findings of its AI models to real-life lab work that could lead to new drugs being developed in the future. In terms of scientific discovery and the potential to translate it into new treatments, the excitement among clinicians about its potential is palpable.

And nobody denies that health insurance administration is chaotic and burdensome and would benefit from being made more efficient and streamlined — tasks which AI is at least superficially well-suited for.

But as the past few years have already shown, rushed and sloppy deployment of AI to take responsibility for approving or denying payment for people’s medical care has created serious problems. The issue is that this technology is being adopted more quickly than any regulator can oversee it. We don’t really know how health insurers are using AI tools. We don’t have a good framework for what keeping a “human in the loop” of insurance decisions — which is what people want — would really mean, Schwarcz said. 

“I think everyone agrees at a high level of generality, ‘Yes, AI should be used to enhance human review and not to replace it,’ but no one actually knows how to write rules to enforce it,” he told me. “I don’t think that there’s anything I’ve seen that has effectively defined what it means for a human to be meaningfully in the loop in the sense of retaining independent judgment as opposed to just reviewing and deferring. It is incredibly hard to specify in rules or regulations a standard that is verifiable and enforceable. That is still, as far as I know, an unsolved problem.”

Some states have started adopting rules requiring transparency for AI use in insurance claims, and lawmakers in Congress have put forward proposals requiring human involvement, including the bipartisan Protecting Patients from Automated Denials Act. But these technologies are so ubiquitous and so flexible that rigorously regulating their use is going to be difficult. Meanwhile, the profit incentive for companies to adopt these tools and deploy them widely is extremely strong. We don’t even know how widespread their use really is.

Danas said he and his clients hoped their litigation would help with “putting the brakes” on AI’s use in insurance. Until we figure out what to do from a policy perspective, what can each of us do in the meantime? Hamer told me that the old advice is still the best advice: If your claim is denied, appeal it. An enormous number of denied claims end up getting overturned on appeal. 

“You do not necessarily have to accept that the first answer from your insurance company is the final determination,” she said.

If there’s one thing that Americans can unite behind, it’s anxieties over artificial intelligence.

According to a recent NBC News/Decision Desk poll, 70 percent of adults say they are personally more worried than excited about the technology; it’s basically underwater in every area of society with one notable exception: its use in scientific research and medicine.

According to Dr. Dhruv Khullar, a physician at Weill Cornell Medicine and writer at the New Yorker, that optimism is well-founded.

Khullar uses AI tools in his own practice as a physician and writes about their advancements in the medical field. He says that “right now, at least, there’s a generally optimistic view of how AI will change healthcare going forward.”

AI in medicine is nothing new. In 2024, the Nobel Prize in Chemistry was given to researchers who developed an AI model that enabled breakthroughs in predicting protein’s complex structures. As it becomes more ubiquitous, it’s also emerging as a resource for doctors to get second opinions and as a tool to take notes on patient-doctor interactions.

On top of that, Khullar says, it might help unlock new medicines to treat diseases. 

Khullar joined Today, Explained co-host Sean Rameswaram to discuss the ways that AI is transforming drug discovery and research, as well as what it still can’t do. They also discuss how to think about AI’s potential in healthcare at the same time as top AI researchers are increasingly warning about the technology’s risk.

Below is an excerpt of the conversation, edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get podcasts, including Apple Podcasts, Pandora, and Spotify.

You’ve been thinking about lifesaving AI innovation. Has AI already started saving lives?

I think it has. This is the fastest I’ve ever seen healthcare take up a new technology. Part of that might be that the healthcare system is so messed up that there’s an appetite for some type of change. It’s unaffordable, it’s inaccessible, it’s inconvenient, the quality is uneven. 

There’s at least a hope that AI is going to help with all of these things, and I think it’s already starting to make its way into the healthcare system. Now it’s our responsibility to figure out how to make the most of it without also promulgating some of the downsides.

For those who are unaware, tell us how it’s working its way into the system.

It’s helpful to categorize it into a few buckets, at least for healthcare. 

The most rapid uptake, and I think the place that it’s already starting to make a difference, is on the administrative side. Many people who have gone to a doctor recently might have noticed that there’s an AI scribe that’s taking notes now. And people seem to really like it, at least so far. Doctors are able to look their patients in the eye in the way that they weren’t able to when they were poring over their computers and just typing what the patient was telling them. 

The second big area is patient navigation. When is your next scan? When’s your next appointment? Do I need to take this medication on an empty stomach or not? There’s a huge opportunity for people, let’s say, who are diagnosed with a serious illness like cancer or heart failure to navigate the system more seamlessly. 

The third big area that I’m really excited about is drug discovery. AI is making a huge dent in the early parts of drug discovery. 

The last thing that I’m excited about and that I use every day when I’m in the hospital is [AI] as a second opinion. Now instead of having to get a consult or turn to a textbook, AI can be a very, very helpful clinical decision support. It’s not to say that I never consult someone, of course, but that first pass — I’m not sure what’s going on. What are some recent trials that might influence my decision here? Is there something I’m missing? Is there a test that I should be ordering that I’m not ordering? — all those types of things, they start to help with.

The biggest chunk of this positive view of AI and medicine is drug discovery. Tell me more about how that’s going so far and how it might be going in a year, or five, or 10.

I don’t want to leave this conversation and say that we’ve solved the cure for cancer because of AI, but I do want people to know that at least for the early stages of drug discovery — figuring out the very basic steps of is this an interesting molecule? Does it have potential biological applications? — AI is already very helpful for that. 

They’re trying to take, basically, what is an infinite number of drug-like molecules that are theoretically possible to be drugs and they’re trying to match that to some disease that’s going on inside a human. And human biology is incredibly complex as well. There’s tens of thousands of genes, hundreds of thousands of proteins, trillions of cells, and you have to match a potential molecule to a potential target within a human. 

In the past, a researcher might take years to study a disease or a biological pathway and figure out, okay, this protein seems to be involved. And actually, it might not be involved, it might be involved, it might be disrupted, but not be the causative agent. There’s a lot of uncertainty there, so now AI can take enormous amounts of data, and it can rank various potential targets that seem to be the most likely to be causing a particular disease and give you that short short list of potential targets that may have taken months or years in the past.

So now you know what to attack, but you have to figure out what to attack it with. So you need a molecule, you need to generate a molecule that’s going to fit into that target or disrupt that target in some way. 

Now again, AI can scour vast chemical spaces and give you a list of the things that seem to be most likely to be able to disrupt that target. And then it can actually help you generate that molecule in some cases. 

So now we have the target. Now we have something that we’re going to attack the target with. And then you have to do something called lead optimization, and that’s the third thing. Lead optimization means you have this lead and you have to optimize it.

“I would make the counterargument that healthcare is ripe for disruption and you don’t even need the frontier frontier models to make it a lot better with AI.”

Now we have to figure out, of all the molecules that seem to be good at potentially affecting this target, which ones are able to be absorbed in the body, which ones are going to get to the right tissue. AI models can predict the most likely molecule to give you that Goldilocks set of properties that’s needed for a safe and effective drug.

As we all know from anyone who’s asked AI to write an email for them or Googled a question, these tools have a certain degree of certitude, even though these tools can just be flat out wrong about stuff. Are you guys worried about that in the field?

Absolutely. And so this is why I think the narrative around AI just replacing scientists or doctors or other workers is incorrect. Because you still need a lot of judgment. 

You need to be able to adjudicate the output of these models to figure out what is most promising and what is potentially dangerous. That is going to require wet labs and scientists and reasoning based on prior experience and understanding the context. There’s all sorts of issues around, can you manufacture some of the drugs that are being proposed by these models? So just because it’s set, it dreams something up doesn’t mean you can actually make that thing in the real world.

Some of the drugs that it proposes might actually be toxic in certain ways that it didn’t predict. And of course, then you have to take this thing into clinical trials. You have to recruit l people who are willing to put this medication in their bodies. You have to find out who might benefit, you have to put it through the regulatory process. 

That’s why I said that the first part of drug discovery, where you’re trying to figure out how do we get the right drug candidates, what seems most exciting to test further, that’s going to be really accelerated. That whole second half where we actually have to figure out if it works in human biology, that is still going to be in some respects an analog process.

It doesn’t sound like you’re terribly scared that we are like ceding control of our hospitals, of our research facilities, to AI. This is very much in the sort of assistant bucket?

For now it is. And I think one of the challenges is to maintain our agency as these models become more and more sophisticated. As you lean more on these machines, if you’re a doctor, inevitably some of the skills, the critical thinking, the reasoning that we put into coming up with the diagnosis that we honed over the course of years, that can start to atrophy. 

These are the types of things that we still need to sort through as we’re implementing more and more AI into the healthcare system.

For the people who just say, shut it all down, this is too dangerous, the risk is far too great, we don’t actually need this, this isn’t doing anything for society, would you make a counterargument?

I would make the counterargument that healthcare is ripe for disruption and you don’t even need the frontier frontier models to make it a lot better with AI.

Even if we wanted to “slow the pace of the frontier,” fine. But there are models from a year or two years ago that could be very helpful in the healthcare setting. When we’re talking about slowing the pace of the frontier and the most sophisticated and potentially dangerous models, fine. 

But if we’re talking about shutting down AI and not using it in biotechnology or not using it in scientific research or not using it in clinical care delivery, that’s where I would push back pretty hard.

When we think about the stakes in healthcare, we tend to think of them in terms of life and death, being sick or being healthy. The conversation is about your physical well-being and maybe your mental health — and it pretty much stops there.

But health affects so much more than your body’s biology or even just you personally, as a new survey from Gallup and Pivotal, a philanthropic group founded by Melinda French Gates, shows. That’s especially true for women, who frequently report negative experiences with the health system and ongoing struggles to get their concerns taken seriously; poor health affects the trajectory of their careers and their ability to be engaged with their families, friends, and wider community.

It starts at the doctor’s office or hospital: 51 percent of women say they have had a negative healthcare experience in the past five years, versus 39 percent of men. About one in three said that a doctor did not take them seriously when they said they were feeling pain or other symptoms, versus 21 percent of men, and 33 percent said that they either were misdiagnosed or did not receive a diagnosis. The cost of paying for care is another deterrent: 32 percent of women said they have skipped or delayed care in the past year because of the cost, compared to 25 percent of men.

“To see that half of women in the United States who sought care in the last five years came out feeling like they hadn’t gotten the help or care they needed, that’s frankly staggering,” French Gates told me in an email. “It says a lot about how little we’ve invested in women’s health and how much we expect them to just push through pain or accept uncertainty.”

And the effects of those experiences, the failure to receive proper treatment, ripples out into the rest of the women’s lives. More than half of US women, 54 percent, said they had experienced at least one health-related impact on their family life or relationships; 42 percent said their health had led to a negative effect on their career or work. It also affects their community: 32 percent said their health had affected their ability to participate in civic life.

The toll is not only physical but mental: 48 percent of women said they’d dealt with a mental health condition like depression or anxiety. And socioeconomic disparities abound. Black and Hispanic women are more likely to report being in poor or fair health. Women who have lower incomes are more likely to face career struggles because of their health than those who make more.

I had the opportunity to interview French Gates, who has made women’s health a priority in her work, over email about the survey; its findings on community engagement, menopause, caregiving, and more; and what could be done to address the problems that it reveals. Our exchange is below, lightly edited for clarity and length.

Which of these survey findings surprised you most and why?

The number of women [54 percent] who said they experienced a mental health challenge during or after pregnancy should stop us all in our tracks. And the fact that less than one in three women who sought care found it helpful is really concerning. It’s why I feel so strongly about integrating women’s mental and physical healthcare, especially during pregnancy and postpartum. Mental and physical health are so linked together.

Too much of the burden is placed on women to get answers. All of us deserve so much better.

Nearly one-third of women said in the survey that health problems limited their ability to be involved in their community. What does that look like in practice, and what do communities lose when women can’t fully participate?

Women are so often the backbones of their communities, whether they’re rallying their neighbors around a cause, leading the PTA, or serving in elected office. Without having women — and their ideas and voices — in those roles, we’re missing half of the conversation. Issues that affect women and families are less likely to get on the agenda. They’re less likely to be solved.

When a woman has a health challenge, and she has to spend so much of her time and resources chasing down answers, that makes it harder for her to show up in those spaces. We saw that in the survey: 30 percent of women said their health limited their ability to be involved in their communities. And when women couldn’t get the care they needed, that percentage doubled.

Women’s health is often talked about as a personal issue, but this data is helping us prove that it’s also an economic issue, a family issue, a community issue — it affects all of society.

Caregiving and family responsibilities prevent many women from getting medical care, in particular Hispanic and Black women. That seems to create a vicious cycle: Women are often so busy being the caregivers in their families that they neglect their own health. Eventually, they are the ones who will need care.

What do you think can be done to break that pattern? Is there a philanthropic solution? What public policy changes could be made?

Women are often taught to put themselves last and minimize their own needs. They don’t always have time to care for themselves because they’re so busy caring for others. And they might not be able to afford childcare or home health support for their aging parents. Our survey showed one in six women delayed healthcare because of their responsibilities caring for their family members. For Black women it’s one in five, and Hispanic women one in four. Too many women are facing an uphill road to even just get to a doctor’s office.

It’s possible to make it easier for people to balance healthcare and family responsibilities — but it’s going to take action from many angles. That’s exactly why I invest in both women’s health and in caregiving, and I’d encourage more philanthropists to do the same. Businesses can also support employees with good paid leave policies and reliable but flexible schedules.

But for women everywhere to benefit, we need government leaders to prioritize increasing access to affordable childcare, home health supports, and paid family medical leave. These are policies that have the support of large majorities of Americans because these are issues that affect everyone. So there’s a real opportunity here to offer meaningful help to families.

I am struck by our collective failure on menopause: Women report that they aren’t aware of menopause symptoms until they experience them on their own, that they struggle to get their doctor to take menopause symptoms seriously, and that their menopause experience has held them back in their career. What are some short-term and long-term steps we can take to address those problems?

“Right now, women need better care at critical moments in their lives.”

If more than a third of women only learn about menopause symptoms when they go through them, the system is clearly not working. Women need to learn about menopause from their doctors before they experience it. But doctors aren’t getting the education and training they need on menopause while they are in school. One doctor told me she got just one lecture on menopause across all her years in medical school. One said it was mentioned one time. They are seeking out better training but it can be hard to find. That’s why Pivotal is partnering with the Menopause Society to expand physician training on menopause so doctors, nurses, and other healthcare providers can access the information they’re looking for to better help their patients.

Because menopause isn’t just about being uncomfortable; it can also bring anxiety, heart palpitations, insomnia — significant symptoms that can really hold women back. More than a quarter of women who’ve experienced menopause or perimenopause said it made it harder to live up to their full potential at work. One in 10 had to take leave or leave their jobs entirely. That just shouldn’t be. Women shouldn’t have to step back right at the moment when they could be stepping into leadership roles.

The most immediate steps can come from policymakers, especially at the state level. They can include menopause care in insurance and Medicaid coverage and offer workplace protections to women in menopause the way they do for pregnancy, so women can get the care they need without losing their jobs. I’m also focused on longer-term solutions, like expanding training for healthcare providers and investing in research to accelerate treatment options.  

Women are at the forefront of a lot of wellness trends these days and yet, as the survey reveals, women also report encountering a ton of health misinformation on social media. Why do you think women are so often the targets of this kind of content? What can be done to point women toward and build their trust in sound medical information?

One in three women said she left an appointment without a diagnosis, with her pain being dismissed, or with no answers or next steps. You can understand why those women would start looking for information online. And because women’s health has been underfunded and under-researched, there just isn’t as much reliable information out there as there should be, which leaves a lot of room for people to come in with misinformation. Investing in credible scientific research to fill that vacuum will give both women and their doctors more information going into their appointments.

In terms of your own organization’s work, which investments are you making that you think can make progress on the underlying problems revealed in this survey?

We need to address the right now and we need to address the longer term. Right now, women need better care at critical moments in their lives.

One way we’re investing in that at Pivotal is by making it easier for women to get the mental healthcare they need during and after pregnancy. So we are investing in integrated models that put mental and physical healthcare under one roof. I visited a health clinic in Alabama earlier this year where they identify issues like depression and anxiety right at the outset and then help the mom all the way through her pregnancy care, all in the same place. That model is something we strongly believe in.

Better care for menopause will require better training, which we are thinking about in both the immediate and long term. I mentioned that we’re making more menopause training available to doctors who are currently practicing. That is something I’m really excited about because I’ve heard from physicians who really want to better support their patients and are looking for better information so they can do that. And longer-term, menopause needs to be a much bigger part of the curriculum at medical schools moving forward.

Another longer-term focus of ours is trying to make up for decades of lost time in research. We are funding medical research focused on how diseases specifically impact women, in partnership with an innovative organization called Wellcome Leap. They are working to accelerate progress in women’s health on everything from autoimmune diseases to cardiovascular disease in years, not decades, which is how long health breakthroughs usually take. That’s the kind of urgency women need and deserve.

A decade ago, insulin became the poster child for America’s out-of-control drug prices. The 2017 death of Alec Smith, who was rationing his insulin before he died, and repeated price hikes for a 100-year-old medication (the patent for which was originally sold for $1 to a university to prevent it from being exploited commercially) sparked widespread outrage that a lifesaving medication could be unaffordable to the people who depend on it to survive.

And then politicians actually acted. Starting with a Colorado law passed in 2019, states began passing laws capping the out-of-pocket costs for many people who take insulin; 27 states (plus Washington, DC) now have such a policy. Then in 2022, Congress included a provision in the Inflation Reduction Act that established a $35 per month cap on insulin prescriptions for people on Medicare. Given the national response — drugmakers also made splashy public announcements about reducing the cash price that uninsured people pay — you would be forgiven if you thought this was the one health care cost crisis that the US had genuinely managed to solve.

But the diabetes community has a dire warning: It’s not over. Millions of people continue to struggle to pay for their insulin and having their long-term health put at risk because of, in the words of one advocate who put it bluntly, pharmaceutical greed.

“There has been so much attention and promise to action around the insulin price crisis. … There has been so much action,” said Shaina Kasper, executive director of T1 International, a global nonprofit that advocates for people with diabetes. “And shockingly, frustratingly, critically, the data from our 2024 survey showed that the rationing rates were worse than ever. Ultimately we’re facing such immense and monstrous corporate greed. … When we put a Band-Aid on one hole, another one’s going to find a way to pop out and keep profits high.”

Fixing the insulin crisis will require a multifaceted approach: drug pricing reform, insurance mandates, and possibly even public manufacturing. Out-of-pocket caps, Kasper said, were always a temporary fix for a very broken system. There is still a lot more work to do.

Why so many Americans still struggle to afford insulin

Both national and local surveys indicate that the policy changes of the past decade have not had the desired effect.

A study published last year from researchers at the Yale Diabetes Center found that people treated there were rationing insulin at the same rate in 2024 as they were in 2017; about one in four people reported some rationing due to the cost of the drug in both years. When you added in the people who rationed because of insurance delays or supply limits, more than one in three people — 38 percent — were still having trouble keeping this lifesaving medication on hand in 2024. A 2024 T1 International survey likewise found that nationwide, 34 percent of the Americans who use insulin reported rationing the medicine. (About 8.4 million people in the US rely on insulin to survive.)

Dr. Kasia Lipska, an endocrinologist and researcher who treats patients at the Yale Diabetes Center and who co-authored that study, was surprised by their findings.

“I was surprised because I’ve been looking at the policy and advocating for policy change; you think things are moving, they should be really improving,” Lipska said. “But if I talked to the nurses and our staff at the Yale Diabetes Center, they told me, ‘Of course they haven’t changed. We’re still hearing these stories.’”

How could this be? The explanation is multifaceted, according to Lipska and Kasper. 

“There’s just still a lot of holes in one who is covered by various protections and then how they’re covered and how they access this,” Lipska said. “It’s not as simple as just showing up at the pharmacy and asking for your insulin, and the sticker price is there, and that’s what you pay. It’s extremely complicated.”

For starters, millions of Americans remain uninsured and have to pay the cash price for drugs. While drugmakers make flashy announcements about helping those people, the process of enrolling for savings cards to get those lower prices can be a nightmare; one congressional investigation found in 2023 that uninsured patients were still paying an average of nearly $100 for insulin despite Eli Lilly’s pledge that its generic product would be available for $25 per vial. Even if you manage to get your discount card, the same investigation found that Lilly introduced several restrictions based on geography and needs, and that the specific insulins that are subject to these voluntary price caps are often out of stock at the pharmacy when people go to fill a prescription (while the more expensive brand name version is consistently available).

And then there are the loopholes in those existing federal and state laws. The federal $35 cap applies only to Medicare; the private insurance that covers half the country is excluded. (There have been bills proposed to extend the cap to private coverage, but they have not gone very far in Congress.) The state laws that do exist typically apply only to small-group and individual plans that are subject to state regulations; larger self-funded plans are exempt from state mandates and currently have no enforced limit on out-of-pocket insulin costs. One national estimate found that around 775,000 people who use insulin and had private insurance were protected in 2025 by the caps in states where they’d become law. But more than 1 million people in those states were not, nor were the 2.1 million commercially insured insulin users in states without a cap.

Even for people who benefit from the mandatory out-of-pocket caps instituted by Medicare and state laws, some of them still struggle to come up with $35 a month, given all of the other price hikes Americans have faced since the pandemic. They may have to navigate a complex process in order to actually receive the promised discount. And while a $35-per-month cap sounds straightforward, in practice, people can still face higher costs. Each individual person requires a unique amount of insulin and, for some of them, they might need two different kinds; the pharmacy may not have the right version and will make substitutions that lead to higher costs. That’s how one of Lipska’s patients ended up paying $140 per month for his insulin — despite being on Medicare.

“These things really add up…and frustrate people,” she said, “because what seems like a great idea is not actually how things work on the ground.”

The consequence is that, despite all the legislative activity and self-congratulations, millions of Americans are still at risk of serious health problems because they can’t get insulin.

The worst-case scenario is what happened to Alec Smith: Somebody is forced to spread their insulin so thin that they put their life is in danger. When diabetics have their blood sugar spike without insulin on hand, they can go into diabetic ketoacidosis, “which literally means your blood is turning into acid,” Kasper said. “I can speak from experience: it feels like you’re dying.”

To recover from an episode, they may have to go to the emergency room and end up taking even more insulin while eating in order to get their body back to equilibrium. But even short of an emergency, Kasper said, people who resort to rationing insulin can experience significant side effects. Prolonged high blood sugar due to rationing could lead to serious vision and nerve problems that were supposed to be a thing of the past once insulin became available.

Those were the scenarios that lawmakers wanted to prevent as they tried to make insulin more affordable. But they remain a very real threat for too many people.

The big idea that could make insulin truly affordable

If there’s good news to be found, it’s that the advocacy community is not giving up. They are sounding the alarm about the ongoing affordability crisis and urging Congress to act. But they do worry that the issue has become less urgent: The truly comprehensive mandate for insulin out-of-pocket caps, which is typically introduced every Congress, was delayed this time. “This year, neither bill was introduced for over a year, and it was very concerning,” Kasper said.

But they are also placing bets on something much more profound than a price cap: the government itself procuring or even producing insulin and making it available to people at the lowest possible cost. 

“This idea that medicines should be for people and not for profit I feel like is really catching,” Kasper said. 

Some states are taking baby steps in that direction: Oklahoma passed a bill this year that would offer government funding for private companies that pledge to produce insulin and sell it at a low price. 

Others are going bigger. As I reported in 2023, California has launched a program that is eventually intended to lead to government-owned facilities producing insulin to be sold on the cheap, though it will take years until publicly owned production begins. The New York state Senate approved a similar plan this year, although funding for it didn’t make it into the state’s budget. Kasper said that she is optimistic the project will make it into next year’s spending plan, and says a lot of work is currently being done to ensure it happens.

In the future, public manufacturing could also help to address the supply problems that continue to pop up. There are only three insulin manufacturers in the US right now. As those for-profit pharmaceutical companies place more emphasis on GLP-1 production — which often takes place in the same facilities as insulin production — nonprofit initiatives could fill in the gaps.

“In this time of tariffs even, with these concerns around shortages and rising prices and the corporations having this monopoly and price gouging ordinary Americans for decades now, as we’ve seen on insulin, let’s just make it ourselves,” Kasper said.

This is a long-term vision; if you need help right now, T1 International has resources to help people get health insurance, access discount programs, and even find emergency insulin. But a more affordable future for insulin will only be possible if lawmakers feel compelled to act. Public outrage created one round of reform, but the risk of political complacency is real. So if you care about this issue and want to get involved, T1 International also has a tool kit for people who want to advocate for policy changes, including around public pharma.

“The general communication that we’ve been hearing is that the insulin price crisis is over,” Kasper said. “Everyone should have access to a $35 copay for insurance. As the data shows, as we’ve been talking about, that is just not true.”