For the first time, obesity has a treatment that works at scale, and the system that would pay for it is nowhere near ready. GLP-1s have handed American healthcare a path to finally treat a critical condition, in a population too large to treat all at once, at a price most budgets can’t absorb. Health plans are reacting in every direction: some adding coverage, some pulling back, most waiting on the sidelines to see.
Elina Onitskansky spent twenty years inside American healthcare, on the payer side as Senior Vice President and Head of Strategy at Molina Healthcare, and before that as an Associate Partner in McKinsey’s Healthcare Systems and Services Practice, watching the system treat obesity the way it once treated mental health: as a choice, an ancillary condition, not really a disease. She also lived with it herself. That combination – personal experience plus pattern recognition for how mindsets, treatments, and coverage actually shift – drove her to found Ilant Health. It’s a value-based center of excellence for obesity and cardiometabolic health, working with health plans and employers to match each individual to the right treatment rather than defaulting to a single answer.
Nurit Ben sat down with Elina on why access versus affordability is a false choice, the prevention conversation that arrives way too late, and how technology is finally allowing smart treatment at scale.
You spent close to twenty years inside the machinery of American healthcare. What did you see from the inside that made you decide this was a problem worth leaving to solve?
I think the terminology of ‘machinery of U.S. healthcare’ is right. It’s close to 20% of GDP. It is a really giant machine, and yet it affects us at a human-to-human level, and that tension is real. What I saw within it, which I think people often miss, is that people attribute the problems to the people on the inside not trying. Most people are trying deeply hard. But despite all of those incredibly good intents, we all have blind spots. Having lived with obesity, I was very conscious of that blind spot at a human and personal level. And I had the pattern recognition from prior experience to ask: what are the meaningful blind spots we’ve gotten wrong before, and why did we get them wrong?
The very natural comparison is mental health. Today it would shock people to ask why someone needs mental health care, but that was a conversation being had ten years ago: is this really health, or is it a choice? So it was interesting to be living the obesity experience, recognizing the pain points, and having that pattern recognition around what happens when mindsets change. You realize that something we thought was an ancillary condition, low acuity, not a big deal, maybe a lifestyle choice, is actually a really big deal. And what does it take to shift the machinery? What is the data you need? How does the treatment need to work? What are the outcomes? For me, it was the combination of the personal experience around obesity and the knowledge of how not just mindsets but approaches, treatments, outcomes, and coverage change within healthcare that made me say: I know what needs to exist here to actually change the approach to obesity and cardiometabolic health, and I can help put it in place.
"It was interesting to be living the obesity experience, recognizing the pain points, and having that pattern recognition around what happens when mindsets change. You realize that something we thought was an ancillary condition, low acuity, not a big deal, maybe a lifestyle choice, is actually a really big deal"
Ilant Health Founder & CEO
Elina Onitskansky
GLP-1s are making aggressive metabolic intervention mainstream, which sounds like a tailwind for everything you just described. But you’ve argued this moment is actually also a dangerous one for payers. Why?
You’re seeing the reaction to it already: some are trying to add coverage, some are pulling back, some are staying on the sidelines to wait and see. I made the comparison to mental health earlier. I don’t have the exact numbers, but anywhere from 10 to 20% of the population may have some level of mental health concern. We know that 50% of the U.S. has obesity, 70% has obesity or overweight, and 90% has a metabolic disorder. So take mental health and multiply it by a lot.
The challenge is that on one hand, that prevalence creates all of the downstream costs related to obesity: diabetes, musculoskeletal issues, obstructive sleep apnea, and by the way, a bunch of cancers. That is real. But there’s also the question of what happens when you make an abrupt transition and when a big percent of the population goes on a really high-cost treatment. That cost is immediate, while the downstream costs may occur or may not. So how do I make this work in an infrastructure that’s already unaffordable? We’re entering this moment around obesity and GLP-1s at multiple inflection points at once.
You also seem skeptical of how much of this conversation centers on prevention.
People want to tell me about prevention of cardiometabolic health, and I’m like: 90% of the population has a metabolic health dysfunction! What are we preventing? Prevention is helpful when you’re at 10% and trying to prevent the other 90. The ship sailed, ran aground on the other shore, and we’re standing here saying, let’s prevent the ship from sailing. It’s way over there.
"People want to tell me about prevention of cardiometabolic health, and I'm like: 90% of the population has a metabolic health dysfunction! What are we preventing? The ship has sailed"
Ilant Health Founder & CEO
Elina Onitskansky
So what do you wish people understood better about what needs to happen now, whether that’s investors or payers?
We need to get out of this either/or mindset. We often have a yes/no, black/white, access-versus-affordability approach. That’s fun to argue, but it’s just not productive in the real world. We’ve approached obesity with people basically saying: either everyone who wants a GLP-1 should have access to it with no requirements, or no one should have access because they’re too expensive, and by the way, there’s a miracle diet that will work. Neither of those is the right answer. What we need to get much better at is the nuance, and we talk about this a lot around precision treatment and precision analytics.
"We need to get out of this either/or mindset. We often have a yes/no, black/white, access-versus-affordability approach. That's fun to argue, and it's just not productive in the real world."
Ilant Health Founder & CEO
Elina Onitskansky
And this has to go beyond GLP-1s, because 90% of the population has a metabolic disorder. It’s not about a drug or a treatment. It’s about what we are fundamentally going to do to change the trajectory and health of the country. As much as I just pooh-poohed prevention, we’ve got to do some level of prevention; we can’t keep moving in that direction. And obviously we’re not going to treat 50, 70, 90% of the population at once. Where do we prioritize? Where do we proactively pursue treatment? What is the right treatment? The answer here is not a drug. It’s a care plan: the right treatment and the right support to generate outcomes, and a way to deliver that at scale. That is the nuance we’re trying to bring. We’re not trying to have a debate on whether people need access to GLP-1s or not. The answer is yes to some, no to others. If we can get the nuances right, there doesn’t need to be a trade-off between access and affordability. That’s really our core message.
From your insider view, is there a reckoning coming in how the system is approaching GLP-1s?
I think it’s wrong on both sides. We’ve seen some of the risk of a GLP-1s-for-all strategy: it exacerbates some of the existing societal challenges that have led to eating disorders and problems with body perception. It would be tragic if GLP-1s had us take a step back from the body positivity approach, because the reality is, yes, we need to address obesity, and the answer will not look like a population of Victoria’s Secret models. We need to not mistake those two dynamics.
On the other hand, the reaction to the potential cost has led a lot of folks to say, we’re just not going to cover it. And because obesity drives 200-plus conditions, that’s not a viable approach either. We know all of the cardiometabolic conditions: diabetes, hypertension, hyperlipidemia, the progression to chronic kidney disease, MASLD. There are the mechanical conditions: obstructive sleep apnea, osteoarthritis. We know there’s comorbidity with anxiety, depression, and disordered eating. There’s fertility, PCOS, hypogonadism. There are 13 cancers. It’s a long list. So we can attack it piecemeal and say, we won’t cover it for obesity, but we will cover it for diabetes and cardiovascular disease and MASLD and obstructive sleep apnea and osteoarthritis. You’re going to end up with an approach that costs more and gets worse outcomes.
Ilant Health Founder & CEO
Elina Onitskansky
Essentially ignoring comprehensive care which is then ineffecient for patients and payors.
And there’s already fragmentation in the U.S. healthcare system, where we treat by body part. Because obesity is so multifactorial, most people we see have multiple body parts affected. There’s a real risk in saying, this problem seems so massive, we’re just not going to treat it until XYZ happens. What you get instead is a hugely fragmented approach to care.
Walk me through how Ilant Health approaches this. You’ve built an evidence-based way to personalize care, where not all patients are the same. Could that have existed five or ten years ago?
What we really focus on is understanding the full picture of each individual. That starts clinically. BMI tends to be a proxy, but you can have two people at exactly the same height and weight with very different needs. So: what conditions do you have, what family history, what risk factors? But also your prior experience, your behaviors, your knowledge around nutrition and physical activity. And then, separate from that, your context: socioeconomic, family, job, all of those things. We look at all of that to personalize care.
That’s what I often call phenotype-based matching. We group people into categories, like early onset of disease or event-driven onset, and we develop plans around those. The real potential, and I think we’re very much on the cusp of this, is to get to a truly individualized level, where we really get to responders and non-responders. We essentially say: people with these biomarkers and these factors tend to respond more to this treatment versus that treatment, and people with these motivations and these life contexts tend to respond better to this support versus that support. We can then begin to solve at that n-equals-one level.
And at scale is the key here, right?
Yes and the technology today, around automating information, matching people, AI, and unstructured machine learning, creates the possibility to do this at scale. Ilant Metabolism Matters, our clinical decision support tool, takes a ton of information, runs it through, and does the matching. That’s something a physician could have spent two hours doing, which makes sense in a concierge model but could never make sense at the scale of America. So we now have the ability to give people incredible care at scale. But the next phase we’re working toward, this n-equals-one personalization with the biometrics and the motivations, cannot exist in a world where you can’t manage large data sets. What we’ve seen with AI and data science is enabling that care.
And think about the scale of the problem – 50%+ of the population.
"This is part of my joke when people say everyone should have access to a GLP-1: there's nothing else where you would say put 50% of the population on anything, unless it's clean air. The ability to actually understand clusters and dynamics and run large data is frankly the only way we turn the tide on the scale of the cardiometabolic problem in the U.S."
Ilant Health Founder & CEO
Elina Onitskansky