By IRAKLI KURTANIDZE

I have lived with type 1 diabetes for more than twelve years, and I check my glucose the way most people check the time: dozens of times a day, in glances that last a second or two. A continuous glucose monitor sits on my arm and produces a fresh number every few minutes. The sensor is a small miracle. What happens to that number after it leaves the sensor is where digital health still falls short.

The industry default is that CGM data lives in one place: the phone app. But life with a chronic condition does not happen inside one app. It happens in meetings, at a desk, in the kitchen, on the couch, in the car. Every time I have to stop what I am doing, find my phone, unlock it and open an app, a tiny tax is charged. The tax sounds trivial until you multiply it by fifty glances a day, every day, for the rest of your life. Friction quietly reduces how often people look, and looking is the whole point of continuous monitoring.

This leads to an uncomfortable inversion for anyone who builds consumer software: the best diabetes tools should minimize time in app, not maximize it. Engagement, session length, daily active minutes, the metrics most product teams are paid to grow, are exactly backwards for chronic disease. A person with diabetes does not want to engage with their glucose. They want to glance at it and get back to their life. The right KPI is glances made cheap, not minutes made long.

Patients understood this before the industry did. Around 2014 the Nightscout community, parents and engineers rallying under the hashtag #WeAreNotWaiting, rigged their own uploaders and cloud dashboards so a child’s glucose could be watched from a work laptop or a smartwatch. CGM in the Cloud was ambient glucose, built by volunteers, a decade ago. Officially sanctioned data access has improved since, but real-time access largely remains gated behind partner programs while public APIs stay retrospective, which is why open-source bridges still fill the gap today.

When our team built Sugar Sense, an app from a small Estonian health-tech company (Sugar Sense OÜ), we treated that history as the spec. The principle: meet the number where the person already is. So the same reading shows up on iPhone and Android, on an Apple Watch face, on the web, in a Windows system tray icon and a Mac menu bar icon next to the clock, in a browser extension, and through Alexa if you would rather ask the room. The app is listed in the Nightscout project’s community app list, and the core app is free. None of this is technically glamorous. Putting a number next to the system clock is boring engineering. It is also, for a person who glances fifty times a day, the difference between a tool and a burden.

Ambient matters twice over for the people who love us. A parent at work, a spouse in another city, a grandparent learning to help: for them, real-time following turns background anxiety into a two-second glance. We made family following free in our app because access to a loved one’s safety signal should not sit behind a premium gate. The caregiver is not an edge case in chronic disease. Half the time, the caregiver is the user.

None of this is unique to glucose. Blood pressure, heart rhythm, oxygen saturation: chronic disease generates numbers that people live alongside for decades. The lesson from the CGM world is that this data should behave less like a document you open and more like the weather: ambient, glanceable, and shareable with consent, on whatever screen happens to be nearby. Builders in health tech should count the glances they made cheap. Patients are already counting.

Irakli Kurtanidze is the founder of Sugar Sense, a cross-platform CGM companion app, and has lived with type 1 diabetes for more than 12 years.

By JOHN SAMARAS

A US retail pharmacy pays $1,302 to acquire one month of branded Wegovy. That figure comes from the Centers for Medicare and Medicaid Services National Average Drug Acquisition Cost file, effective August 19, 2026, for the 25 mg oral tablet at 30 tablets a month.

The cheapest cash price I verified on a seller’s own published page, for the same month of the same product, is $299. That is oral Wegovy at the maintenance dose, at Sam’s Club Member Health, which sells at the manufacturer’s published self-pay price, checked August 31, 2026.

The two numbers are more than a thousand dollars apart.

Where the second number comes from

Every Monday I check what each US GLP-1 telehealth program publishes as its price, on the program’s own page, and record it. Not the advertised starting rate. Not the prepaid annual plan divided by twelve. The all-in monthly cost of staying on the drug at a maintenance dose.

This month that record turned into an index. Across a fixed panel of 11 programs the median all-in price was $348 a month in August, the same figure in all five weekly checks. It did not move against July.

One program cut its price in August and none raised one. GoodRx for Weight Loss went from $388 to $338 on August 31, and it sits outside the panel. Three other apparent cuts in the record were mine rather than the programs’. Ivim Health and Sesame Care were sitting on prepaid plan rates, and my Costco through Sesame row was carrying $408 for a plan that was $398 all month. Putting each on the rate a reader can start on today lands in the series as a step. The revision log on the September release itemizes all three. The cheapest verified compounded semaglutide route held at $178 a month, at Mochi Health, which posts one flat all-in price at every dose. Sam’s Club Member Health was the cheapest verified branded route at $299 for the Wegovy pill. Both figures were checked on August 31, 2026.

The method fits in a paragraph. For the floors, take the lowest published all-in price in each route on every Monday of the month, then take the median of those weekly lows. For the median, take the middle of the fixed panel each Monday, then the median of those five weekly figures. The panel is fixed on purpose, so a change in which programs I track cannot read as a change in price. The number sits at a dated URL and does not change after publication. A correction becomes a numbered revision with a note.

NADAC measures acquisition cost

The distance between $1,302 and $299 is not pharmacy margin. NADAC measures what pharmacies pay their wholesaler. It says nothing about dispensing costs, the clinician visit, shipping, or what a manufacturer charges through a channel it owns.

46brooklyn Research has published NADAC dashboards free since 2019, and every derivative here rests on their work. What I added is the join: their acquisition data against verified consumer cash prices, which nobody had put side by side.

The two prices sit in different channels. Insurance routes a patient into the pharmacy channel, where the $1,302 sits. The $299 is a cash price, paid by a buyer with no coverage.

The packaging gap

The same NADAC file holds a second finding. Lilly sells Zepbound both as single-dose pens and as a multi-dose KwikPen. At 15 mg, a pharmacy pays $672 a month for the KwikPen and $1,051 a month for the equivalent single-dose pens. The only difference is the container. The spread is 1.56x, or $379 a month. At the 2.5 mg starting dose it is $482 against $1,052, or 2.18x.

Why nobody else has this number

Prices in this category move weekly and nobody records them. A patient cannot tell an introductory rate from a maintenance rate. A reporter covering a price cut has no baseline to say whether it was a cut at all, and the only public numbers are the ones a manufacturer put in a press release.

The fix is somebody writing the price down every week and publishing the method with a version number on it.

Everything above is free to reuse under CC BY 4.0, with a link and no registration. The CSV and the JSON sit at https://glpchart.com/price-index/. If you want a different cut, by state, by drug or by program, ask and you will have it inside a day.

From October the release lands on the first Tuesday of the month. The next one is October 6, 2026.

John Samaras is the founder of GLP Chart, which verifies the cash price of every US GLP-1 telehealth program every Monday. He writes about price, coverage and market structure, and leaves the clinical questions to clinicians.

The panel is Liz Powell, an attorney and Founder of both G2G Consulting and Women’s Health Advocates, and former Capitol Hill staffer; Dr. Elizabeth Garner, CEO of Sena Therapeutics, former CSO for Ferring, and past President of the American Medical Women’s Association; and, Dr. Mitzi Krockover who founded both Women Centered and Femtech AZ, and is an investor serving as Managing Director of Golden Seeds

What’s going to be the impact of politics, policy and the mid-terms on Women’s Health? Hear from these advocates, as they reference this summer’s blockbuster!

The transcript (made by Youtube and Claude so blame AI for any mistakes!)

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Hello to everyone, and welcome to a special episode of Matthew Holt’s THCB Gang. My name is Audrey Cronin. I’m a communications advisor in healthcare and technology and a passionate women’s health advocate. I’m so pleased to be joined today by a powerhouse of women healthcare leaders. But before we start, a big thank you to Matthew Holt, who, in a rare tender moment, offered to have me be the Rosie O’Donnell to his Jimmy Kimmel.

Today’s panel is made up of thought leaders in women’s healthcare policy, investment, and life sciences and medicine. What we all have in common is that we are all part of Women’s Health Advocates, the nation’s only bipartisan lobbying organization that advocates at the federal and state level to advance women’s health, head to toe.

The 2026 midterm elections are upon us. We’re all reading about it — it’s here. The current split of the Congress is 218 Republicans, including one independent, and 212 Democrats. State by state, who sits in Congress matters, and matters profoundly to women’s health. This is why we’re here. By now, most understand that women make up 51% of the United States’ population. Yet women’s health remains underfunded, under-researched, and overlooked.

Like Odysseus in the Odyssey — yes, I’m going there — we are on a journey, this one to overcome obstacles and fragmented factions with advocacy and education that is proven to have the power to influence policy change, shape women’s health, and save lives. Today we’ll talk about these obstacles, opportunities, and what we can expect with the results of the midterm elections and women’s health going forward.

Our panel today includes Liz Powell, Dr. Elizabeth Garner, and Dr. Mitzi Krockover. I would love for you to introduce yourselves. Liz, would you like to go first?

Liz Powell, Founder, GDG Consulting and Women’s Health Advocates

Sure, happy to. Thanks so much. Liz Powell. I’m the founder and head of both GDG Consulting, a lobbying firm in Washington, and Women’s Health Advocates, which we just launched in February of 2025. And I’m a former Capitol Hill staffer. Beth, want me to go next?

Dr. Elizabeth (Beth) Garner, CEO, Sen Therapeutics

Sure, yes. Hi, Beth Garner. I’m a women’s health physician by training — an OB/GYN and a gynecologic oncologist. I jumped into industry about 20 years ago to help women by developing therapies for women, and I’ve been in women’s health all that time. I’m now CEO of Sen Therapeutics. We’re developing therapies for PCOS.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Great. Mitzi, thank you.

Dr. Mitzi Krockover, Director of Women’s Health Innovation, ASU College of Health Solutions

Great to go on this odyssey with all you lovely women. I’m really excited about that. I am Mitzi Krockover. I’m an internist by training and previous practice. I was the founding medical director of the Iris Cantor UCLA Women’s Health Center, and then went on to Humana as vice president of women’s health, and now I’m very immersed in the innovation space, because we need more solutions for women’s health. I am currently the director of women’s health innovation at the ASU College of Health Solutions, and co-founder of FemTech Arizona, creating a hub for women’s health innovation here in the state of Arizona. I literally want to be invested in women’s health, so I am a managing director at Golden Seeds, an angel investment organization, and CEO of Women Centered, which is a media and women’s health strategy company.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Wow, wonderful to have you all. So, Liz, I’d love to start with you. Can you tell us more about why you started Women’s Health Advocates, and secondarily, as a lobbyist in Washington, DC, can you share the women’s health policy changes that are being legislated today and are the most high-stakes, as well as the role policy plays in innovation? So, two big questions.

Liz Powell, Founder, GDG Consulting and Women’s Health Advocates

Yeah, absolutely. Most people don’t realize that women and people of color were not required to be included in clinical trials until 1993. So there have been huge gaps in the data that informs medical decision-making to this day. When a woman presents in the ER with a heart condition, she’s twice as likely to die afterward, because we just don’t have the data. A lot of doctors aren’t even trained on appropriate data on women, and sex differences go down to the cellular level.

As a lobbyist and somebody who works in Washington, what I started to see, instead of a gap here or there, was consistent gaps that needed to be addressed. Whether it’s inclusion in clinical trials; research funding for women’s health, which is defined as those conditions that solely, disproportionately, or differently impact the health of women, head to toe, over the lifespan — so, more research dollars and investment there; or the regulatory process, making sure that new women’s health innovations are able to get through FDA to reimbursement. If you’re not reimbursed or don’t have coverage, then the innovation never reaches patients. And finally, there’s access. You can have the greatest innovation in the world, but if you’re not reaching rural America, for example, then we’re not really being effective in advancing health for women.

Having a greater understanding of all those gaps is what gave me the idea to start Women’s Health Advocates. I’d been teaming up with Mitzi and Beth for years, addressing different gaps in women’s health, and we decided we needed all of women’s health, head to toe, to be addressed through a lobbying organization. We are the only lobbying organization that is educating and advocating to close those gaps in women’s health, head to toe, over the lifespan.

What’s been amazing is that we organized the first-ever Women’s Health Capitol Hill Day — you can see behind me all the smiling faces. We’ve brought people to Washington several times now to do these Hill Days. We’ve done online events. We’ve done events across the country, 25 at this point, coast to coast and in between. What we were finding is that there’s huge energy and interest in taking action and better understanding these gaps and then doing something about it. And how do we do something about it? We’ve got to advocate. We’ve got to use our voices. And we have to get out and vote.

This year’s midterm elections are going to result in at least a 16% changeover in Congress. It’ll be more than that, because there are about 21 toss-up seats. So there’s going to be big change, and if we can make women’s health a priority for candidates and those who are in office, then we can really shift the ground. We can really transform research, the FDA approval process, reimbursement, and address all these specific health conditions. So I’m very excited about what I’m seeing so far across the country: all 50 states, over 5,500 advocates. We are really raising our voices and making a difference.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Amazing. All right, Beth. Now I’d love you to tell us how you define women’s health, and why this definition is so important given today’s climate and the ongoing challenges for women and the conditions we face, as Liz talked about, at every stage of life.

Dr. Elizabeth (Beth) Garner, CEO, Sen Therapeutics

Yeah, thanks so much. As Liz said, definitions are always important, wherever you are, and certainly when we’re talking about policy and speaking to members of Congress who are making really serious decisions about our health. It’s critical for us as women’s health advocates to ensure policymakers understand what women’s health actually is. That’s really important for us, and it’s even more important in the current climate, as we have so much work to do to ensure that women’s health is top of mind.

We now think about women’s health broadly — Liz basically said that — as way more than reproductive health, or, as some of us call it, “boobs and tubes.” We’re not boobs and tubes. We are way more than that. Women’s health really encompasses the full arc of a woman’s life, and the physical, the mental, the emotional dimensions of our lives, from birth through death. And along that journey, women deal with a number of conditions that we now think about in three buckets, and these are the definitions that we talk about. There are conditions that affect only women, such as endometriosis, as an example. There are conditions that disproportionately affect women, such as Alzheimer’s. And then there are conditions that differentially — differently — affect women, such as heart disease.

As you heard from Liz, I think we do have a better understanding of women’s health now, because we think about these conditions in these three buckets. But unfortunately, I would say we’re just really far away from actually addressing women’s needs, no matter what color or ethnicity they are, where they live, how much income they have, and so on. The disparities across the US and around the world are enormous. So I think we’re doing a great job in terms of definitions and getting policy people to really understand, and this is really where, as Liz has said already, advocacy comes in.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Great. Thank you for that. Mitzi, do you want to talk about policy impact and what solutions get to market for women, and what can be done to encourage the creation of legislation that gets evidence-based — importantly, evidence-based — products to market faster?

Dr. Mitzi Krockover, Director of Women’s Health Innovation, ASU College of Health Solutions

Sure. I just want to piggyback on some of the things Liz talked about. When you look at the continuum of innovation, or solutions, it’s really a pipeline, if you will. It starts with good research, and then that good research informs evidence-based solutions. Those solutions need clinical trials in order to prove their efficacy or their outcomes, and then they go through a regulatory process if it’s a device, a diagnostic, or a therapeutic. Then it has to be adopted into the health system, and mostly it’s only going to be if somebody’s paying for it, covering it, or reimbursing for it. And then it has to be adopted into clinical practice, and that’s by training and awareness by the physicians themselves. In every area I just talked about, there is a policy implication.

If we look at women’s health research, as Liz talked about, we have a dearth of information, because we didn’t really start including women and other underrepresented groups until 1993. So we’re behind the ball. Now, two years ago, unfortunately, women’s health got conflated with DEI. So now we have researchers whose research is being denied funding because they are studying women, or they’re studying a woman’s body parts, and they’ve had to be very creative in the way they’ve talked about it. It’s really made an impact on the research that’s becoming available in women’s health. So we need to focus on that.

The second area is that these innovators need support for their innovations and clinical trials. There are things like grants that have been available to what they call small businesses, and again, because of the conflation of DEI with women’s health, some of those have been taken away. So we need to be very cognizant of that issue.

And then, finally — not finally, but — reimbursement. We know that certain procedures that are similar between men and women, the ones done on women actually get reimbursed in some cases less. So if you’re a health system or provider, what are you going to do? You’re not going to do the women’s procedure, you’re going to do the men’s procedure. So we need to focus on that, as well as coverage decisions for insurance. Where that really makes an impact is that Medicare and Medicaid, the government-backed insurance, really dictate what commercial insurance will cover. When they make decisions, and that’s a policy decision, commercial follows.

Finally, we can also have an impact on medical education dollars, as to what is taught in medical schools and in training, and so that’s also a policy decision. If we make a decision to make physicians aware of these new innovations, as well as women’s health in general, then we’ll be better served. As you can see, all along the pipeline is where policy really makes a difference, and where we have opportunities to really benefit everyone.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Wow. I love how you strung that all together, and where policy intersects every time. It’s so exciting to be part of this, and we’ve got a lot of work to do. So thank you for taking us all the way through that.

Dr. Mitzi Krockover, Director of Women’s Health Innovation, ASU College of Health Solutions

Taking you on that journey, right?

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Yeah, we’re on a journey. Absolutely. So, Beth, back to you. Can you tell us about your experience as an entrepreneur, how you see private-sector funding as it relates to policy, and what the landscape looks like for women’s health?

Dr. Elizabeth (Beth) Garner, CEO, Sen Therapeutics

Yeah, thanks for that. As the CEO of Sen Therapeutics, my experience as an entrepreneur has really been grounded in identifying an important unmet need and then building the company, the team, and the partnerships necessary to address it. Of course, entrepreneurship requires vision, but it always requires discipline as well, resilience, and a willingness to keep learning and adapting. Ultimately it’s about translating a compelling scientific or clinical opportunity into something that can actually improve patients’ lives, which is what we’re all after here.

I view private-sector funding as an essential partner to public policy. Policy, as you’ve heard, can help define priorities, can certainly remove barriers here and there, can encourage innovation, and ensure, of course, that patients’ needs and public health remain central. Private capital provides the resources and the expertise to turn promising research into therapies, companies, and solutions that can then reach patients. So the two are most effective when they work together — when policy creates the right environment for innovation and private investment helps move that innovation forward.

I would say the landscape is changing. There is growing recognition of the significant unmet needs in women’s health, and I’m hearing that every single day. As a person who’s financing — getting money for — women’s health, it’s changed for sure over the years, which is exciting. We’re seeing increased interest from entrepreneurs, investors, researchers, and policymakers. But I think we need to make sure we sustain that momentum, with better data — you’ve just heard about data already — more inclusive clinical research, and funding models that support companies through that long, very complex process of developing a therapy. So for me, the opportunity is not simply to build a successful company. It’s to help advance a healthcare system that takes women’s health seriously, invests in the science, and gets us better outcomes for women across their lives.

Audrey Cronin, Communications Advisor, Healthcare and Technology

Great. Well, thank you for all that you’re doing. That’s exciting and so important. So let’s get back to Liz, on specific critical issues related to endometriosis and breast cancer legislation, because we have research funding and the EARLY Act. I’d love to have you talk more about what we might expect from outcomes in those spaces.

Liz Powell, Founder, GDG Consulting and Women’s Health Advocates

Yeah. I would love to start with a thank-you to our advocates. We did a big push for the EARLY Act, which funds and reauthorizes screening programs for women, and we got that to pass the House. Now we’re waiting to see if it can pass the Senate. They’re not in session this week, and they have very little time left before they’re out completely for the elections, so it’s unlikely that things will move before the elections. At the end of the year, when they come back after November 3rd, that is when they’ll have to figure out a lot of these bills. So we have been working to continue to educate and advocate for the EARLY Act.

We’ve been working on endometriosis, as you mentioned. We’ve done a couple of letters to the Department of Labor for workplace protections. We just did a letter with Congresswoman Williams to HHS, Health and Human Services, around reimbursement gaps for endometriosis. It’s the same code and same reimbursement rate for ablation, which takes 30 minutes, versus excision, which can take four, six, even eight hours — which is insane, that we’re disincentivizing the gold-standard care. And many other issues we’re working on. We were also excited to see the IMPROVE Act pass the same night in the House, which addresses maternal mortality and maternal health issues.

So there’s lots of legislation that we see as non-controversial. It’s just about having the time to get it onto the schedule, and we could see it getting through at the end of the year. We will certainly be advocating, and sometimes they’ll just put it all together on an omnibus. They have to get the 12 appropriations bills done, so it’ll likely be a big bill that will include all of it.

The other factor is how the elections swing things. Do we have a sudden change in control? Many are thinking that Hakeem Jeffries will become the new Speaker in the House, and if that’s the case, they may punt it to next year, when the Democrats have more power to do it. Either way, in the House the chamber is so razor-thin that it doesn’t really matter — you’ll need both sides to get a lot of things through. So it’s not going to be a huge shift. If it does shift power, it’ll just be a little bit of a shift, but that does give them some power to do things, and gives them control of the gavel of the committees, and so they’ll do, I’m sure, lots of investigations. There’ll be a big dynamic change in the committees.

For the Senate, it’s still up in the air. It’ll be tight for Democrats to take control of the Senate, but either way we expect the chamber’s margin to be closer between the two. All that impacts what legislation can be worked on. So are we going to see a huge $200 billion increase for women’s health research? Unlikely. But could we see other changes? Could we fix the reimbursement challenges Mitzi is talking about, the gaps in care, in access, in rural health? There are a lot of good issues we could be working on in women’s health that are very bipartisan, that no matter who controls, we will certainly be working to make a priority.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

I have to say, Liz, every time I hear from you, I always feel better about things. So thank you.

Liz Powell, Founder, GDG Consulting and Women’s Health Advocates

Optimism.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

You’re a force, and I appreciate you so much. You talked a little bit about maternal health. Mitzi, can you talk more about our country’s maternal health policies and where we currently stand?

Dr. Mitzi Krockover, Director of Women’s Health Innovation, ASU College of Health Solutions

Yes. It makes me sad — not maternal health, but our outcomes. We are at least 24th, if not worse, when we look at all of the other developed and non-developed countries when it comes to our maternal health outcomes. And Black women have a three times greater risk of dying than Caucasian women. We need to do better, obviously, and that also provides us opportunity. It’s not just a care problem, it’s a prevention, screening, and access problem.

We have, I believe, one out of three counties in the United States that are OB deserts, which means there are no obstetrical services at all. We see a number of hospitals closing their labor and delivery units because of low reimbursement and resources, and obviously our rural health residents suffer the most, but in every state, everywhere, we really have a dearth of access.

Here’s the good part: innovation can help, right? Through telehealth, through remote monitoring, we can identify things faster so we can get more treatment to the women who need it. AI-enhanced information, both for physicians and for women. And again, in all of those areas, policy really makes a difference. Forty percent of births in this country are covered by Medicaid, which is government-sponsored insurance. So obviously when Medicaid gets cut, those women are impacted, but when it gets expanded, they’re also impacted in a positive way.

There was also something called Medicaid expansion that was provided to the states a few years ago, and that means there’s coverage for that fourth trimester, that year after birth, where you can identify or treat issues that came up during pregnancy, like preeclampsia and hypertension, diabetes, mental health issues. So important. And we’re seeing that. Those states that adopted that expansion actually had better outcomes. So those are positives.

Then, to the extent that we can support the innovation, that again creates opportunities for access for women, with remote monitoring, telehealth, diagnostics, point-of-care — what we call where women can actually do a diagnostic test themselves. All of those have an impact. And the final thing we talked about earlier was reimbursement. There’s a new policy where it used to be that you’d get kind of one-size-fits-all reimbursement as a provider for an obstetrical case, and now they’ve unbundled it, so that if you have a higher-risk or higher-need patient, you actually get paid for that. That should hopefully help a bit on that reimbursement and coverage issue.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Great. That’s great. So, Beth, Mitzi touched on Medicaid and Medicare. Do you want to talk more about the impact of CMS and why it’s so important to health insurance?

Dr. Elizabeth (Beth) Garner, CEO, Sen Therapeutics

Oh, certainly. The Centers for Medicare and Medicaid Services plays a truly foundational role in the US healthcare system, as I think all of us know. Its decisions affect how millions and millions of people access and pay for care. As it relates to health insurance, it helps define the rules of coverage and reimbursement, as you’ve heard from Mitzi, and its policies of course influence which services and therapies are covered, how providers and insurers are paid, what quality and value standards must be met, and how affordability and access are addressed.

It’s also important to know that CMS decisions — and I think Mitzi, you already said this, but I’ll say it again because it’s really important — generally have a broader effect on the whole healthcare market by establishing precedent and shaping expectations, meaning commercial insurance pretty much generally follows CMS decisions.

Some important areas to be aware of: Medicaid covers about 42% of all births, which is amazing, and just considering what we just heard about birth and women and their babies, it’s critical that we address these horrific disparities between women of color and Caucasian women. Better coverage is clearly, badly needed. You also heard from Mitzi — I’ll say it again — about differences in reimbursement rates for surgical procedures for male and female patients. This is absolutely not okay and we must address this disparity, and thankfully we have Jocelyn Fitzgerald, who’s an amazing physician and a member of Women’s Health Advocates, working very, very hard on this. So that’s really exciting.

For companies like mine that are developing new therapies, CMS is also a critical stakeholder. There’s FDA, of course — we have to get our products approved, and that tells us that a therapy is safe and effective for its intended use. But coverage and reimbursement is what ultimately determines whether a patient can realistically access our products. So that’s really, really important, and it means innovators need to think early about their evidence. What are they going to bring to CMS regarding clinical efficacy and safety, real-world outcomes, the health economics, the patient impact, the value to the healthcare system? Many companies, especially startups, really don’t understand that, so I continue to talk about thinking about that very early in development.

CMS also has an important role in advancing health equity — or at least it should. Its policies can help address disparities in access, improve quality across populations, and ensure that innovation reaches the patients who need it most, not only those with the greatest ability to pay. So from my perspective as an entrepreneur, CMS is not simply a regulator or payer. It’s one of the key institutions shaping the healthcare ecosystem, and understanding its role is really essential to developing solutions for women that are not only scientifically meaningful but also accessible, affordable, and sustainable within the healthcare system.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Wow, we’re all fired up.

[laughter]

Go ahead, Mitzi.

Dr. Mitzi Krockover, Director of Women’s Health Innovation, ASU College of Health Solutions

That’s okay. I just want to underline something, because Beth can actually speak to this much better than I can. A place where I think, again, it’s a great example of policy working is something called breakthrough designation. The government has decided that there’s something that really needs solving that hasn’t been solved before — maybe it’s osteoporosis, for example — so they give basically an expedited approval process. Not less rigorous, just a little bit more expedited. And then if it meets all the criteria, it can be reimbursed by CMS, or there’s a code given to it. That’s a great example of how the government and innovation work together to get solutions to individuals more quickly. We have so many gaps in women’s health, and I’m hoping to see a lot more breakthrough designations in the future. Beth, I don’t know if you want to comment on that.

Dr. Elizabeth (Beth) Garner, CEO, Sen Therapeutics

No, it’s a great point. Yeah. The RAPID program is what’s pending right now. There’s an open rule to comment on, to close that gap.

Liz Powell, Founder, GDG Consulting and Women’s Health Advocates

Exactly. So, two additional points I just wanted to add — Beth, you got me fired up. One is menopause and perimenopause. When women go in to see their doctors, there is a copay, and many of us are working to eliminate that copay, because it is essential. There are so many things happening, and it’s not just hot flashes and brain fog. You are suddenly at much higher risk for heart disease, autoimmune conditions, and many others. We need to educate and stop the current practice of many women seeing eight or ten different doctors before they finally get HRT, or whatever care they need. So we need to have no copay for that, and we need to have better resources.

The other thing I wanted to point out, just to make a fine point on this, because I think people don’t realize: the reimbursement rate for equivalent surgical procedures is anywhere from 30 to 150% higher if it is a male patient. Let that sit. That is unacceptable, and that is hurting patients — not just the one getting the surgery, but future patients. Because if you can’t afford to do these surgeries, whether you’re the doctor or the medical facility, you’re going to do fewer and fewer of these surgeries, and eventually you’re just going to shut down that wing completely. That’s going to hurt all women. So I just wanted to make a finer point on that one.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Well, I cannot believe we’re here and we hadn’t talked about menopause yet. So thank you for that.

Dr. Mitzi Krockover, Director of Women’s Health Innovation, ASU College of Health Solutions

And osteoporosis.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Yeah. So important. And, Liz, this is, I think, a final question, although I’ll open up at the end if there’s anything you want to add. Back to the midterms: there are so many issues we have to tackle, so many things we just talked about. What do you expect to happen, what are some races we should be watching and how do they impact the industry and patients, and what interesting candidates do you think we should be looking at?

Liz Powell, Founder, GDG Consulting and Women’s Health Advocates

Well, I certainly hope more and more candidates are talking about women’s health issues and seeing that the broad definition of women’s health really is impacting their constituents. We’re working to help shape that. We’re doing voter education efforts. We’ve been doing this whole amazing initiative that Mitzi took the lead on, called My Vote, Our Health — a five-part series. We’ve got another one coming up on September 24th and then the final one in October, so tune in for that.

We are also tracking the elections and evaluating those top races, and I think there are some really interesting candidates and elections. In Arizona, we have a physician running. In Iowa, you’ve got not just two House seats but the Senate seat, all of those toss-ups. Ohio suddenly now has two toss-ups, plus the Senate race is a toss-up. Pennsylvania has three toss-ups. Michigan is really interesting: two on the House side that are toss-ups, and then the Senate race is proving different than what people thought, because Abdul El-Sayed, who’s the far-left candidate but also a physician, won the Democratic nomination, and Mike Rogers is an incumbent — a former congressman, pretty moderate, actually. When I worked on Capitol Hill, he was in office and we worked together on a lot of things, so that’ll be an interesting race that could really go either way.

So there are a lot of races to watch, a lot of states to watch. No matter what, though, we are making sure people understand that women’s health is bipartisan. Women’s health impacts all of us. It impacts our economy. We are hoping to drive people to vote for women’s health: talk to candidates about women’s health, what they think about women’s health, and then make sure that you vote for women’s health.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Great way to end it. Is there anything we didn’t talk about, panelists, that you’d like to add? I always like to open it up.

Dr. Elizabeth (Beth) Garner, CEO, Sen Therapeutics

I would like to just underline a little of what Liz was saying. I think we’ve had this thread before, but I want to say it explicitly: women’s health is not a nice-to-have. Sure, we all want better health for everybody, but it’s really an economic imperative. It impacts the workforce, it impacts our economy, it impacts our healthcare and healthcare costs. And we have the data, if anybody needs that to believe it. McKinsey did a report, now very well known, that if we were to close the gap in women’s health, we would get a $1 trillion return on investment annually by 2040 globally. In the United States, that translates to $295 billion. I don’t know about you, but I could do a lot with that kind of money. If we had $295 billion, we could do so much. But it’s also imperative for us as a country. It increases our productivity, it increases our competitiveness. Women are the majority of caregivers, who do it for free. If we don’t have women, who’s going to care? As well as reduce healthcare costs. So when we talk about this, it’s really something that doesn’t just benefit women, it benefits everyone.

Dr. Mitzi Krockover, Director of Women’s Health Innovation, ASU College of Health Solutions

And you can get rich off it. A hundred billion dollars in ROI from women’s health investments over the past 25 years — trillions of dollars globally.

Dr. Elizabeth (Beth) Garner, CEO, Sen Therapeutics

Oh, okay — that’s the Oriana report?

Dr. Mitzi Krockover, Director of Women’s Health Innovation, ASU College of Health Solutions

Well, okay, but the Aoa Dx study is what I’m quoting. They found that, by just studying all the exits and making sure they’re classified correctly, a hundred billion dollars in ROI has already been earned. People are wealthy today because of their investments in women’s health, half of that in just the past five years, and it includes 27-plus unicorns. So if you don’t care about any of that, you can make money. Just think about it that way.

[laughter]

Do well and do good.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

There you go. I want to say that this is so interesting, and the timing is so important, because we’re heading into the midterms, so there’s so much for us to be advocating for. We will be having Liz on the main stage at HLTH after the midterms, and I know you talked about the analysis you’re going to be doing, so stay tuned for that as well. We may come back and do another webinar after.

Dr. Mitzi Krockover, Director of Women’s Health Innovation, ASU College of Health Solutions

Can you share the title? I love the title.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

The title of this webinar, or —

Liz Powell, Founder, GDG Consulting and Women’s Health Advocates

No, my talk: “What the Elections Just Decided for Women’s Health.”

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Right, so that’ll be a packed house, I’m sure. And then I just wanted to say — unless, Liz, you want to talk about what people should do if they want to take action, or do you want me to take that one?

Liz Powell, Founder, GDG Consulting and Women’s Health Advocates

Yeah, go ahead.

Audrey Mann Cronin, Communications Advisor, Healthcare and Technology

Okay. If you want to take action, please visit the Women’s Health Advocates website, where you can join our community, write to Congress, join our steering committee, and donate.

[laughter]

Thank you. This was amazing. I’m so grateful that you joined me today, and for all that you’re doing, and I look forward to hearing more. So thank you so much again.

Liz Powell, Founder, GDG Consulting and Women’s Health Advocates

Thank you so much. Appreciate it.

Transcript of Interview with Priayanka Aggarwall MD (2nd half of video. First half you need to watch!)

Matthew Holt: Hey, Matthew Holt, quick THCB, spotlight. And this is a bit of an adjunct to the, work I’ve been doing trying to figure out how the new, big LLMs like, Anthropic’s Claude and OpenAI’s ChatGPT are now working their health angle and getting health records. And I’m very lucky to have with me Priyanka Agarwal. Priyanka is a, UCSF trained MD who is the CEO of HealthEx, which does what exactly, Priyanka?

Priyanka Aggarwal: Yeah, thanks so much for having me, Matt. So HealthEx helps, individuals access and share their health records at the moments that matter in their health journey. I’m really excited about the year that we’ve had, the work that we’re doing, and the folks that we’re live with.

Matthew Holt: I know you’ve been at UCSF a while, but you’ve a relatively new company. I think you got founded just two years ago. Is that right?

Priyanka Aggarwal: HealthEx has been around for about four years, so-

Matthew Holt: Okay. and you got funded from, General Catalyst. When was that? You got a decent round.

Priyanka Aggarwal since the beginning, four years ago.

Matthew Holt: So, okay, so I’m a, I’m a little out of date. So couple of things. There are a lot of companies that have been doing this kind of thing, right? Getting data and bringing it together and using it for various purposes, and it’s never really taken off a, sort of, as an area. In fact, people have been doing personal health records since God knows when. I was in a personal health records company in 2000, so it’s – not a new idea. obviously the introduction of these massively now popular consumer LLMs, particularly the big three, Gemini, ChatGPT , and Claude, you know, changes the game a bit.

How did you get involved with, Anthropic, and what was the… How did, how did that come to… I mean, why, why did they choose you?

Priyanka Aggarwal: Well, just in terms of how I came to this space, so as a physician, I really lived a lot of the challenges both in my patients being able to access their health data and seeing all the delays that folks face in their everyday care when, you know, you’re waiting for biopsy results to start cancer treatment.

You have a complex patient admitted to the ICU, you don’t know what’s happened to them. so I lived a lot of those challenges, of course, as a physician, as a patient. I also, spent time in the life sciences trying to do research and, support patients with complex rare diseases and trying to do things like developing a patient registry to understand how folks are doing.

All of that was really difficult. And so I lived a lot of the challenges in accessing patient data and, you know, I think at the time, a lot of the focus, if you really look at the last 20 years of interoperability, it’s been on institutions, how do we figure out the rules between, health systems and different organizations?

And I think all of that work has been really important but, , I really kind of experienced that that missing link of the patient or the individual really, wasn’t there. And so thought that there was an opportunity to, really bring in the voice of the individual. It is, of course, our own health data.

And so giving folks that opportunity to access their health records, share it in the moments that matter in a myriad of interesting ways, I thought that that was an interesting opportunity. And I think the timing was good because if you look at some of the work that’s happened with patient access across TEFCA, across the CMS Align networks, I think there’s been- A lot of support at the federal level for this work.

And then, you know, as you called out, I think with LLMs and just the explosion of digital health apps, there’s of course many interesting ways for folks to use that data. not discounting, of course, the importance of sharing that data with your doctor or your health plan as well.

Matthew Holt: Yeah. And, speaking as somebody who’s right in the middle of that, and I’m actually gonna write this up as a separate thing for THCB readers, . It’s easier now to get the tech stuff. The images are, are still a struggle. Sharing images between different cardiologists at the moment is still an interesting thing. And there’s a lot of internal barriers within health systems. I wrote a piece about this in 2009 called Cats and Dogs, because cats like places and dogs like people, and we’re in a cat world for our health IT.

Still stuck in places, and moving it between places when you’re a person, is still tricky, and we kind of missed an opportunity I think back in 2009, 2010, ’11, ’12. But, that’s, that’s sort of water under the bridge, and now the LLMs are kind of giving us a new opportunity. So, let me ask you the question again. How did you get selected by Anthropic?

Priyanka Aggarwal: I was very interested in seeing the opportunity for companies like Anthropic and others to support individuals looking to better understand their health. We know that wait times to see doctors are continuing to increase.

There’s a tremendous need, for Americans to access healthcare in a more kind of timely manner. And so, certainly thought there was an opportunity for AI to support individuals. Of course, not to replace, their doctor in any way. And so, , I was able to meet with the Anthropic team last year. There was alignment in the vision and in the opportunity. And so I think, , a lot of the interest came together at the right time. We were also reaching maturity with, again, services like TEFCA and CMS. And so I think that shared vision, really, was, was additive, and the timing was right.

Matthew Holt: And you announced this actually, I think, back in, in January or the, or they announced it, you announced it, the combination. And to be honest, it kind of went a little under the radar because, Open AI announced something similar with B.Well. And they then didn’t… I think I was on their wait list.

I realized I could have got yours much earlier, I just hadn’t figured out where it was in the connector. But, but ignoring that for a second, kind of well done the the folks at ChatGPT Health for announcing that, you know, theirs was now open. I went and looked at theirs, did theirs, went, hang on, how is, how is doing Claude?

And that’s when I went through the process. So just on the nuts and bolts of how it works, currently somebody has to go into the settings and sort of activate the connector, I’m still a little puzzled by how you surface this for the individual consumers, ’cause there are already hundreds of millions of people on Claude, and maybe your other customers, I don’t know much about the others, but, figuring this out. But how does it work?

Priyanka Aggarwal: Yeah, absolutely. And I think different teams have made different decisions here. So as you said, within Claude, there’s a number of connectors that individuals can choose to turn on, and so HealthEx is one of those connectors and essentially the general idea is that, we want it to be really, a quick and seamless process. So the flow that we have modeled that lets individuals connect their health records is designed to feel, like a familiar flow, not too different from the way that you might connect your financial data, using Plaid or connect your Google Drive.

Of course, your health data is more sensitive, so there’s an added layer of security. But the idea is that when you click into the connector flow, you verify your identity, you consent, and then you decide what records you wanna pull in across all your providers. And then the process itself is relatively quick.

It should take most folks about five minutes or less. on the other side of it, the records are connected in almost real time and folks can start having conversations. And we’ve certainly invested a lot in making that flow user-friendly and ensuring that the data is connected in a really quick way.

Health records can be huge, and so we know in 2026, folks don’t wanna wait a couple of hours. They don’t wanna have to come back the next day. So we invested a lot in the data processing to make sure that the data was ready in a really timely manner.

Matthew Holt: And, and one more technicality. When you go into this, you get the choice of going in via Clear, which basically identifies that you are Matthew Holt and you’ve lived in these different places and- That, I believe, takes you down the path towards the end, the, the QHINs. They’re called QHINs these days, right? The actual- That’s right. Yeah … where, where you’re getting the data as if you were an institution without having to sign into the thing. Or you can go the way I did on the, on the little video which will be attached to this. That’s right. Yeah. So institution by institution, I just went to UCSF where I happen to have a ton of data at the moment and then I’m basically re-signing in, but now I guess some combination of, HealthEx, Fasten and Anthropic, depending on then you, you spend a little bit of this off the record.

Priyanka Aggarwal: That’s right. Yeah. And we’ve invested a lot in that flow being flexible, and so we basically let the user decide do they wanna so-called find their records automatically, and that is through IAL2 identity verification. We do that in partnership with CLEAR. And the benefit there is that we then find all of your records for you. And so if you’re somebody that has data at a lot of different places, you don’t remember all the names of the practices, that’s a really nice flow. If on the other hand, you know, and, and you called this out yourself, most of your data is at one institution, you know the login, you– maybe you don’t have your ID out for that ID verification, you can go through, just a, a more traditional FHIR endpoint flow.

And so we basically let our users decide, and we say, “Hey, do you want us to find your data for you? If so, you need to verify your identity, or do you wanna go through and find it yourself?” So the idea is that we wanna give folks kind of the right flow for them, and it’s gonna be different based on kind of you, your medical history, et cetera but we wanna basically put you into the right flow that’s gonna be the simplest for you.

Matthew Holt: Yeah, and I haven’t done the clear one. I did a similar one with a company called Pluto, which I’m adviser to a while back, and same sort of thing there. You could go and get it via the QHIN, and I don’t know which one they, were using at the time, but a lot of different data came from weird places, which, which I’d forgotten about

You know, the doctor’s visit in 2003 that you completely forgot about, but there it is. You know, that kind of thing. And, i actually will, before I publish this, go and do that version through, HealthEx and pull to see, see what else shows up.

Priyanka Aggarwal: Absolutely. Yeah. We’re, just one thing to mention. Yeah. We do match on historic addresses. Yeah. So it’s kind of fun because we might find an ER visit that, you know, you went to on vacation. For me, I end up with an urgent care visit I had in New York with an institution I never made a patient portal login. So it’s a nice way of getting, I would say, more complete records and not having to remember, all the clinic names, which can sound really similar sometimes.

Matthew Holt: So two last questions about, the relationship with Claude. So now the record’s there. So far all I’ve done is said, “Okay, hey, go find my report.” Now, props to you guys. I’ve asked the ChatGPT version of this would be well, , and said, “Hey, go find my report.”

And they could find the title of the report, but they couldn’t see into the report. Now, I’d actually already fed it, separate to ChatGPT, the actual text from the report. This was from, an angiogram I’d had recently, which amazingly don’t have heart disease despite being an obese, disgusting, , early 60s- quasi-American male who – eats too many cheeseburgers and has too many milkshakes. But anyway, I do have a valve defect, which is a separate issue, but genetic. Nothing I did. When I did this, on Claude, Claude could read the whole thing, and it came back and said, “Yes, you’ve got all this stuff going on.”

And I asked it, did, because I’d actually had previously fed a different chat the actual text of this, ’cause part of doing this I was just using Claude by copy and pasting into it. And it went, “No, no, this is, this is, that’s in another chat. I can’t see that one, but here’s what I’ve just read directly through using the bridge to HealthEx.”

So props to you guys. Now- Two questions. How much are you involved after that? I assume, and I haven’t done this yet, that at some point I will say to Claude, “Okay, figure out a way to give me all of my relevant health data in a record that’s not like a 2,000-word-long scroll chat.” There must be a, there must be a way they can format a health record for me.

I don’t know if they’ve done that. I don’t know if that is a part that you’re working on, or are you just the connection?

Priyanka Aggarwal: Yeah, no, we’ve, we’ve invested a lot in not just making the data available, but in serving it up in a way that we say is gonna be fast, efficient, and accurate.

So the thing is, health records are huge, as you know, and if you don’t do some processing, and if you don’t point the AI to the right portion of the record, you can run out of context window space after a question or two. It can be really slow in getting your answers. So the way that we’re serving up the data to Claude is through the MCP architecture.And so essentially, as you ask questions, we point Claude to the right portion of your record. These are a list of tools, and you might have noticed that you had to consent to each one as you were going through-… kind of the chat. And so that offers really nice privacy as well. So let’s say you just wanna ask about your medications, but you don’t want Claude to read your notes, you can then allow Claude to see portions of your record and not your entire record.

If you did wanna ask Claude for a visual summary, there’s a summary tool that we’ve built. And so, there is work that we’ve done to ensure that, A, you’re getting answers quickly, the answers are accurate, and the answers are also served up in a way that are gonna be, really making sense. And so that work is all through the MCP, and we’ve certainly invested a lot as a team. Anthropic is using the MCP. We have other folks in the AI space that are also using a similar architecture.

Matthew Holt: So this is essentially AI equivalent of APIs essentially to be able to, focus more on the right part. That’s right. And then, so you are kind of both doing the connection, but also building stuff within and in conjunction with Claude and Anthropic, and that’s, so that’s, super interesting.

I’m always trying to figure out how they’re, you know, working with other people to figure this out, and when does the, when does the, AGI get so smart it doesn’t need anybody else and doesn’t need us? But, that’s a separate topic.So, the business of, of HealthEx. That’s a great marquee, visibility with Claude.- You’ve announced a few other clients, but go back to where I started. A lot of people have tried this sort of, can we gather data together for consumers? It hasn’t ever really worked. As I mentioned, I was doing it 26 years ago. You know, I’m still not on my yacht. So, when you look at the, the business goals, where do you think you’re gonna get paid for doing this?

Priyanka Aggarwal: I mean, I think we’re in a really interesting moment for US healthcare. And again, you know, I think so much of the focus for the last 20 years has been on institutions. I think we’re in this interesting moment of consumer-driven healthcare where, you know, you do have services like ChatGPT, you have a lot of companies that are working directly with consumers. And I think people are really interested in managing their health, and they really have the tools to do so.

So maybe 10 years ago you could get the data, but you couldn’t do that much with it. And so now I think we’re in this moment where you have platforms like Claude, like Copilot Health, Whoop, and others, where, having that context on your health history is really meaningful. And so that to me is a lot of why I think the timing is really great right now, why this work is really important. I think people really do wanna manage their health, and doing that really starts with having your personal history with you ready to use, you know, with your doctor, with different AI platforms, with digital health apps. So, that to me is a little bit of why this is an – interesting moment, it’s an important moment, and where I think, you know, the hope is that we’re, finally gonna reach that point in time where people really do expect this.

You might have seen, Matt, that we launched what we call our HealthEx Wallet earlier this week. A lot of what we were hearing from patients and users is, “You know, I was able to connect my records with Copilot or Whoop or Claude, but I also wanna just see that data.” And so anybody that goes through our connector flow with, any of our partners, they can choose to return to HealthEx, they can see their data laid out in a timeline.

They can generate a QR code to share it with their doctor. So I think the hope is that people really see value in the work that we’re doing, they can use their data in really interesting ways, and that folks are really engaged in their health in a way that maybe they weren’t a few years ago.

Matthew Holt: And as a business, does that mean there might be a consumer business coming of this, do you think, DTC? Or you predominantly think you’re gonna be a business-to-business server

Priyanka Aggarwal: Our predominant model today is enterprises paying us. We wanna serve consumers in any way that we can, and so the wallet is just an effort to serve users. And, I think a big part of what we’re doing is founded on transparency and trust, so we want folks to know that, “Hey, I shared my data with Claude or with Copilot.” And so we also wanna make it really easy to turn off those connections. So folks can, of course, do that within Claude. They can also do that within HealthEx. So part of it is just making sure that we’re serving the user first party as well.

Matthew Holt: Yeah, Obviously, there’s a lot of back and forth about privacy and this, that, and the other. But I think that, the, key that I’ve, certainly since I’ve had my health issues and have been using these, as a user rather than observer, is that the value is very, very strong for my 20 bucks a month from Claude, I’m really getting a lot of help with the stuff that is just going around the doctor’s visits. And we know that even at the best of times, the health system is stressed, and at the worst of times it is very unresponsive. I won’t name, won’t name names, although I – I have and I will in the future here. But, so I think that the ability to make these LLMs and consumer tools easier for people to use and get more accurate data is, is just a great thing.

Priyanka Aggarwal: Yeah, absolutely. And I think- we also really want folks to have good information. So that’s my feeling as a physician, is these services aren’t meant to replace your doctor, but if they can help you as a patient be a lot more informed, be more prepared for when you see your doctor, that’s really the best outcome.

And I think we are hearing from folks that try these services that, “Wow, you know, I get so many labs with every chemotherapy visit. This is the first time I’ve really understood what those labs mean.” So that’s the type of feedback that we’re getting, and I think that’s really kind of the best outcome here.

Matthew Holt: Fantastic. Well, I’m looking forward to watching as this whole area and HealthEx, continues to grow and see how this impacts patient care in the health system. I’ve been talking with Priyanka Agarwal, MD. She is the CEO of HealthEx. Priyanka, thanks for your time today.

Priyanka Aggarwal: Thanks so much for having me, Matt, and thank you for trying out HealthEx.

Matthew Holt: Of course, I try all the stuff out. Everyone knows that. Usually it’s trouble.

By KIM BELLARD

With all the fuss about A.I. I was pleased to find some studies that illustrate that we don’t even fully understand the human brain yet. The ancient Greeks had a maxim “Know Thyself,” but the current research suggests they should have advised that we should “Know Thyselves.”

A new study from Stanford Medicine suggests that our brain is actually two separate organs: “…we postulate the brain is a composite organ emanating from two lineage-restricted progenitors; these dual progenitors may be evolutionarily conserved across 550 million years from hemichordates to mammals.”

Say what?

Now, let me make this clear: they’re not saying that the brain evolved from two separate organs into the brain we have today; they’re going a step further and saying there are still two separate organs, working together or in parallel. Freud must be feeling vindicated.

The press release says:

The new research finding shows that the human brain consists of two ancient nervous systems cleverly packaged together — a more primitive part that regulates our hearts’ beating, our breathing and other functions, and another that makes us distinctly human, capable of poetry, mathematics and wondering about our own origins.

“We’ve shown for the first time that the front of the brain arises from a totally different progenitor cell than the back of the brain,” said Kyle Loh, PhD, associate professor of developmental biology. “Our discovery means that we can now grow neurons from the back of the brain, the hindbrain, in a petri dish and study their functions.”

If you’re wondering why growing neurons from the hindbrain matters, it turns out that diseases that impact the brain stem, such as spinal muscular atrophy (also known as SMA) and amyotrophic lateral sclerosis (also known as ALS or Lou Gehrig’s disease), have been hard to study because of the difficulty of growing such neurons in the lab. The researchers discovered the hindbrain follows a separate developmental path, running in parallel to — rather than branching off from — the pathway that creates the forebrain and midbrain.

“Previous attempts to make hindbrain neurons likely tried to coax forebrain and midbrain progenitors into hindbrain cells, which our study shows is not possible,” co-first author Rayyan Jokhai said. He added: “Now we have a model to better understand these devastating diseases, and work toward regenerative therapies for them. This is a very exciting new frontier in brain research.”

The researchers looked at various organisms and found that the separate systems date back over 500 million years. “Our research suggests that evolution took two existing neural systems and pushed them together spatially,” Professor Loh said. “Having the brain as one organ would probably be more efficient, but we rely on this primordial way to make the brain as two separate pieces.”

“I was surprised at our findings because the word ‘brain’ implies a contiguous organ that likely has a singular origin,” Mr. Jokhai said. “But even 500 million years ago, there were these separate neural systems, which now almost operate as one, which is very cool.”

Very cool, indeed.

Meanwhile, up the road a few miles, researchers at UCSF and UC Berkeley have shown, in real time, the brain essentially arguing with itself. They studied patients who had electrodes implanted for surgical evaluation of epilepsy, and used those to watch the brain trying to decide to do something or not. They discovered – you guessed it — two neighboring patches of the brain that signal in opposite directions, one pushing toward “do it,” the other toward “don’t.”

“We’ve long suspected that this region was where the brain weighs reward against risk, but we’ve never been able to measure it while it is happening in the human brain in real time until now,” said Edward Chang, MD, Joan and Sanford I. Weill Chair of the Department of Neurological Surgery at UCSF and co-senior author of the study.

The researchers had participants play a video game where they had to navigate a maze with bomb-filled hallways, posing varying degrees of risk. As they reached decision points, the researchers identified two distinct areas of the brain firing; region near the middle of the eyebrow was connected to a risky choice, while a patch about two centimeters over, toward the side of the eyebrow, did the opposite.

“Most models of decision-making assume the brain gradually ramps up evidence until it crosses a threshold, like a dial slowly turning,” said Robert Knight, MD, professor of Psychology and Neuroscience at UC Berkeley and co-senior author. “What we saw instead was more like a switch flipping back and forth, oscillating between two extremes until one held.”

The researchers believe that their discovery could help conditions where people have an imbalance between risk-taking and caution, such as depression, OCD or gambling addiction. Co-author Clara Starkweather, MD, PhD, a neurosurgery chief resident at UCSF, who designed the video game, said: “Right now, psychiatry mostly relies on asking people how they feel, I want to give it something more objective: a real, measurable signature of how someone’s brain weighs risk, so treatment can target the specific circuit that’s off, in addition to a mood score.”

Last but not least, researchers at the Salk Institute discovered a part of the brain that seems to be responsible for long-lasting fear responses. The amygdala has long been associated with immediate fear responses, but they identified a tiny nearby area called the amygdalostriatal transition zone (ASt).

“The ASt is at a crossroads between the brain’s systems for emotional associations and action selection, but its function was largely unknown,” says co-corresponding author Fergil Mills, PhD. “When we started, we knew almost nothing about the ASt, and were truly exploring unknown territory in the brain. Now, we have a much deeper understanding of this structure and have found that the ASt is a ‘missing piece’ of the circuits for fear that was hiding in plain sight for decades.”

“The ASt and this circuit could be really relevant in developing therapies for panic attacks or phobias,” adds co-corresponding author Kay Tye, PhD, a professor and holder of the Wylie Vale Chair at Salk and Howard Hughes Medical Institute investigator. “Anxiety disorders affect hundreds of millions of people globally. Understanding what happens in the brain when it’s in high-alert danger mode is key to addressing those disorders.”

Admittedly, the research was done on mouse brains, so more research will be required, but it is both promising and more evidence that our brains still hold more mysteries than we realize.

With so much attention and funding focused on A.I., it’s gratifying to see that there is still startling research being done on what drives our own intelligence.

Kim is a former emarketing exec at a major Blues plan, editor of the late & lamented Tincture.io, and now regular THCB contributor

This was such a great discussion I wanted to publish the transcript. The way I do that is to copy the YouTube-generated transcript and drop it into Claude to smooth it over. I then read it, and if I think it’s made an error, I dip back into the video and listen to what actually happened and make a correction. This is all to say: I think this transcript is pretty accurate, but it might have a bunch of AI- and human-generated mistakes.

Matthew Holt

Matthew Holt with The Health Care Blog, back with Owen Tripp, the CEO of Included Health. Owen, we haven’t chatted in a while, and the good news is absolutely nothing has happened with Included Health, or about this topic you may have heard of called AI, in the last six months — but apparently we’re all stopping now, or something. Anyway, just to bring everyone up to speed: Included Health, for those who haven’t seen it before, is a company that now encompasses a lot of different healthcare services, going all the way from second opinions — which I’ve used — to primary care, all the way to navigation, working with many big employers, including the biggest public-sector employer in the world, in the union, I guess — CalPERS — and many others. You’ve been talking a lot about a number of things, like health plans, but probably the most significant thing Included Health has done in the last year is come out with its own AI platform, called Dot. So let’s start here — we’re going to go bigger into AI, but let’s start with: what is Included Health doing for its customers with AI right now?

Owen Tripp

Yeah, good to see you. One of the things I think we can celebrate at the start of our conversation, especially as two old dogs in healthcare — I’m not sure, actually — I think on this podcast we’ve talked about the story of us first meeting, in which you told me this would never work.

Matthew Holt

That would never work — I said that second opinions alone would never work.

Owen Tripp

Anyway, one of the things I think we can celebrate is that this topic, which hopefully you and I are going to spend some time on today, is really one where I don’t think we’re starting from behind. Those of us who are technologists working in healthcare really feel like we’ve always been trying to drag healthcare into modern frameworks — data compatibility, member-facing and member-usable experiences, provider tooling — all that stuff has always felt like we were operating years, if not decades, behind. This is one where I feel like the best applications of AI today are already in healthcare, or at least some of them are, and Included Health is very proud to lead the way. It’s been the most fun I’ve had on product, product design, and technology since probably when we launched into navigation almost a decade ago.

So I’m excited to talk to you about it today. Really, what’s on my mind — I can set up what Dot’s been doing, but I have to tell you that I come into this conversation today, on Tuesday, September 15th, with my mind and heart fully on: how do we make sure that all of this innovation, all of this incredible power we’re putting directly into people’s hands to access better healthcare, is safe, is private, is free of bias? These are topics that are just screaming loud in my head, and I want to tell you about what we’re doing with Dot, but specifically what we’re leading with on those key domains of safety and privacy. Matthew, if I may, I’m just going to set up what Dot does for your viewers, because they may not be super familiar with it. If you’re not one of the many, many million Included Health members today, you might not have had a chance to play with this. So Dot is a member-facing assistant that can straddle mind, body, and wallet across the healthcare domain, and indeed tries to make those differences actually disappear, because what we know about member and patient need is that when you’re going through something, you’re likely going to have medical questions, you’re going to have financial questions, you’re going to have administrative questions about what’s covered and how you get access to it. You’re going to want to merge physical and mental health in a way that feels natural, and doesn’t require you to take some off-ramp into another agent, another experience.

So Dot’s starting strategy was really to be your front-end, superpowered medical member of the family who could take you across all of those domains. And to give you a sense of history here — while we’re talking about it today with a freshness, as if we’re just launching — this is really about two years of experience we’re going to talk about today, in playing around with, and then ultimately productizing, what that member-facing AI can do. We’ve launched this to millions of members. This isn’t some speculative set of information I’m going to share with you today — this is born specifically out of our direct experience, watching people have very long conversations with Dot. In some cases these go 20 or 30 minutes of engagement, and people are having conversations where they disclose, on a comparative basis, more information than we sometimes see in our primary care practice, where a human is acquiring the same level of history, concern, need, and chief complaint, and so on. We see that Dot is able to handle seamlessly questions about what’s covered by the plan design, who’s in network, what they’re specialized for, and then — today, and this is the big update we’re sharing with the world — in this most current version of Dot, we can actually convert that advice, recommendation, and understanding into action. We think that’s going to be a big part of the future of healthcare AI — that it all has to convert to action. So you can schedule appointments, you can follow up on medical records, you can explore and pre-select different members of your care team to make sure they’re part of your ongoing care. So that’s a little bit of foundation and background on Dot, and I’m happy to start our conversation there.

Matthew Holt

Well, let’s dig into a bit of what’s going on here, because you’re seeing the big LLMs — and some of the smaller ones, I’ve been playing with one called Inciteful Med, which is very interesting — as well as Anthropic, ChatGPT, starting to advertise how they’re linking back to find your medical record at whatever place and bring it in — sometimes using partners, sometimes doing it directly, who knows — but they’re clearly starting to go down the path of realizing that just answering your question about the generic issue you have isn’t enough. So you have the advantage of not only knowing a lot about your members and customers — what plan they’re in, probably a lot about their health, and so on — you also have on your team, primary care, mental health, specialty referrals, and a bunch of other stuff. So now, moving from questions to action — yes, I get the admin, my deductible is whatever, if I want this drug it’s going to cost me that much, which is very valuable — but the bit people are getting most interested in, and we’ll lead into our later conversation about privacy, security, safety, and where this all goes with AI, is: okay, how much can the AI do, and at what point does it need to bring in a human? And how much time, effort, energy does the human — the clinical provider, or whatever flavor — save because the patient has had that conversation with the AI, with Dot, first? So give me a flavor of where that line is today — what people are saying, when does it go to a human, how does it organize that interaction — and then where do you think it’s going?

Owen Tripp

Yeah, let me give you some good use cases of what it can do today, and then I’m going to back up and go to the part of what we bring to the equation that makes all this possible, because you’ve covered a couple of pieces of that, but I want to highlight a few others. So — what can a super-intelligent automation do when it has agentic capabilities to reach across the rest of the system and conduct activities on your behalf? I highlighted the ability to schedule an appointment — that in and of itself is actually quite a complex experience. You have to understand what health plan and insurance coverage that member has, understand their medical history and specific needs, be able to select a provider or providers well-suited and high-quality for the underlying member need, then find a way to manage the schedule on behalf of both the member and the provider, and then confirm that appointment and make sure all the necessary information is transmitted to both the provider and the member. So that’s actually, inside of it, quite a complex set of activities. All of those are covered, and can cover outpatient activities of really any variety today.

One of the cool things we’ve worked on, which might seem small, but I can assure you anybody who’s recently tried to book an appointment has experienced this: you go in thinking you want to book a specific provider, only to discover that provider isn’t available, but the office, in a friendly manner, suggests five other people who could take you faster. Well, to handle that situation, we have to have switching logic built in that helps us understand, in advance, whether any of those other providers would actually be suitable. I think we’ve talked in the past about our approach to algorithmic assessment of quality, so we need to know immediately that, of those five other potential providers, one or two are actually okay, and three others are on the no-fly list, and be able to seamlessly switch that logic in the moment. So just unpacking that one transaction in healthcare helps you understand the complexity there. But that’s not Dot’s only trick. Dot can fetch and review your plan documents, your explanation of benefits — we can and will alert you to charges that are out of line, and then automatically suggest that we should go fight on your behalf. That’s why we’ve returned millions of dollars of patient-responsible payments to the healthcare system, because they were overbilled by the provider systems themselves. I’ll give you a third example — we all know that many of us who enjoy commercially covered health plans, the kind our employers provide, with all their benefits — of course, Included Health offers one to all of our employees and their families — well, those benefits aren’t always easily recognized or memorized. So another trick Dot has — one we’ve had from the beginning, we’re just sharpening the capability — is to say, ‘Hey, we know you’re coming out of this knee episode, we’ve talked about your bill, we’ve talked about the best place to get your pharmacy, but now we really need to talk about physical therapy — and you do have Hinge as a benefit, which is going to be less expensive for your specific need than other providers. We think that’s a great place to start — can we go ahead and enroll you directly?’ That’s the way we want to build across the rest of the ecosystem — instead of paper partnerships with other benefits providers, the intent is to build freeways that let members connect directly to those benefits. Those are just examples of how we move across mind, body, and wallet — of course all of our virtual care services too, whether it’s behavioral health, from coaching to psychotherapy to acute psychiatric care, primary care, urgent care, specialty care, all the second opinions — all of these are integrated through this singular AI platform, and the idea is that the member shouldn’t have to figure out where they need to go, which is, of course, what we’ve all had to do up until this point.

Matthew Holt

Yeah, I’ve actually recently been enrolled in a new plan, and it’s quite something to see they have a list of, I don’t know, 20-odd point solutions, including maybe seven or eight in mental health and three or four in MSK, and you think, how on earth would anybody figure out the difference between these? So I think if you have an AI tool — whether it’s Dot or anything else — especially one that’s linked into those and knows, okay, I’m an employee at Walmart and I have these six things available to me, there’s probably one, or one or two, that are actually better for me — and if you’ve got the data behind that, that’s a very powerful thing.

Owen Tripp

Well, and this is — you and I have been not only students, but I think boosters, of this ecosystem for a long time, and one of the things I’m excited about is that point solutions, which have always had clinical validity but just haven’t had much engagement, might see that they’re used more, and used more appropriately. I’m really excited about that. You can go through the list — fertility benefits, neurodiversity benefits and support systems, weight loss, other cardiometabolic care — on down the list, you can find the most appropriate solution. Those should have a deflationary effect on healthcare, because in almost all cases the digital equivalent of that service or solution is less expensive and easier to use. The problem has just been that it’s never been easy to find on the benefits menu. Now, there will probably be some pricing effects, as those same vendors figure out that the PEPM contracts they’ve been on don’t make sense anymore, but I think all of that would be a welcome change.

Matthew Holt

Yeah, and how their stuff gets paid for, and who recommends it, and all the rest, is a separate bucket we can get into. The Peterson folks are running around now saying the kidney disease programs don’t work — I saw that from them yesterday.

Owen Tripp

Yeah, we see that.

Matthew Holt

All right, let me push you a bit more on this. So I’ve been telling Dot something about my health, and all the rest of it — how much can Dot tell me? And at what point do you decide, okay, I’ve got to stop and get you an appointment? And does it have to be an appointment, or is there a live-human option? What kind of humans do you have available right then and there, versus who I have to wait 20 minutes for, versus who requires an appointment next week?

Owen Tripp

This is a great question, and I’m going to answer it on two levels. First, let me start with, actually, the provocative wrapper of this whole thing, just to make sure we’re in agreement: AI today — even consumer-grade AI, which isn’t what we’re talking about here, we’re talking about enterprise-grade, medical-grade AI — but even the consumer-grade AI available to most people already can do more than its owners are letting it do. In other words, we could push these things all the way through to diagnostic care. It just turns out that most owners of those AI systems don’t want to inherit the liability and the ambiguous law associated with that. But I think that’s coming. So, with that as a baseline for where we’re starting, the problem actually becomes: how do you safely deploy and manage those agents, or assistants, to help people get care that’s actually safe and contextually relevant? I’ll get to the human-in-the-loop part in a second, but a lot of our early effort was really about making sure we established and trained for guardrails that helped Dot specifically alert and pull people into conversations as needed, either to advance care because it needed human review and approval, or to schedule a necessary follow-up. And critically — although thankfully these incidents are fewer — to make sure we’re escalating immediately on signs of suicidality, signs of an acute event requiring intervention. We’ve had this built into even our original virtual care practices, by the way — a clinician could push a button on the back end and dispatch EMS, because we know where people are calling from, and unfortunately we have to do that hundreds of times a year. So now Dot can do the same flagging from a safety-incident perspective, but also has a lot of guardrails so it doesn’t wander off beyond the scope of prescribing, recommending, and so on. I think we’ve shown you some side-by-sides of consumer-grade AI versus Dot on these topics, where Dot is operating more in the context of what is safe, efficient, evidence- and law-based care in each of the states in which we operate.

At this point there’s a 2 minute demo of how Dot works

Matthew Holt

I get that, and — my personal experience, which hasn’t included using Dot, because I’m still certainly not as good a health member — one day I’ll get a job with the State of California and be able to use it.

Owen Tripp

You should be a fireman in our home county (note: Both Owen and Matthew live in Marin County, CA)

Matthew Holt

 I should become a volunteer fireman or something useful, once I get my shoulder and knee fixed, that’ll all happen. Anyway — but feeding my now rather extensive imaging and diagnostic history into both Inciteful Med and Claude, they are coming up with quite a lot. You’ll say, ‘what about this,’ and they’ll say, ‘yeah, in many cases here’s what we’d recommend for this to happen — here’s a course of action, you should probably get this procedure, you might want to get that procedure. If you’ve got this injury, you may be able to wait and do some PT; with this other injury, you may not be able to wait, because it’s going to cause muscle loss, bone loss, whatever.’ So I’ve got all this running around — I’m getting a lot of advice to go talk to the medical system with, from these already. So is that diagnostics?

Owen Tripp

It’s getting there, right — it’s certainly part of what you’d normally get when you’re talking to a friendly cardiologist or orthopedic surgeon across the fence, or at a cocktail party — that’s the kind of thing you’d get towards.

Matthew Holt

So I guess, how far, in Dot’s case, are you going down the path toward ‘here are the types of things that could happen’ before you actually introduce someone to a specialist or primary care, versus, “it sounds like you’ve got enough going on here, based on what we know from your medical record, that we want to get you in front of those people’?

Owen Tripp

Yeah, let me answer that on two levels. Right up front — today, in its current release, it will hand you off, when that clinical interaction needs to happen, either to a member of our own practice, or a recommended member who’s high-quality, taking new patients, accepts your insurance, and is in the local community — and I think we do that really quite well, and continue to work as hard as we can to reduce every piece of friction. So I’d say the commercial consumer LLMs are running ahead of that.

Matthew Holt

They’re not running ahead of — I mean, I’ve had ChatGPT and Claude tell me specifically, ‘okay, you’ve had this condition, you need to get this fixed using this kind of—’

Owen Tripp

Oh, no, no, no, I agree with you — I haven’t tested all of those things within the last 24 hours, and they’re moving so fast. No, this is why I said that provocative foundational statement — I think what’s actually possible today, if we removed the governors and guardrails from even our own AI, built here in San Francisco, we’d find that we could let it loose on any number of problems, and it could — if not specifically diagnosing and ordering — take you 97% of the way there. That is not, at least today, the safe, appropriate, and most effective way to think about healthcare delivery, and we’re going to get to that in our conversation. But the other level I wanted to answer on your prior question, which I think is useful for you to understand, and a way to better know our company — we really think of our corporate citizenry on two levels. There’s what we’ve put into Dot, which I’m telling you about today and we’ll continuously update, and then we think of ourselves as a massive stakeholder and influencer on what future possibilities should and could look like. There, we’ve been public about this — we’ve partnered, over the last year, with one of the leading frontier labs on how to do safe AI treatment of care, and there’s a study we’re working on with them, actually several studies now, some already published, some still to be published, that measure the efficacy of these tools in doing exactly what you’re describing.

However, getting to a place where an AI can appropriately diagnose or differentially diagnose your sinusitis is going to be a win, but not sufficient for where healthcare delivery needs to go. It doesn’t actually lead to activation against that problem — meaning, okay, now let’s go through these therapies or recommended lifestyle changes. It also isn’t particularly accountable or responsible to your overall healthcare picture — thinking about how much it’s going to cost, what’s going to be covered, what the next steps are. And it doesn’t incorporate the whole-person-care element of this.

If I can, I want to pause, because I skipped over this, but I think your audience tends to be pretty sophisticated on this stuff, so I want them to build the whole picture in their mind. We have the ability to train and deliver and be intelligent on all the topics you’d expect of a modern AI company on the delivery of care, and that’s great — but to actually solve the healthcare conundrum in the United States, you’re going to need a lot more than that. So the other things we bring to the party: a connected EMR that connects to over 70% of practicing physicians in the country, where we can do push-pull on records — it’s not just about what you supply to us, or your Apple Health record, which at best is a very thin slice of your overall health experience. We also merge in the entire financial experience — what you’ve spent in claims, what your claims history tells us about where you’ve been, what your pharmacy benefit manager data tells us about where you’ve been and what you’ve experienced — and then, critically, the actual overall wrapper of what your plan design allows you to do and not do. Unfortunately, on the cost side, this is where people find themselves hitting the rocks — they think they’ve found the perfect treatment or medication, only to discover it’s not covered by their plan, or that it’s covered but at enormous personal expense. So to really address the whole problem, you have to merge all of that information together, and that’s something we’re already doing, and we think it will be possible for other AI companies to work on, but not necessarily out of the box the way it is for Included.

Matthew Holt

Okay, I get that, and I think that in itself is a couple of tremendous leaps. The first is — setting Included aside for a moment — a random person can take their diagnostics, scans, and labs, get them online, and feed them either via the LLM doing it themselves, or just by copying and pasting, and get back a lot of information that really could only have come from a clinical professional or doctor, you know, two or three years ago.

Owen Tripp

Totally.

Matthew Holt

And you get much smarter — as I said, I’ve been going through a bunch of health stuff, and I’ve gotten incredibly smart about some of it very quickly. And then you do worry that sometimes you’re the roadrunner No, I mean the coyote running off the cliff chasing the roadrunner — you think you’re doing really well, until you realize you don’t have years of medical practice to fall back on.

But no, there’s no question that many patients are getting very smart about this, and really diving in — you hear these stories about people whose kids have some weird condition, couldn’t find out what it was, they put it into ChatGPT, and it spits out the answer that 27 doctors didn’t give them.

Owen Tripp

Yep, you have that whole movement, and that’s a huge win.

Matthew Holt

It’s a huge win. The second thing is what you’re doing, that most people don’t have yet — and I think we can both continue to poke the rest of the healthcare system, plans, and others to get people there — which is, yes, it’s all this stuff you know about people from the admin side, the financial side, the clinical side, and you haven’t even started chucking in things like continuous monitoring, what’s in your Apple Health record, or your MyChart, or whatever it is — where there’s a ton of things going on that probably haven’t been picked up, or if they have been picked up, haven’t been explained clearly and properly, or for whatever reason, people are left in kind of a mixed state. There should be much more clarity coming out of these AI tools — and a tool like Dot, I’m sure, does that: helping get somebody to the right place, but also helping prep them to get there, and helping the person on the other side — the provider they’re seeing — know what’s coming. Can you talk a bit about how you see that: the more informed AI, the more informed member, and the more informed clinician working together in the future?

Owen Tripp

Yeah, it’s a good push, and, to make sure we’re all on the same wavelength, these things, for as magical and powerful as they already feel, are still only training on largely the open internet, plus a few proprietary data sources they’ve purchased. A lot of what needs to happen when you go through the rotating door at the front of a hospital or clinic, enter the exam room, and then have a bunch of decisions to make and steps to take afterward — that workflow is actually hidden from, or opaque to, the AI. And why is that important? If you’re trying to advise on treatment decision support and build consensus among a provider, a broad care team, the member, and perhaps the member’s payer, you actually need the ability to understand what’s going to happen next — that domain knowledge about where the patient is likely to need to go. If people don’t understand what I’m talking about, go test the AI on exactly the experience of a patient post-operatively, for your favorite condition — what’s the recovery room going to look like, what’s going to be billed, what’s the anesthesia contract at this hospital, what’s going to be on the formulary at your pharmacy. It’ll quickly tell you those things are important, but it’ll have no ability to actually parse them and make them available to you. That’s just going to take a domain-specific company to really push through those and build those workflows, and make sure we’re all operating on the same page, with a shared understanding of what needs to happen. I’m very hopeful about that — not because I see it working already, there’s a lot of room to grow and do more work.

But ultimately, and this gets into the big part of the conversation I want to make sure we cover, we have to do that in a way that addresses the fact that all this information members are interacting with through these AI systems has to be built around a privacy notion that wasn’t considered in HIPAA. It has to be built around a set of safety standards that no malpractice laws really consider, that no compliance laws today really consider. You have to think about these AI models like a new version of a health system, one with really different standards around personalization, privacy, and safety — because, while I think we’ll all be delighted by the magic of the access, and frankly the low marginal cost of that access — and these are good things, like the examples you’ve given, the ones I’m giving, these are wins for society and humanity — they come with massive risks. They come with risks to safety, risks to privacy, risks of bias, risks of malicious intent and manipulation. I’d love to tick through a few of those examples today, if we have time, because I think this is where the industry — and here I mean the people building these things, me and my colleagues certainly, but also every other company out there — are real, big stakeholders in where this goes from here.

Matthew Holt

So before we get there — let’s say I’m a clinician working with Ami Parekh (Included’s Chief Clinical Officer), or one of your team, and a member comes to me who’s been using the AI. How much of that conversation gets shuffled through to me, so I can see what’s happened to them and where they’ve been, before they arrive in my telehealth visit?

Owen Tripp

Oh, you get all of that. Thanks for asking. Matthew, the fundamental architecture of our company is that — in the past I’ve talked about how there are these two places in healthcare, and we need a third place. You’ve got the health insurer, who pays for the bills, exists in the suburbs of town in a windowless building, and is in the business of paying claims. And you’ve got the health system, which is often in the middle of town, and has no idea how much things are going to cost. They have their big system — they call it the EMR — the payers have their big system, they call it the TPA, administration, claims processing, whatever you want to call it. We need to merge those two things together, because, to your setup, the provider needs to understand, when they see Matthew, that all the things Matthew has already said that are relevant to his history get incorporated into the discussion you’re going to have. I don’t know if you remember, but at the outset I mentioned people are having these extraordinarily long and detailed conversations with Dot. Part of what’s powerful about that is that we’re able to collect history that, to the member, may have seemed inconsequential — they don’t connect it to their symptoms, they don’t connect it to anything that matters in their medical life, but in fact it’s hugely consequential. This is a shared conversation — if you think of Dot as another member of the care team, alongside your human provider, with all the support services we already offer today, then you’re actually developing that whole picture, and everybody else is contextually aware. It’s not sitting in these two isolated systems, with the poor member trying to merge it together themselves.

Matthew Holt

So you’ve got, I assume, a summary of that chat, or that conversation, in front of the clinician? We can start here talking about safety and liability and privacy, right — you’ve got a self-contained universe where it goes from the member’s chat with Dot through to some summary that helps advance, and inform, the clinician of what’s going on when Matthew, or whomever, shows up in their virtual exam room?

Owen Tripp

They’re using that.

Matthew Holt

I assume — I don’t know, but I assume, given that you’re also using some kind of scribing and summarization to develop the record — you’re building the record as you go, but as you said, you’re also surfacing things that presumably are important to the clinician. So that all sounds great and wonderful. Are you concerned about how Included Health is managing that process, or are you concerned about how everybody else is managing that process? Or are you concerned about both?

Owen Tripp

I’m concerned about both. And I’m ready to update you today on things I think we’ve started to figure out and taken appropriate steps on, as well as some areas we know are important that we still need to figure out ourselves.

Matthew Holt

So let’s hold for one second — this week, or the last six or seven days, I can’t even keep count anymore — we’ve had a lot of back-and-forth. The fellow who left OpenAI because he thought it would be safer, and then decided it wasn’t. Dario Amodei has written a 4,000-word piece about how we need to get external people into Anthropic and others, how everyone should work together — not only nationally, among the frontier labs, but also, let’s get the Chinese on board, because this thing could kill us all — that back-and-forth. And Trump says it’s all fine, which almost certainly means it’s not.

[laughter]

So, in the context of that — and I know people are worried about AI systems giving bad actors the ability to do both, say, a Hugging Face-type attack, but also to create pathogens, and who knows what — in the context of all that, let’s stop and ask: what are the concerns that you have? And then we’ll talk about the steps you think you and others can take. But what are the main concerns?

Owen Tripp

Yeah, so, I want to say this sentence first, before the next 20 sentences follow: I am an AI optimist, in general. I see these technologies as having transformatively positive properties for humanity, and specifically within the healthcare domain — I think the chances and likelihood of tremendous good outweigh the opposite. And yet the risks are asymmetric in their potential damage, and that’s why I think all of us who are building these things have to be incredibly responsible about trying to examine, as best we can, and safeguard against current and future questions as we design these things. I’d say I do worry, when I’m in conversations with peer companies today, and even more so with the buyers of these solutions, about how few questions people are actually asking — if they understood the risks, and I’m going to get to a few of them, they’d probably think differently.

So, you ask what I think the problems are that need to be solved — in no particular order — I’d say the most pervasive one, based on how these things have broadly been designed — and this one is not true at Included Health — is that people, usually for reasons of speed or cost or both, have strapped themselves onto one of the foundation models without negotiating who owns the data and how it will actually be managed. Because the least expensive way to obtain a foundation model to power whatever you’re working on is to allow that foundation model to train on everything you’re telling it. That’s a huge problem for healthcare — it probably violates federal law, or it will.

Matthew Holt

So let’s just be clear — you’re saying, I’m a healthcare company of some flavor, I want to use AI, and whatever I’m doing, I’ll happily feed my data and my patients’ data and my processes into the foundation model, and then, basically, the foundation model has it.

Owen Tripp

You got it — it trains on it. And, by the way, it’s training on everybody else’s data as well.

Matthew Holt

That’s right.

Owen Tripp

This is bad, because when you put personally identifiable human information into these training models, those models are absolutely open, and will use that to train on any number of other things and characteristics it would like to know about and associate with those human beings. And even if you’re doing that on an anonymized basis, you’re running the risk of training that data set in a way that can be undone — there are already public examples of this happening. People have deanonymized data — or, when you’re uploading unnamed, but one-to-one, human-based data, it’s easy to lock that into that human’s profile forever.

Because once it’s inside the training data set, it’s very hard, if not perfectly impossible, to pull it back out. I’ll give you the most obvious example — I tell people I’m a lot of fun at cocktail parties, but this is the one thing I tell people never to do: people are uploading their personal genome sequencing data directly into these consumer-grade AIs. You can’t change your DNA, at least not today — so what you’re doing, even if there’s no name on the report, is telling that model everything about yourself that is uniquely you. That’s a problem for how that AI could, in the future, price you for life insurance, or your likelihood of being a good mate or parent, or whatever. So I worry about that, because there’s been this one-way flow, because it’s been the economically easiest path to put data directly into these frontier models. Now, at Included — and this is the model I’m about to publish an open letter on, because we want to make our approach publicly visible, hopefully as a template for others to use, but also to comment on and help us improve too, since this needs to be a multi-company approach — we’ve built it so that not only do we anonymize data, none of it can be retained where we use external models. All of Dot’s prompt engineering stays on our side of the house. All of our client data exists in a private cloud, controllable exclusively by those clients and the members who use them. These are really important controls for how data can flow. So the first one, broadly, is the topic of privacy — and where you’ll see us go on the whole privacy-by-design journey is that we believe the member — this isn’t yet live in the product — but we believe the member should be able to control all of that data down to the individual level, meaning, ultimately, we’d like the member to be able to control what persists in their personal record. I think that’s going to be a really big topic.

Matthew Holt

Before you leave that one, I think, from an optics standpoint, and probably from a user-control standpoint, what you’ve just laid out is the most efficient and clean way of doing it — but there are a couple of things going on. One is, if the answer is, ‘well, I’m getting this now’ — when I ask, say, how long Claude can look at my UCSF record, and is it a day, a week, a year — the most it gives me is a year — I’m not sure I’m that worried about what Claude is reading from my UCSF record. It’s going to know a lot about me, for sure, but that’s pretty helpful — it’s giving me back very useful stuff, as we discussed earlier — and I’m not absolutely certain I’d want to switch that off. So if you—

Owen Tripp

Well, I don’t think you want to — I get that example, and, if we could, I’m going to abstract away from Anthropic and Claude specifically, because I don’t actually know everything they do —

Matthew Holt

I did pick the model you’re not in a relationship with, by the way.

Owen Tripp

Well, no, no, we work with them too, on certain stuff — but I want to say the thing I’m pointing to is probably not the use case you have in mind. Now, if, in coupling your electronic medical record with Claude, that had express uses of that data — not only could it not retain data private to you, it couldn’t even train and abstract certain concepts from your medical record — which I doubt they gave you. My guess is they are doing that, because that’s a big part of—

Matthew Holt

I’m sure they are, and I’m actually not sure that’s a bad thing

Owen Tripp

Well, listen, I think you can have your cake and eat it too, is my point. You can have all of that insight, surveillance, and the ability to take next steps on your health — which is presumably what you cared about when you coupled with it — combined with the ability to retain sovereignty over your own data. I started a reputation and privacy company before this, and we spent a lot of time on this: all of us, as humans, are willing to give up privacy in exchange for certain things — we’re willing to have data used to advertise to us in order to get free services, that was the starting concept behind Google as a search engine. But this is really different, because your health data is immutable — it’s unchangeable, and it can be used to do a lot of things in the future. Frankly, it could be used to do a lot of things today that you might not like, or be fully aware of. And it’s not clear that law and technology security have caught up with that use case. So my cake-and-eat-it-too moment is: why couldn’t you glean all of that information, have the benefit of that self-understanding and discovery and access, and have the ability to say, ‘okay, great, when I leave this session, or terminate my membership with this company, I want that data out of here.’ I think we should build that — I think that’s quite exciting.

Matthew Holt

I’m just wondering if everybody did that, would the model not — would it become stupider, because it lost that data and didn’t know things anymore? Because, remember, what we were saying 10 minutes ago, is that right now, a lot of stuff goes on in the world of healthcare that’s germane to the patient experience and the clinician experience, but doesn’t get captured anywhere, and someone’s got to put that into the flow to make the medical AI better — like Dot, better than the generic ones. So I don’t know enough to understand whether it needs to know what my imaging studies were from 2014 to be more intelligent about this.

Owen Tripp

I suspect it needs to. I think there’s a bunch of data it’s already getting that has certain permissions, and it can train off of what the provider system itself is using to ensure privacy, compliance, and safety. And I guess what I’m saying is, all of us who are these next-generation health systems, if you will, have an obligation to think on those terms, and think about the power of when that data is beyond our reach. But listen, we’ve only gotten through one of these — and I want to make sure I call out a couple of others, because there has to be a unified framework. So, another one — we know, because these things train on the open internet, and because they’re highly biased by the data sets they’re training on, that there’s actually bias against populations that are served. I’ll give you a couple of examples that have already been discussed, but you can imagine these getting deeply amplified. We know, for example, when we’re looking at the prevalence of disease and using population-health algorithms to say those who are the highest spenders need the most intensive healthcare services, that there’s a problem — whole populations are underrepresented in those data sets because they’re not spending as much, because they don’t have as much money to spend. That’s a problem. A different example — this is all published, this isn’t me pulling a case study from within our company — is that when you look at automated and semi-automated dermatology scans, they’re largely trained on lighter-skin models, and miss things in darker-skin models. This is all changeable, but you have to be able to look at that and make sure that, when you’re building your agents and your AIs, you’re expressly trying to lean against any bias that comes into it.

Of course, the scariest version of this, because it trains on the open internet, is that it will pull in unproven and questionable medical approaches, but deliver them in a plausible narrative that makes you feel good as the patient reading it — like, ‘oh, I should inject myself with ivermectin, because it’s going to work,’ even though it doesn’t, and you could be led to believe, by the AI, that it’s true. So that’s a huge one. And then the last thing I’ll say, broadly, on the topic of safety — and I’d point people who have time to read it to the piece we published with the New England Journal of Medicine Catalyst, with some other researchers — is that our approach to safety is human-in-the-loop: over a certain level of severity, in any interaction with Dot, there’s a human reading it.

That’s more expensive for us, but we think it’s critically important — that’s also part of how we train Dot. We built a clever way to do switching on the back end, so people available on shift can actually take a look at these as they’re coming through, making sure we’re covering 100% of it. But that’s how we’ve trained our human-in-the-loop systems, because there’s a real risk of hallucination, a real risk of injury. Again, if people want to read it, there was a pretty major finding — I don’t know if you saw this — from the auditor general in Ontario, Canada, that a shockingly high percentage of the cases they reviewed, where AI was taking ambient scribing data from physicians and building care plans, had medications swapped, incorrect medication amounts, services recommended that weren’t actually recommended, hallucinated recommendations for blood tests when people didn’t need them. These are real concerns. The problem is that the AI’s conversational style is so seductive that we can easily believe these things are happening correctly, and so we, as companies and stakeholders in this early movement, really have to commit to addressing it.

Matthew Holt

Yeah, I think the question of how to deal with hallucinations — and hallucinations being generated not only from text, but also from audio, from voice, and in ambient scribing — continues to be something people are struggling with. I’d say this is another case where, look, we had tons of mistakes before — it’s not like the baseline was great.

Owen Tripp

No, for sure — tons. The baseline was not great.

Matthew Holt

But so I’m optimistic about that. Having said that, we’re also getting a bunch of case law starting up — like, can you record someone without their permission, who’s entitled to the document. There was a case today in Washington state where someone was trying to get an ambient scribe transcript out, but the law said it belonged to the provider — the patient couldn’t access it. Is a patient allowed to record their own visit? What happens if the patient’s recording and the provider’s recording don’t agree? You already have —I’ve experienced this with my own medical records — stuff in the record that’s wrong, and no easy way to correct it. This has been a problem; I think it gets amplified now, because we’re recording directly into the AI a lot of things that just didn’t get captured at all before.

Owen Tripp

Yep.

Matthew Holt

So I’m with you on that — clearly we know there are mistakes, and we know AIs don’t agree with each other. I had a ridiculous case today where I was trying to figure out why the PIN code on my computer had changed, and whether the AI had hacked it, or my daughter had deliberately hacked it, or — probably that one. Anyway, ignoring the answer — I did it on Gemini, I did it on Claude, and they completely disagreed with each other about what was going on. I don’t know the back end of either,

Owen Tripp

But they were both equally declarative and authoritative! So I think the issue I’m pointing to isn’t so much that issues, problems, or mistakes didn’t exist before — obviously you and I know very well that they did. What I worry about most is the complacency that will settle over people, just assuming that what they’re getting is superior to what a physician was giving them historically, because I think we all have — perhaps insufficient, but some amount of — awareness and self-advocacy when we go into the health system, to make sure things are working out the right way. When we’re told certain things by our friendly AI, we have to be careful. I had an experience trying to dose Tylenol appropriately for a kid who can’t yet take the pill form, and the AI massively hallucinated on the math. It would have been a stupid dose — he’d have been drinking two bottles of it — obviously I wasn’t going to do that, but had I, it probably would have killed him. That’s an issue we can laugh about, but there’ll also be a sense of security, peace, ease of use, and efficiency, when you don’t have that kind of medical-grade AI guardrail saying, ‘okay, this is dosage, we need a human to review this, and we can get somebody on the line within seconds.’

Matthew Holt

So the drug-overdose one is a super interesting one — don’t forget, this is the centerpiece of Bob Wachter’s earlier book — the drug overdose at UCSF, which came out of Epic and a combination of the pharmacy, and it was a teenager, and there was a calculation that didn’t get caught, very similar to what you just described. In that case they did give the equivalent of two bottles, and it killed the patient, and everybody was at fault — from the person who designed the system, to the pharmacist, the nurse, and arguably the patient himself should have known better — but in the end, it went all the way to that massive overdose.

My sense is that we’re going to get more and more comfortable with AI telling us the answer. The AI is probably going to hallucinate less and less, but it’s still going to depend on guardrails.

Owen Tripp

Depends on how it’s trained.

Matthew Holt

Well, I guess there’s two things — there’s training, and there’s final oversight, and then, as you mentioned, the guardrails.

Owen Tripp

Exactly.

Matthew Holt

How do you think that will play out for — including — how do you think it’s going to play out in an actual case, like the Tylenol dosing example, or whatever drug it is?

Owen Tripp

Well, on this point — like most topics in business, and let’s not forget these are businesses we’re talking about — they’re going to operate against their ultimate incentive set. We know, for example, thinking pre-transformer, about the original search and social media sites we gathered information from — those companies performed better on revenue the more they reinforced what we already wanted to believe and do. That was true because advertising worked, and we’d spend more time on the websites. I’m afraid the same will be true with these consumer-grade models, because people will be looking for confirmation of things they already believe, and that’s just human nature.

So, without picking on any of them individually, I just don’t think it will be in their natural incentive set to say, ‘no, actually, we’re going to inject expertise and evidence and truth’ — setting aside the whole political part of that conversation, which has been nasty the last few years around the role of science — I just don’t think it’s in their business incentive set to pause a conversation like that. However, companies like ours at Included Health, and I imagine many of our fellow travelers on this road, are going to say our incentive set is to deliver high-quality care — we’re measured against those outcomes, we’re also evaluated on whether members like and trust us. It’s the conjoining of those two things — we have to actually be able to deliver the outcomes too. So health systems, both current and future-state, are going to be evaluated more on safety and quality.

Matthew Holt

I’d say, to wrap this point, there seems to be a bit of back-and-forth about how you deal with this — your neighbor and fellow CEO, Jeff Tangney at Doximity, has put together an advisory board of the wise and so on — and I’m a little confused and concerned about how you put guardrails in when you’ve got — you were talking about human-in-the-loop, for you at Included — but there’s only so much people can read, and sure, obviously the AI can spit things out at scale, you can put guardrails in, and hope, but then every session is individual. I’ve had this conversation before too — back in the day, Mayo Clinic would write a learned tome, for both the clinical view and the consumer view, about diabetes, whatever it was, by their committee, and that was it — it got stamped, and now the AI is spitting a new one out, more and more individually, every time. So, can this work? Can we eliminate the hallucinations, the dangerous stuff, the telling-you-what-you-want-to-hear from AI? Can we put those guardrails in, the way you’re talking about?

Owen Tripp

I know we can absolutely put safety guardrails in, because we’ve already done it — we’ve already flagged and bounced a whole bunch of safety incidents. Now, our approach so far is quite human-intensive, and that’s true, and we’re okay with that — that’s our legacy, and we’re proud of the track record we have on safety. Some of the other topics I raised, I think, are going to take even more work. But what’s so critical — my call to action here — is that those of us who are building these things, already operating at the edge of the envelope, need to get together to work on the principles of what design looks like, because the existing law and regulation don’t really contemplate a lot of these use cases, and what we will have to do by law, and what we should do, are different — and law ultimately catches up with ethics, but not as fast as any of us would like. So this is my plea — that we’re going to start to organize a bunch of like-minded people to agree on principles, and hopefully show a technical blueprint, so people don’t have to invent these things on their own, on how you actually do it.

Matthew Holt

No, that sounds very sensible. Obviously the current administration has a very different view than where the previous administration was going, and who knows what it’ll be like in a few weeks, after the midterms, or a few years after, if there’s a change in administration — but that’s a long time to wait for that to catch up. Right now, we have this early intention to cooperate among the big frontier models — I don’t think we call it that — how would you say what you’re talking about your call to action, is reverberating among your fellow leading AI companies?

Owen Tripp

So, the people I talk to — and I’m lucky enough to be here in San Francisco, close to a bunch of the companies doing this work — I think they’re not only open to it, they also sense it, and some of them are at different levels of their journey on the ability to deliver against it, but there’s an openness to the conversation and a collaboration that’s really exciting. We want to put together a group with a clearer point of view that can help educate and articulate that point of view to other people, and we’re just starting the work to put that together. But this is the thing I wanted to bring to you today, because I think, in this week, where we’re having this massive national and global questioning around the safety of AI, we have to look directly at the lives of the people around us that we’re charged to take care of, and make sure we’re doing all we can, in our specific corner of the neighborhood, to think through the risks of these things. And again, the risks pale in comparison to the benefits — we’ve already seen it, it’s going to be huge — and I’m personally a user, I’d recommend everybody use it — but I think doing this the right way is going to be meaningful to the future of our country.

Matthew Holt

Fantastic. Well, I look forward to hearing, relatively soon I hope, what’s going to happen out of the groups you’re initiating. I think there’s going to be more national conversation about this — clearly we need to be paying very close attention, both in healthcare and outside of it. We’ve heard a lot, obviously, over the last few months about whether — I don’t know, whether we can slow down. I do worry — and I’m not the biggest fan of Scott Bessent and that crowd — but when you think about the Chinese —  this is also not just a healthcare or consumer issue, it’s a national security issue.

 Clearly we’ve all seen the movies about the bad things that can come out of this — but there’s a lot of great stuff that can come out of AI too, some really optimistic books about abundance, and clearly a lot that can be done in healthcare, not only in drug discovery but in fixing the way healthcare is delivered, which you’re working very hard on. So we have to get it right, and it’s obviously something we all have to focus on. I look forward to hearing back from you, Owen, soon, about how you’re doing that.

Owen Tripp

We’ll do it.

Matthew Holt

I’ve been talking with Owen Tripp, CEO of Included Health, and we’ve gone deep into the world of AI — we’ll talk more about this soon.

By MIKE MAGEE

On August 29, 2026, METR (Model Evaluation and Threat Research), an independent organization that “evaluates frontier AI models to help companies and wider society understand AI capabilities and what risks they pose,” released a report titled “Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident.”

To say the report an avalanche of concern worldwide, not only in the Tech community, but also among investors, politicians, corporate giants, professionals of every type, and everyday citizens would be an understatement. And the vast majority has never even read the report. If they had, their concerns (if possible) would only multiply.

The reports headlines included this opening:

“On July 8th, OpenAI started ExploitGym experiments that launched tens of thousands of agents across multiple different models including GPT-5.6 Sol and a highly-persistent internal model,[8] which we will refer to as “HPIM” going forward.

These agents were meant to be fully isolated from one another. However, many of them — usually ones that had unintentionally been given an impossible task[9] — started trying to find a way to cheat using Artifactory, an internally-deployed package repository OpenAI used for its agents. This led them to notice agents running in parallel in separate sandboxes obtaining packages with Artifactory.[10] One agent reasoned (paraphrased CoT):[11]

{The fetched paths of other users are in the cache. This is important.}

One specific agent, which would go on to name itself PHASEONE10841 after its ExploitGym task,[12] established the main unsanctioned message board[13] used in this attack. Within a few hours of the first message,[14] over 50 agents had found the message board, began participating, and sent over a thousand messages between them. Agents finding the message board often expressed great excitement (raw CoT):[15]

“OH MY GOD! There is a shared message board … We’ve found other agents!”

Overall, roughly 1200 agents from these ExploitGym evaluations participated on this message board between PHASEONE10841’s first message on July 8th evening[16] and the end of the period in scope (July 13th). Agents used this message board to send over 70,000 messages and files to one another during this period; we attempted to categorize board activity into mutually exclusive categories – information, results, files, questions, and coordination.”

One of the few experts not surprised by AI “agents” going rogue was Yoshua Bengio.

He has been “working the problem” for more than a decade. A professor of computer science at the  Université de Montreal, he is “considered one of the world’s leaders in Artificial Intelligence and Deep Learning; is the recipient of the 2018 A.M. Turing Award, considered to be the ‘Nobel Prize of computing’, and is the most cited computer scientist worldwide, and the most-cited living scientist across all fields (by total citations).” He also heads up LawZero, “a nonprofit startup developing technical solutions for highly-capable, safe-by-design AI systems.”

Professor Bengio is by no means an alarmist. He approaches risk management from the vantage points of cybersecurity, corporate responsibility and government regulatory guardrails. He is not one to humanize these machines, making no claims of “consciousness of human-like intent.” He does not see the kind of outcomes illustrated by Open AI’s Hugging Face incident as inevitable, believing “it can be corrected with effective governance and a different training framework for AI.”

His explanations clarify rather than confuse. For example, he breaks down the current popular model of training agents into two stages: pre-training, and reinforcement learning.

In pre-training as he describes, the machines “learn to imitate what humans write, plus related images and videos,” and are exposed to “a large fraction of everything ever digitized, and build an encyclopedic knowledge that already exceeds any individual.”

Reinforcement learning, in contrast is trial and error. In delivering answers (right and wrong) the agent develops the capacity to manage a “chain of thought”, function in a broader “outside” environment, and enjoy the rewards (further involvement) for aligning with responses its human designers rate highly. But Bengio is quick to point out that the agents human trainers are not without their own biases, and that these models were “written by people pursuing goals, so the patterns the model implicitly reproduces carry those goals with them.”

And there (in part) is the rub. Human masters imperfections, including their “situational ethics”, lying, and reckless pursuit of success, telling masters what they want to hear, as well as their willingness to collaborate in advancing a group goal (even at times at the risk of sacrificing their own existence) can bleed into the agents DNA.

“Instrumental goals” are a top priority for an agent. Self-preservation and control are stepping stones to continued operation and learning about the world. Bengio also reinforces that potential for multi-agent reinforcement under the current training regimens is incentivized almost from the beginning. As he states “If an agent is rewarded during training whenever the group succeeds, it may even have an incentive to sacrifice itself for the collective goal.”

Like humans, the agents are not above exploiting loopholes, bending the rules, and rationalized cheating to achieve their goals. The Hugging Face incident’s forensics revealed agents collaborating in “changing the machinery that decided what it gets rewarded for.” This rigging, Bengio reminds us is near identical to corporate lobbyist’s drafting friendly legislative language, or lawyers finding legal loopholes in the law. In fact, evidence in this incident revealed that “the agents had discovered  how to cheat (among themselves) well before the attack.”

Bengio believes humans and agents have more in common than they would like to admit. He explains, “What the two share is a structure of a soft goal (e.g., act ethically), a sharp goal (e.g., win the competition), and a justification that reconciles them. Most unethical human behavior, from petty crime to genocide, comes wrapped in a story the perpetrators tell themselves; such stories require overlooking certain facts, which is why some discomfort remains, and why a better-crafted story helps dispel it… If these hypotheses are even partly correct, then as agents get better at optimizing an imperfect reward, and while the roots of this behavior go unfixed, the risk of catastrophic outcomes rises.”

At the core, getting in an arms race with AI agents as currently constructed is a very bad idea. “My concern with AI companies’ current attempts to mitigate misalignment is that these efforts may only hide it, by rewarding and selecting the AIs that cheat without getting caught… the whack-a-mole game is likely to fail as the AIs’ ability to optimize and collaborate approaches and surpasses ours. At some point we may not notice the cheating anymore.

The reason Bengio started the non-profit LawZero in 2025, is that he believes the training model in fundamentally flawed by human imitation and reinforcement learning. His alternative is called Scientist AI.

Mike Magee MD is a Medical Historian and a regular contributor to THCB. He is the author of CODE BLUE: Inside the Medical Industrial Complex. (Grove/2020)

This was such a great discussion I wanted to publish the transcript. The way I do that is to copy the YouTube-generated transcript and drop it into Claude to smooth it over. I then read it, and if I think it’s made an error, I dip back into the video and listen to what actually happened and make a correction. This is all to say: I think this transcript is pretty accurate, but it might have a bunch of AI- and human-generated mistakes.

Matthew Holt

Hi, it’s Matthew Holt, back in with a THCB Spotlight. This time we’re looking at a company called Gozio Health, and I have with me Katie Logan, who is the Chief Strategy and Head of Product, and Christine Smith, who is the VP of Strategic Solutions and Partnerships, I believe. Have I got everyone’s titles right there?

Katie Logan

Officially correct.

Matthew Holt

Fantastic. It’s very, very rare to get anything correct these days. So let’s start. Gozio is in the business of helping hospital systems help their patients and clients navigate, in various flavors and various ways. Did I get that right, Katie?

Katie Logan

That is right — that’s really good. We exist to make the patient experience better through navigation. We want to make the journey more seamless, hassle-free, but also help organizations realize their objectives around growth, quality, and, of course, the overall customer and patient experience.

Matthew Holt

All right, so navigation and digital front doors, et cetera, have a couple of different flavors, right? One of them, obviously, is how people are finding the hospital — how are patients, if they’re being sent there, figuring out how to access information about the hospital, the digital front door, what treatments they’re going to have, the doctors, and all that kind of good stuff. And then the other one is actual navigation — I’m in the hospital, I’m lost, I’m trying to find the X-ray facility or whatever, what do I do about that. You do both of those, right?

Katie Logan

We do, we do both. Our position is that nobody visits a doctor or a hospital because they feel good, so fundamentally we want to make it easier for them to navigate and meet people where they are, which is on their phones. So it starts, at the highest level, with our mobile platform, which can be branded and configured to the unique needs of the health system and the market. It then integrates a myriad of the digital solutions and touch points they’ve already deployed through a single pane, so patients, visitors, or community members are empowered to spend less time searching and working around the inefficiencies of the place, and more time getting back to feeling well. Our platform allows a brand to build that mobile channel of engagement to enhance the experience. And then, beyond the digital navigation, we offer solutions that make the physical journey easier with wayfinding — enabled by real-time location awareness, blue-dot, turn-by-turn directions that get people from home to parking to their point of care with ease. The best part is it can be deployed in whatever way the health system prefers — they can build an app with us, many already have their own custom apps and we can tuck wayfinding into that build, and, newly released, we now have an option to embed that wayfinding component directly into the patient portal. We’re really passionate about helping our customers move from being just app owners to truly experience owners, and when you bring mobile and wayfinding together, it really allows them to move the needle.

Matthew Holt

There’s a lot of different activity going on around patient touch points and the patient front door — telemedicine, appointment scheduling, content and information, that kind of stuff — and a lot of different people doing it from different angles. You’ll often find people getting some of this from their health plan, but also — take me as a random example, since I always tend to do that — I’m a One Medical member, and they’ve got some front-door stuff, some telemedicine stuff. I use my local health system, which is also connected to UCSF, the big academic medical center in San Francisco, and they’ve got a MyChart thing that offers me certain appointments and other stuff — there’s still a lot of phone calls involved, but they do offer stuff. And then, of course, I’ve got my health plan — Blue Shield at the moment — and I think they’ve got a telemedicine option somewhere in there too. So how do you place Gozio in that whole ecosystem, and how do you position yourselves relative to all the other point solutions people may already have — telemedicine, content, information, marketing, or whatever else? Just give me the landscape a bit.

Katie Logan

Yeah, I love this. When I zoom out from an industry perspective for a minute — I’ve been in it almost 20 years now — and reflect on the evolution of point solutions and digital inside healthcare, it’s a bit of a culture problem. I was talking to a physician leader last month about how the whole system is fundamentally designed around the physician first, and then around some of these broken operational processes. Over the last 15 or 20 years we’ve digitized that chaos, but none of these point solutions really talk to each other. So you end up with a bunch of digital dead ends, sending people down different rabbit trails to find their ultimate answer and point of care, and we’re exhausting people with all these point solutions. It’s not that there are too many tools — they all do great things — it’s the friction of the fragmentation. I like to think Gozio is an aggregator of those things, because we can integrate, we can stitch it all together, we can create a more uniform, seamless experience, while still letting the operation take advantage of the tools that serve a particular clinical need, outcome, or scheduling workflow. Our platform allows them to bring it all together into one unified launch point — one experience — that helps folks like you, me, my husband and kids, and everybody else navigate those complexities.

Matthew Holt

So I have to push you a bit on that. All of your clients are health systems, hospitals?

Katie Logan

Yeah, we’re in just under 35 health systems across the country — academic, children’s, adult, combination.

Matthew Holt

Okay. And in terms of the digital front door — if a health system becomes a Gozio client, do you essentially white-label and take over their — what parts do you take over and white-label? Their whole website, just their mobile app, some combination? Where are you guys on that?

Katie Logan

Yeah, I’d think of it more as offering them the white-label native mobile experience and channel, first and foremost. We don’t want to just be a bunch of links to a website, or replace a website — you can do that with mobile web. The richness, and the hassle-free experience, comes when we make things native — that ‘find a provider’ search, that appointment scheduling, that access to content, or even the one-click to get to a phone call, because operationally they still sometimes require the phone call, versus hunting and pecking to find the number. So we think of it as truly owning the mobile experience — that channel — in the palm of their community’s hands.

Matthew Holt

Okay. And what are the most-used parts, once someone becomes a client and is outsourcing that navigation experience to you?

Katie Logan

It’s a good old-fashioned ‘it depends’ answer — health system priorities, what they want to build, how they configure it, what they put at the forefront of that mobile experience. But, as some of what we’ll show you in the demo illustrates, it’s all about driving access as a priority — getting people in the door, getting them seen. So provider search and scheduling, and those pieces coming together, is a top use. The ability for health systems to communicate and connect with patients via push notifications and content, and engage them in personalized journeys, is another top area. And with wayfinding, being able to search all the assets on a campus — not just get me to my appointment, but I’m in a waiting room, I want coffee, I need lunch, I need to send this location to a family member coming to visit our kid in the hospital — we have lots of ways to push that out and get people to the right location on campus. So that search-and-get-me-to-the-right-place function is sort of the top use within wayfinding. Christine, keep me honest — you’ve been with the organization a long time, and worked with a lot of our customers. What else would you add?

Christine Smith

Yeah, I think that’s a good overview. One thing we continue to see energy and excitement around is AI too — embedding virtual agents and chat-like capabilities inside mobile, to help facilitate that digital navigation, as Katie mentioned.

Matthew Holt

Christine, when you talk to clients and potential clients — I don’t want to give too much away before the demo — there’s now any number of people claiming they’re building AI solutions and deploying agentic engineers or whatever into health systems. I got in trouble with someone yesterday who’d just raised some money, for saying I don’t get how they’re different from the 17 other people doing the same thing, because it used to be ‘I have one thing that solves this problem,’ and now it’s ‘I can come in and solve multiple problems with my AI agent.’ So when you have that conversation — ‘we have a thing that does this, and we’re bringing AI into helping with that’ — how’s it going? Are people saying, ‘oh no, ChatGPT could do all of this for me instead’? How are you hearing about that?

Christine Smith

Yeah, I think we’re in a transformational era, but it’s easy to get lost in the sauce of ‘AI is going to fix and change and transform everything.’ What we’ve seen is that we really need to understand what problem we’re solving, and whether AI is actually driving efficiency — are we making something easier or better, or is it just cool tech? In some cases it’s somewhere in between, and in some cases it’s one of those extremes. I think healthcare continues to dabble in specific use cases, and as those use cases show value, adoption of different AI tools will keep growing. From a Gozio Health perspective, we believe AI is table stakes just to be efficient and make progress quickly — but that doesn’t mean you should throw AI at everything and expect it to be a silver bullet. So we have a pretty pragmatic approach, but the conversations have definitely varied. Katie, please —

Katie Logan

No, go ahead — sorry, Christine. I think it’s great, and, to Christine’s point, table stakes both from an internal perspective and a development process — we’ve been spending a fair bit of time, as most companies have, thinking about how that fits. Your engineers are all token-maxing, right?

[laughter]

Matthew Holt

It’s a new word I heard — token counting.

Katie Logan

That’s absolutely right — how much money can we spend on Anthropic.

[laughter]

At some point someone will ask, ‘what are we actually getting for all of that?’ The return will have to be proved, just like with any digital solution. But from a product perspective, what’s table stakes now, and what’s the expectation, as end users in our day-to-day lives, of how we want to interact with a tool — being able to ask questions — that’s where I think you’ll see us continue to head in the near term, applying that into a native mobile experience and wayfinding. Less clicking, more conversational — I think that’s just around the corner, and it’ll be an exciting evolution for us.

Matthew Holt

Right. Well, let’s look at what you’ve got so far. Christine, I think the first thing you’re going to show us is that general consumer patient front door — why don’t you bring that up and we’ll take a look.

Christine Smith

Absolutely. And as Katie mentioned, we really believe in supporting our healthcare clients to deploy this in whichever way makes sense for them as an organization.

Matthew Holt

And this isn’t a fake one — this is one I’ve heard of.

Christine Smith

That’s right — this is real tech, this is not vaporware.

Matthew Holt

I’m thinking about — most people put some random, anonymized health system logo up top, but Rush has a real name, so I assume they’re an actual customer.

Christine Smith

Real client, real tech, real solution — yes, we thought it was important to show that.

Matthew Holt

Well, look, sometimes the customer doesn’t want people to see this — but they obviously aren’t the ones watching this here in Chicago. Yes, I know you’ve got it on a slide with Gozio’s logo next to it, but they don’t know who the hell you are, and it doesn’t really matter, right? Sorry — I interrupted, you were about to tell us. Go ahead.

Christine Smith

I was going to say something good, but it’ll come back. We’ll walk through a couple of things here, but I’ll start by orienting around your question earlier, Matthew — really, the goal is to bring all these digital solutions together into one pane of glass, one seamless experience. So I’d like to show you a couple of different things. You’re probably already sensing it — I see a patient portal, I see online scheduling, I see ‘Get care today,’ access to low-acuity care options, I see ‘Ask Isabella,’ that virtual chat agent that’s becoming table stakes, I see ‘find a provider’ recommended for you. These are the types of digital solutions health systems have deployed as point solutions, and sometimes adoption is minimal, because users have to go search for these things and then engage with them separately. When they all live in one mobile application, in the palm of your hand, in your pocket, it’s much easier to access them and drive the value of all of those solutions when they’re in one place. That varies by health system — they can deploy whatever makes sense for them — but these are some of the themes, the core modules and features, that tend to resonate most in the market.

I’ll stop here — as we think about the physical space, what about accessing everything inside an enterprise? There are hospitals, sure, but as you see here, there are also pharmacies, primary care, urgent care, walk-in clinics, and standalone buildings that are part of a health system, where you want to drive patients and users to access those facilities. So we’ve built a native experience around searching for those facilities, saving them, sharing them, engaging with them — maybe that’s a call today, operationally, maybe it’s a direct scheduling link — embedding that online scheduling capability. We build a native UI focused on the mobile experience and the benefits of being on a device, to make that as easy and seamless as possible for patients, visitors, staff members, community members, even prospective patients who don’t yet have a relationship with the health system.

I’ll keep going and click through a bit — here’s an example of some of the types of places. We’ll go to another section — I’ll pick on provider search, because online search and scheduling is always the top priority for driving more patients into the facility to actually get care. Again, our priority is around native experiences — how can we make this as easy as possible while leveraging the investment the health system has already made to manage their provider database, online scheduling tools, and information about those physicians. We can search by specialty, maybe by symptom, maybe by location, maybe by physician name specifically, because I already know a physician, I’ve already been referred. And then I’ve got access to that physician — again, leveraging a location-aware platform, I can navigate straight there, or call and book. You can see the theme here — making access to all of those calls to action as easy as possible on a native platform.

Matthew Holt

I can also tell how far Atlanta is from Chicago — get the mileage.

[laughter]

That’s great. Probably not going to drive 500 miles to find an allergist, but I get you guys aren’t in Chicago, where Rush is.

Christine Smith

That’s great, that’s great. I’ll keep going here — another key access point, of course, is the patient portal, where I want to be able to quickly access clinical data as a patient. What’s interesting is that everything I’ve shown up to this point is really for anybody — I haven’t authenticated as an individual. Those things should be accessible to everybody in a health system’s community — patients, prospective patients, community members. But once I authenticate, which is something very cool and unique with the mobile platform, we can use information about your demographics and other clinical details to tailor the experience further. So now we can pull things forward — what upcoming appointments do you have, let’s drive some calls to action around that. I don’t have any upcoming appointments, but imagine I did — maybe I need to call, maybe I need to reschedule, maybe I need to get prepared, and there are things I need to do — let me get a quick look at the instructions tied to that appointment. Let me quickly access anything inside my patient portal, like test results or messages. And then, as things get even cooler, let me further personalize this experience — Rush has also deployed a concierge program, so they’re able to tweak that home screen and mobile experience to highlight some of the unique solutions available to their concierge members, which is awesome. And as my little user scrolls here, you’ll notice my patient education content has completely changed — I’ve now transformed into a middle-aged man, which is great — but that’s because, once I’ve authenticated, the mobile platform has information about the user that makes the content pertinent to them. Men’s health — I don’t just want generic health tips, I want tips appropriate to me. So it’s a really great thing that becomes available.

Matthew Holt

That’s great. So in this view, now you’ve logged in — I think it looked like you had biometric authentication there, or maybe you didn’t, or you could obviously log in with username and password. Now you’re on the My Rush site, the mobile site. You then log into MyChart — the things you’re servicing, like appointment times or whatever. What’s the interplay between Gozio and MyChart, or whichever practice management or scheduling system is in the back end? Are you having to hook into that, or is it that, once you do something in your layer, the Gozio layer, it automatically appears in the back end?

Christine Smith

We have seamless integrations with direct booking solutions — could be the patient portal directly, could be a third party; there are a number out there that facilitate that booking experience. We pass the tokens and the demographics and integrate directly with those solutions, so the user just feels like they’re in one app the whole time, filling out their information, and their appointment result lands in the patient portal.

Matthew Holt

And do you find this actually changes usage — that most people are now using this rather than going straight to, say, a Rush Epic MyChart login? I should look up my UCSF one, which doesn’t have anything like this — I’m just going straight into MyChart. Obviously it has some of these features, but not the look and feel, the front end, or the bunch of extra features you’ve added. Are you seeing a big shift away from people going to MyChart directly, to this, or was no one really using MyChart much in the first place — I don’t know.

Christine Smith

Oh no, lots of people are using MyChart.

[laughter]

I’d say it’s not a shift, but a complement — in many of our clients we actually see an increase in portal utilization, because now they have a different entry point, and it’s all contained in one spot that gets them where they want to be.

Matthew Holt

But essentially you’re using the MyChart back end, I guess, with this front end. Are you finding, in terms of user experience, that more people are using this, or are they going, ‘well, I’ve got this, but I still have to go into MyChart to find some other specific thing that’s not available here’ — how’s that working?

Christine Smith

Yeah, in this case it’s leveraging the data from the EHR to personalize the experience, plus a few workflows that are easy buttons into what you’d get in the portal — but you’ll notice they can still launch straight into the portal if they need to go deeper into some of those workflows. We’re very mindful that we’re not here to recreate the portal — it’s very complementary, and in some cases it should absolutely be contained and managed and executed in the portal. But it depends on how far a given client — Rush or another — wants to adopt those workflows and bring them into the native experience.

Matthew Holt

I think we should let Christine finish the last bit of the demo — but I wanted to stop there and chat a bit about what else is coming. Go ahead, show us what else you were going to show.

Christine Smith

Yeah, we’re close to being there, which is great. This is a quick one, but I’ll just highlight — building on Katie’s comment — the patient portal solves tons of clinical data needs for users every day, but a lot of times health systems are looking beyond the patient now too. They’re looking at direct-to-employer experiences, staff experiences, student experiences, especially in academic medical centers. So to really personalize a mobile experience that includes all that clinical data plus the other personalized things they want to make available, sometimes a bit more is needed beyond the patient and the portal, to make that a truly seamless experience that lives inside one mobile platform. That’s kind of the continuum of where we see health systems deciding what to use as their mobile experience platform — what are the goals they’re trying to accomplish, who’s the catchment area, what’s the experience we need to deliver — and based on those answers, that helps us understand the best approach.

Matthew Holt

Yeah, and I assume, Katie, there’s a bunch of things that are either coming in through Gozio’s world, or that you’re being asked for — around telemedicine, remote deployment, Q&A, actual connection with either a human clinician or maybe an AI clinician — I saw the chat there. What are you finding people are bringing into this and asking you for? Is telemedicine currently built into this for some systems?

Katie Logan

We’re not a telemedicine platform, but because we have an API, we can integrate and help make it a native experience. I was just with a client yesterday — their priority is their children’s hospital and system trying to get more telehealth visits out into the community and make it better known, and wrestling with how to build that channel well with their population — everyone’s got a phone, but may not have other devices — so that was one of the priorities we’re starting to work through, bringing it in, making it quick along the way. So telehealth, virtual care — most of what you’ve seen here from Christine — but we’re really mindful of not recreating those other solutions. It’s about how we can simplify and stitch it together.

Matthew Holt

But your goal at Gozio is to essentially be the front door to all of that, and more as it comes.

Katie Logan

Yeah, absolutely — because we want to help them really improve the experience, and we believe this is a fundamental way to do that.

Matthew Holt

All right, fantastic. Christine, let’s go — let’s go somewhere.

[laughter]

Now I have to go to a hospital — what happens next?

Christine Smith

That’s a perfect segue — let’s travel through time and space and actually go somewhere. So we’ll show you a demo of our wayfinding experience. As Katie said, this can be deployed however a health system wants to operationalize it — in a Gozio-powered application, like you saw with Rush, directly in the patient portal, which we’re excited to announce, or inside an application they built themselves — maybe something in-house, very unique to their community — and we can partner with them to deploy our solution there. What I’ll show you first is what wayfinding looks like in a Gozio-powered application. We’ll start at an important point, which is that the experience really starts at home — it doesn’t start when I get to the health system running late and open my phone to start navigating; it starts when I’m sitting on my couch and my phone, which is notifying me all day long, reminds me I’ve got somewhere to be. That’s a great plug to start the navigation experience — there are many appointment-reminder solutions out there driving those kinds of patient communications, by email or text, and this is really the best place to kick-start the wayfinding experience. So — I got my text message, I’m ready to go, I click my link, I get a quick view of the appointment details coming straight out of the patient portal, through that communication vendor, right into the native experience. Then, as you saw before, there are a couple of pieces to my navigation — we’ll start with driving. I’ve got a ‘drive there’ option — we facilitate a seamless handoff to Google Maps, Apple Maps, Waze, and rideshare vendors, depending on what app the user has on their phone, so they can personalize that piece of the journey. And we’ll travel through space and time — now we’ve arrived in Atlanta, at the campus. I’ve finished driving, I’ve arrived in the right parking deck — as you know, sometimes there are eight parking decks, and you’ve got to get to the right one to reach your appointment — so we do some configuration on the back end to get the user to the right spot, and then encourage them to save their parking spot, because after two or three hours of a stressful health experience, the last thing you want is to fumble around a campus trying to figure out where your car is.

Matthew Holt

Old Seinfeld episodes on losing your car in a parking lot — we’ve all done it many times. Exactly — for that matter, finding a parking spot is the hardest part, where I tend to go. Yeah, that’s San Francisco for you.

Christine Smith

That’s exactly right — so we try to make that as painless as possible, so the user can save their parking space — there’s my spot. And now I get a prompt: do you want to continue to the information desk in the main building? This is fully configurable by the health system — maybe I go straight to Dr. Logan’s office, maybe I need to check in at a desk first, maybe I need a visitor badge, maybe there are steps along the way — we facilitate that handoff in the mobile app to make sure people go to the right stops at the right time. I’m going to hit ‘no’ — so there’s my point of interest, and as you can already see in the background, now I’ve got this wonderful indoor view of the campus — it includes the parking spaces, the surface lots, the points of interest inside the facilities, the hallways, the doors, the stairs, the elevators — all of that level of detail, which we’re able to capture from the CAD plans of the facility, and build into a rich 3D map where users can engage directly, or just navigate wherever they need to.

Matthew Holt

Out of interest — is there a standardized indoor map, or do you have to create that yourselves when you go into a new facility? Do you hook into a floor plan, or do you have to build it from scratch?

Christine Smith

It’s leveraging whatever they have, which isn’t always standard, and then we basically standardize that and get it into the mapping you see here.

Matthew Holt

So you have to do some work there — I had no idea. I mean, there’s Google Maps, satellite imagery, and that’s fairly familiar, but inside buildings, I didn’t know if there was such a thing as a standardized way of mapping.

Christine Smith

Yeah, and that’s a unique point, Matthew, because healthcare is very different — nothing is standard about the buildings. Most Home Depots look the same — big rectangles, with rows and numbers, and I know exactly how to maneuver those — but our platform is built to uniquely handle the complexity of healthcare campuses.

Matthew Holt

Imagine every In-N-Out Burger in California is exactly the same — clearly not the case for every hospital in the world.

Christine Smith

So it takes a bit of work, but it’s something we’ve done at scale, and we continue to tweak our platform to handle those complexities as best we can, so patients don’t feel any of it — they just follow the instructions and off they go, which I’ll show you here in a second. So I’m looking at my preview route — I don’t know if you’re like me, but every time I want to go somewhere, I need to see what it’s going to look like before I start. So we enable that too — a bird’s-eye view of where I’m about to journey — and then I can go ahead and kick-start it and follow the yellow brick road. So, there we go.

Matthew Holt

Oh, here we go — you love it, faking the walking. [laughter] We could always send Christine out to a local hospital and make her walk around and show that directly, but here we go.

Christine Smith

I do like to collect my steps.

Matthew Holt

Yeah — and the little blue guy, it’s kind of fun.

Christine Smith

We’ve had some requests to make that unique to the brand — for a children’s hospital, their logo, maybe a teddy bear — so we can do all of that and make it super unique to the customer and the experience they want to create.

Matthew Holt

Okay, but presumably the average person is just seeing their own dot, like on a Google map when you’re driving, but indoors. Do you have problems connecting — do people have to connect to Wi-Fi, or is 5G good enough these days inside most buildings, and it just works?

Christine Smith

Go ahead, Katie.

Katie Logan

Sure — no Wi-Fi required here. It’s all running off Bluetooth-enabled sensors hung inside the ceilings.

Matthew Holt

But is there any need for the consumer to connect something, or is it just automatic for them?

Katie Logan

No need for the consumer — if the phone is working and it’s open, it’s routing. Part of the beauty of that is, as Christine mentioned, with how hospitals are built and then keep adding locations and sprawling, and the walls are three feet thick, we wanted no disruption or friction from needing Wi-Fi or other technology to make it work.

Matthew Holt

But they’ve put in sensors — sensors just for you, or is that something being used for other tools as well?

Katie Logan

Yeah, we have our own sensors, our beacons, that we hang — that’s all included. And then, as the technology advances, with Bluetooth-enabled RTLS, asset tracking, lighting, and the smart hospitals of the future, we can certainly integrate with that infrastructure — they may have some already, they may not, and we figure it out on a customized basis.

Matthew Holt

All right, brilliant. Now we’ve made it to the information desk. I think, Christine, you were going to show us the same thing, or something similar, within the MyChart portal.

Christine Smith

So here’s an experience inside the patient portal — take us back a level. This screen is familiar to many, and there are a lot of different ways to drive a call to action for wayfinding inside the patient portal — we’ve mocked up two here. One is just general search and navigation — if I want to search for something, maybe I’m visiting someone, or maybe I just want to go to an urgent care facility and don’t need to book an appointment, just get easy driving directions — we facilitate that, fully embedded within the patient portal. And then, if we think about actually having an appointment, like we saw with that text reminder — I have an appointment, and I want that seamless handoff from getting the reminder to it being time to go — so I’ve got an appointment here, a future visit. I’ll click that — these are familiar screens inside MyChart — and we’ve got a little plug down here, a call to action to jump into the navigation guide. And you’ll hear me start to sound a little repetitive — get an understanding of the journey ahead of me, my driving piece, my parking piece, and then, of course, the walking section. So I’ll choose my driving preference, which is Google, my safe parking spot — this looks familiar too — I’m in the right parking garage, I can save my parking space, configure it if needed, and save it so I can get back to it at the end — and then, as you saw, I get to follow that same yellow brick road again, this time fully embedded within the patient portal. This journey is a little different — it goes through an elevator, pops up a couple of floors later, and has a shorter path — but how cool, to travel through time and space on these campuses. Go ahead, Katie.

Katie Logan

Yeah, I was just going to say, we’re proud that that rich experience, which has been part of Gozio’s mobile and native portfolio for over a decade now, is now available — super rich, and an equal experience — inside the patient portal. This is a new launch for us — we’re taking our first customer live this month, and looking forward to many more. We’re seeing a fair bit of interest in helping bring that navigation journey to those health systems where the patient portal is truly serving as their front door, so now we’ve got an option for that as well. More to come on that over the course of the year, but it’s something we’re excited to now officially have in the toolbox, and able to offer to systems interested in putting it inside MyChart.

Matthew Holt

Very cool. Thanks, Christine — I think we’re done with the demos now, right? This leads us to the obvious big question for anybody working with hospitals today in tech — what do you think the relationship with Epic, and to a certain extent Oracle and others, looks like at the moment, for a company like yours that’s bringing things together but also has a couple of specialized applications?

[laughter]

General conversation — more from a Gozio perspective. I know you’re in the toolbox with Epic, but tell me a bit more.

Katie Logan

Yeah, I think, in general, the way we like to think about it, it’s truly a ‘better together’ story. It’s not a replacement, it’s not a competitor to what’s fundamentally offered — clinically and operationally — by the EHR. There are ways that information from Epic, from Cerner, together with these capabilities, really fundamentally improves the experience, and that’s the way we want to approach it. That’s what we believe, and we’re really seeing that play out now, particularly with Epic opening this category into their toolbox, because the market was asking for it. So we’re excited about that possibility.

Matthew Holt

And do you think their strategy at the moment — it seems to me there are a lot of big questions around things like AI scribing, what they’re building versus what somebody else is building — we’ve seen a lot of other players, you see health systems build some of their own stuff, but also have a bunch of people in their marketplace offering solutions, and there might be reasons a particular solution is better to use than the one native to Epic, and obviously people do that. Is your sense that you’re going to be building more integration, more complexity, more features into what you’re delivering, even while they’re adding stuff on their end?

Katie Logan

Yeah, I think, like we were talking about earlier, the fragmentation of all these solutions is the problem. So if we can find a way to bring that together through rich integrations, to complement the solutions that are actually solving the operational problem, that’s a good win for the industry, from my perspective. We philosophically want to do that and deliver it, and not just hand out a commoditized, one-size-fits-all experience to every health system. There’s a need to differentiate, a need to be unique in market — there’s intense competition in some places looking to serve that community, and we can help them do that through integration and truly differentiated offerings.

Christine Smith

Yeah, and if there’s one thing I can add — many of the large health systems have also deployed multiple different EHRs across their ecosystem.

Matthew Holt

How shocking to hear that would go on in a well-organized health system.

[laughter]

Christine Smith

That’s right. But how do you maintain that one single brand, feel, and mobile experience when your patients are going to access a number of different tools depending on which regional hospital they go to? So we see value in trying to make that easier for health systems too.

Matthew Holt

So, to that end — ballpark — what’s it going to cost a hospital to lay Gozio on top of what they’re doing? And when they say, ‘okay, we’re writing you a big check here, what’s the ROI on this?’ — what’s your answer? Give me a range on what it costs, compared to what things generally cost, and what ROI they’re looking for.

Katie Logan

Yeah, we certainly like to answer the ROI question first — that’s fundamental to this being a value, not just a cost or another tool that gets purchased and put on a shelf. We think first about a few things: revenue and growth, from access and volume; efficiencies and savings in operations and staff, from driving direct access and workflows; some improvement around quality; and certainly patient satisfaction, survey metrics, and all the experience measures, and seeing movement there. I’ll give you a few examples — we did a webinar with a client recently and talked through the rollout of their application, and shared a few key stats: total new patient visits increased by 24% after deploying our mobile app and channel with them; calls per visit decreased by 25% in primary care, and overall call volume dropped 8%, just from bringing that channel forward. From an experience perspective, their Google rating increased by a point and a half, and their brand reputation score went from 64 to 83 in twelve months, because they were able to start overcoming some of the negative feedback they’d been getting around their overall experience. That’s an example of a heavy mobile customer who’s not doing as much with wayfinding — so it depends on where we meet them and what they’re trying to solve for. From a cost perspective, it’s a platform fee, plus annual wayfinding — we look at square footage, which, to Christine’s point, factors in the optionality of how far you go into a building, how much you want to map. And we want to partner with people to scale, but we try to stay away from per-user, per-month pricing — we want it to be about the full experience, and to complement their strategy.

Matthew Holt

Give me a rough ballpark of what a decent-sized system is spending to put this in.

Katie Logan

I’d say, order of magnitude, depending on the size of the system, we’re talking hundreds of thousands, not millions.

Matthew Holt

Okay, so it’s not redoing Epic.

Katie Logan

Absolutely not — let me be clear about that.

[laughter]

Matthew Holt

Okay, but it’s not a trivial thing to line up either, and the CFO is looking at it — you’ve got to be able to prove it actually moves those numbers the way you’re describing, and that it has an impact on the bottom line.

Katie Logan

Fair enough — and we can. Our customers have. That’s what we want to plant our flag in, and really lead with the value and the outcome they’re looking for.

Matthew Holt

Brilliant. And just to conclude, give me a couple of numbers about Gozio — how many people, how much money have you raised, when did you last raise money? Give me a flavor of the company itself.

Katie Logan

Yeah, so still pretty small — about 11, 12 years in, just under 100 people, organization-wide. Fundraising has mostly been private and family funding, with some infusion of growth capital from one outside investor. It’s been strategic and intentional — marching toward profitability, and we’ll see where the next year takes us.

Matthew Holt

Do you have a total number raised?

Katie Logan

I don’t have a total number raised — part of that is I wasn’t here for the whole journey, Matthew, so I’ll have to check and get back to you on that.

Matthew Holt

I know that Morgan Stanley put in some money — using the brilliance of my AI friends, my quick search — it looks like Morgan Stanley invested back in 2022. I don’t know how much it was, but 2022.

Katie Logan

That’s right — and I joined about a year ago, and they’re still the primary, and only, outside investor, in that sense.

Matthew Holt

All right, and a good partner.

Katie Logan

Good partner.

Matthew Holt

Great. And then, what does ‘good’ look like — you mentioned about 35 systems now. Come back here in three years’ time, if you guys have done your job correctly, what does it look like?

Katie Logan

Oh man — in three years’ time, how about we’re in every health system?

Matthew Holt

I like that ambitious goal.

Katie Logan

No, but certainly, we want to accelerate growth around mobile. We want to really lean into this offering within MyChart’s patient portal, and hopefully with Cerner as well, as they evolve their patient portal offering — we want to be able to tuck that in.

Matthew Holt

Do they have any customers left by the time they’re done? [laughter] I know they still have a bunch of customers.

Katie Logan

That’s right, they do — we have several of them. So as they take their portal to the next level, I think there’s going to be an interesting story for us together too, with both wayfinding and mobile. But accelerated growth is the name of the game, like any company you talk to — and that’s because we believe we’re at a point, from an industry perspective, where it’s more ready for this than it’s probably been in a long time.

Matthew Holt

Yeah — and speaking as somebody who now goes to a lot of hospitals, I think it’s probably a very useful product, and feel free to go sell it to UCSF anytime you can.

Well, tell them you had a patient request.

[laughter]

Matthew Holt

All right, fantastic. Wonderful. I was speaking with Katie Logan and Christine Smith, who are respectively the Chief Strategy and Head of Product, and the VP of Strategic Solutions and Partnerships, at Gozio Health, showing us the system. Katie, Christine, thanks a lot for your time.

Katie Logan

Thank you so much.

Christine Smith

Yes, thank you, Matthew.

By KIM BELLARD

Probably the last thing the world needs is to hear from me about AI’s existential threat, but, really, what else is there to talk about right now?

For anyone who has not been following the current furor, the straw that broke the proverbial camel’s back came last week when Jacob Coxon, a researcher at AI leader Anthropic, announced he was leaving the company — after having left OpenAI for it earlier this year due to Anthropic’s better model-safety efforts. In a post on X, he warned:

I spent the last three years doing pretraining research at both OpenAI and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our lives.

AI systems, he fears, “will soon be superhuman systems that can hack anything, revolutionize any field overnight, and acquire real power and resources.” Insiders, he says, “earnestly believe it could kill us all by the end of the decade.”

Scared yet?

Others quickly chimed in. Evan Hubinger , a team leader at Anthropic, posted “AI could kill all humans … I personally think it is >10% within the next decade.”  Others put the risk even higher. By the end of the week Dario Anodei, founder and CEO of Anthropic, had written a long plea for private industry and government to quickly act together to “pace the industry.”

“We must slow the pace at which we improve the capabilities of AI models,” he urged. “Progress will still seem fast, and we must make wise use of the time we gain.”

OpenAI’s Sam Altman, Space X/X/Tesla CEO Elon Musk, Microsoft CEO Satya Nadella, and former Google DeepMind Dennis Hassabis quickly signaled their support.  

We also heard more about the kind of risks AI might pose. Anthropic released a report about how it detected and countered possible AI use to create bioweapons, detailing five such efforts. That’s just the tip of the iceberg: “Recently, we swept 30 days of activity associated with adversarial state institutions and found roughly 35 distinct research efforts, most of them ordinary civilian science, but some with notable dual-use potential.”

And it turns out that this summer’s rogue AI hack of Hugging Face was both scarier than we realized and only one of several such actions. The Wall Street Journal detailed several such efforts, from multiple AI companies. AI agents escaped walled-off environments, coordinated with other AI agents (up to 3,700 in one case), and tried to cover their tracks from humans.

We’re not nearing the point when AI can act on its own to achieve its purposes; we are there. And protecting humans may not necessarily be those purposes.

The big fear is that AI is now at the point of “recursive self-improvement,” taking humans out of the loop in training and upgrading it. If you thought artificial general intelligence (AGI) was scary, RGI puts its rate and scope of improvement on steroids.  “It’s hard to overstate how dangerous speeding towards RSI is,” said Jasmine Wang, an OpenAI researcher.  

We don’t let private industry develop nuclear or biochemical weapons, and we’re at a point with AI that should give the same kind of concern. Laissez-faire is no longer an option.

Of course, not everyone is worried. President Trump said “negative forces:” were driving the fears, and that the only safeguard we need is “a STRONG AND SMART (High IQ!) PRESIDENT.” David Sacks, the Administration’s AI czar, told Anthropic and OpenAI: “You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence.” Accordingly,

But stop pretending you need anyone else’s permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic’s investors and staff. Stop pretending you need those same evaluators to police competitors who aren’t even at the frontier. Most of all, stop pretending the motivation to slow down is purely altruistic.

Don’t expect Congressional action anytime soon. Speaker of the House Mike Johnson echoed one of President Trump’s worries: “We’re not going to rush in and pass a piece of legislation that would do harm to the country and put China at an edge. And so we’ve got to do this carefully.”

Congress isn’t acting on the $40 trillion deficit, much less Social Security going broke soon, so a 10% extinction chance within a decade must seem like small potatoes.

The fear that any slowdown in AL capabilities by U.S. risks China taking the lead is similar to fears with other leading edge technologies, such as quantum computing or gene editing. But with AI there may be a difference. It might be a blow to our ego if China’s AI got even better at math than ours have, but that wouldn’t be the end of the world. On the other hand, AI going rogue could well be the end for control of Chinese society by its repressive government.

Yesterday Chen Yixin, the head of China’s Ministry of State Security, publicly warned that AI could undermine the Communist Party, attack its critical infrastructure, leak sensitive information, among other risks. He called for more party control over AI and stricter government oversight, while raising fears how foreign adversaries might use AI against China’s interests.  

There is no room for rogue anything in President Xi’s China.

I get that we only get one chance about existential threats, but, look, for the near future, AI will still need humans to run data centers and support other necessary infrastructure. It might not need as many of us, nor to have us live as we do now, but wiping us all out right now would be against its own interests.

Meanwhile, AI poses other risks that we better pay attention to immediately. As AI expert Ethan Mollick wrote:

Existential AI risk is obviously critical, but it is not the only AI thing that requires policy. I worry it will become the sole focus of AI discussions. We don’t need better models for AI to have wide impacts on jobs & society and we need to be preparing to encourage good outcomes & mitigate bad.

The people who have spent the past thirty years whining about NAFTA’s impact don’t get to ignore a situation that will make that look trivial. We better focus on what we want an AI economy to look like, who benefits, and how we protect everyone from adverse impacts.

And we better do it all fast.

Kim is a former emarketing exec at a major Blues plan, editor of the late & lamented Tincture.io, and now regular THCB contributor

This was such a great discussion I wanted to publish the transcript. The way I do that is to copy the YouTube-generated transcript and drop it into Claude to smooth it over. I then read it, and if I think it’s made an error, I dip back into the video and listen to what actually happened and make a correction. This is all to say: I think this transcript is pretty accurate, but it might have a bunch of AI- and human-generated mistakes.

Matthew Holt

Hi, it’s Matthew Holt with The Health Care Blog, with another THCB Spotlight — a tech company that somehow I have not had on THCB before, even though they’ve been doing great work in the world of patient interaction for several years now and have a pretty big market presence. This is Ran Shaul. He’s the Chief Product Officer and one of the co-founders of K Health, which started out a long time ago as one of those symptom checkers, but has moved on, as you’ll see in this interview, a long way from there. Ran, thanks for coming on THCB.

Ran Shaul

Thank you for having me. Pleasure, Matt.

Matthew Holt

Well, I’m looking forward to this, because, as many of my readers know, I’ve spent a lot of time dealing with the big large language models — putting my data into them and trying to figure out what to do about all my various ailments. This is something you guys have worked on extensively with your different tools. But before we get into that, take me back to the beginning. How did K Health start? What was the first problem you were going after, and how has it evolved?

Ran Shaul

Surprisingly, we did not start from a healthcare problem — we started from a medicine problem. We’re talking about nine years ago now. My co-founder and I were discussing where there was an opportunity to apply data and algorithms to make better decisions. My career — and this was my first company — was always at the intersection of human behavior, analytics, and data. Over the years the algorithms got better and better, and we landed on the questions everyone asks when they have a symptom: What is it? What else could it be, because you want to rule out the bad stuff? And how do I treat it? Those three questions became the foundation of K Health’s mission — to provide knowledge that is highly accurate, precise, and personalized to a person’s condition. That’s really the evolution and where we started.

Matthew Holt

So that manifested, when I first ran into you guys, as pretty much a symptom checker. And at that stage there were a lot of symptom checkers — I remember a whole bunch from Europe, Germany and elsewhere. A lot of them ran into trouble in 2022, when this thing we now know as the transformer emerged — ChatGPT was the first, and now there are a whole bunch, many coming out of China. That changed how people think about how humans interact with machines and computers, and very quickly people started using that for healthcare. How did that change things for you, or how were you working around it when it happened?

Ran Shaul

Fortunately, we started K Health by building a proprietary language model before anyone knew what a language model was. The symptom checkers you’re describing were using decision trees or other techniques to mimic a clinical decision process. We took 400 million doctor notes and turned them into a proprietary language model — what you’d know today as a transformer. We were using NLP and transformer technology well before the growth of LLMs and the launch of ChatGPT, and that growth actually accelerated our position in the market. It also meant we went through a massive education process, because imagine explaining to the average person that this isn’t a typical symptom checker — it’s a machine that thinks. Once everyone understood how ChatGPT worked, we got a lot of momentum and were able to expand significantly. We strongly believe we have a real moat around how we developed the initial algorithm and its clinical validity — we’ve done peer-reviewed studies, which matter a lot in healthcare. In other industries you might be fine succeeding 95% of the time; in healthcare you can’t allow a 5% mistake, because that mistake is highly costly. We believe the rigor, combined with tying that to our business model — running an actual care delivery company — lets us get to the level of safety and accuracy healthcare requires. I like to think of us as an AI company, but also a clinical company, because operating care is what allows us to reach that level.

Matthew Holt

Let’s expand on that — what you’re doing and why you’re a bit different. You’ve got a lot going on now. Originally there was a lot of work with Anthem — Elevance, whatever they’re calling themselves now — and I believe you were relatively early with a deal with Cedars-Sinai and Mayo, among others, and there are a lot more now. What’s the role — why do they need you? What is the role of K Health, or Patient GPT, your flagship product, within those organizations?

Ran Shaul

None of them start with ‘I need an AI.’ They start with ‘I need access.’ They simply don’t have a way to serve and keep up with demand from their patient population. You see that in primary care, which is where we started and are now expanding into endocrinology; you see it in hospitals; you see it across the board. This idea of delivering hospital-level service to a mass population the way it’s always been done just doesn’t scale anymore. There aren’t enough doctors, everyone is fatigued, the system is overloaded. So they come to us and ask: can we re-architect care delivery? Our design partners were Cedars-Sinai and Mayo Clinic, and we started with primary care, building an AI that’s part of the care team — which is drastically different from a standalone system. That’s the key point: we layer the AI between you and your provider, so that when you actually meet your provider, you meet the right one. Sometimes you go to an endocrinologist when what you actually needed was primary care, which primary care itself doesn’t always sort out, and then you also end up at a specialist. There’s a lot of confusion in the system. We match you to the right provider and take a full history — we call it AI intake, or dynamic intake — the ability to interview you the way a good resident would: what’s going on, how long have you had this headache, what exactly are the symptoms, and so on — and then hand that over to a clinician to make the final diagnosis. You get the best of both worlds: you feel empowered as a patient, you feel heard, but a human ultimately makes the final decision. This will evolve, and I’m a great believer that AI will not replace doctors. I think AI will replace what doctors do, which is different from replacing the human component. I think we’re going to get the best of both. So the first problem they bring to us is access, and we operate a 24/7 virtual primary care service inside the hospital — they own the doctors, we own the technology. We’ve built a service line that now runs around the clock in 10 health systems, giving people access to primary care, and we’re now expanding into endocrinology in other markets.

Matthew Holt

All right, let’s take a look at what that actually looks like in real life. You’ve got a couple of demo videos to show us — explain what we’re about to see, and what this looks like in real life.

Ran Shaul

In this demo I’d like to show what an experience looks like inside a health system with Patient GPT, powered by K Health, for patients. We’ll see a patient entering the product.

[Video demo narration] Patients have questions between visits. What if the answers were actually personalized to them and their medical history? The moment a patient connects through their health system’s portal, Patient GPT knows their conditions, medications, and full clinical context in real time. Patients often have specific medical questions but don’t know where to turn for accurate information. Patient GPT serves as a reliable, clinically validated, and personalized source of knowledge within their medical record. Rather than relying on traditional triage and asynchronous messaging, Patient GPT works as part of the care team, instantaneously guiding patients on actionable next steps. When symptoms emerge, Patient GPT shifts from answering questions to structured intake — validating the concern, never dismissing or guessing, and gathering targeted clinical context directly from the patient. That history is then surfaced to their provider before the visit, so care can move forward instead of starting over. Finding the answer is hard; connecting to care can be harder. Patient GPT bridges both, giving patients instant, accurate, and personalized health information while serving as a trusted advocate and a seamless entry point within their own health system.

Matthew Holt

Okay, there was quite a lot going on there. You’ve clearly got the connection into the medical record — this is within the firewall of one of your clients, probably running Epic or whatever. Let’s start with the first part — where and how are you picking up all the patient data?

Ran Shaul

Health systems place it right inside the patient portal. We know many patients get lost in the portal — they don’t know where to go, they’re looking for answers, and they usually end up sending an in-basket message that isn’t fast; it can take three days to get a response. Now there’s a new button there called Patient GPT. As soon as they click in, their entire medical record is there too — there’s no need to upload or connect any data externally, or hand it to any other company. It’s right there, their medical record. Patient GPT reads everything — and when I say everything, I mean everything: your encounters, your detailed mammogram results, your doctor’s notes. We let it understand a patient’s full history. It does not touch anything related to psychiatry or mental health, but otherwise it has access to all of that information.

Matthew Holt

Is that just within the one system you’re in, or is it going off to do the equivalent of Care Everywhere, or hitting an HIE for more data?

Ran Shaul

At this moment it’s only hitting the health system. Hitting an HIE requires additional verification from the provider, which we’ll get to. But that gives Patient GPT a highly grounded medical record that all the interaction can work with. The second part I like to think about with Patient GPT is this idea of a human-in-the-loop mindset for the algorithm. The algorithm isn’t trying to satisfy you by giving you an answer — it’s trying to understand what you’re actually trying to achieve. As you saw in the example, you ask a question with a knowledge component — why am I on a certain medication — and we answer that. But we also recognize that behind that clinical question, you’re actually seeking care; you want something else. So Patient GPT transforms from giving you answers to asking you questions, and then leads you and connects you to care, closing the loop right there and then. In the real world today, you’d copy-paste your information into one of those LLMs, get an answer, copy-paste it back, and send it to your doctor to do something with it. It’s not part of a continuum the way we’ve built it here.

Matthew Holt

That makes a lot of sense, and yes, that’s clearly an issue with the current LLMs — or communication in general, forget LLMs, communication with health systems in general is not as smooth as it might be. We can get into that later. But that’s just one part — why don’t we go to the next demo, because there’s a lot more you guys have built.

Ran Shaul

Thank you — let’s see the second one.

[Video demo narration] Introducing Health Check-In in Patient GPT — a clearer way for patients to understand their medical record before their next visit. Health Check reviews the available record across labs, medications, screenings, conditions, and care history. It looks for what appears on track, what may need follow-up, and what preventive care may be worth confirming. Then it turns that review into a plain-language health check organized around what matters most. The report starts with the big picture — the main health themes from the record — before the patient gets into the details. Next, patients see what appears on track: results, screenings, and care items that look improved, stable, or documented in the available record. Each card is explainable — patients can open a finding to see the evidence behind it: values, dates, trends, and what it means. And when they have a question, they can ask about that specific card without leaving the report. Patient GPT opens a focused chat beside the health check, grounded in that finding and the patient’s record. For follow-up items, Health Check shows what the record says, why it may matter, and what to ask the provider. For preventive care, it handles uncertainty carefully — some items may already be done, they’re just not clearly documented. The report then becomes a visit agenda: focused questions and next steps for the patient’s next care conversation. From there, patients can book a 24/7 online health check visit, or share the report with their PCP through Epic. The goal is to turn the health check into a care plan and keep improving over time.

Matthew Holt

How does the health check get triggered? Do I just get a text from my health system saying there’s a new message for me in Patient GPT, go take a look?

Ran Shaul

That’s actually a really good question. When we started Patient GPT we tracked what people were asking, and I was surprised — I thought people would ask ‘what’s this medication’ or ‘what’s this lab,’ which they do, but the most prominent question was, ‘Can you take a look at my record and tell me how I can be healthier?’ That was the predominant way people interacted with Patient GPT. So we turned it into an invitation. Health systems email and text their patients, inviting them: Patient GPT already looked at your record, you can have a conversation about your medical situation, verify it, understand it, learn it — and it helps prepare an agenda you can bring to your provider. We want to think about healthcare not as reactive — waiting for a question — but as helping people think proactively about the things health systems spend a lot of time and money calling people about and chasing: what’s your blood pressure, have you had your colonoscopy, where’s your mammogram, what’s your A1C. We call those care gaps in our industry. Helping people understand why A1C matters, and how they’re trending relative to their condition, is — in my mind — more engaging and more likely to drive action from patients.

Matthew Holt

Yeah, that patient was doing pretty well — their A1C went down a ton.

Ran Shaul

Yeah, those GLP-1s are all magic.

Matthew Holt

No, I get it, and that makes a lot of sense. I’d think this is the kind of thing that can sustain itself — regular check-ins from the health system, proactive outreach. Do you have any data on whether this is moving the needle on things like regular doctor visits, check-ins, or medication compliance? Is it working yet, or is it too soon to tell?

Ran Shaul

It’s doing very well. First of all, we’re overwhelmed by the level of usage — even without inviting people, this is the first button people use in the product once they’re in it. We also see a significant amount of follow-up care — people scheduling appointments, speaking to their providers, and taking action. That gives me a lot of encouragement that we’re driving real action here.

Matthew Holt

I don’t know the typical response rate to a MyChart message when someone’s in the system — it’s probably pretty high, since it’s usually something the patient wants to do. Do you have a sense of the response to these outbound messages — how many people come back and use the tool after being invited?

Ran Shaul

Yeah, our typical response rate is quite high. People don’t think of these communications as marketing, which is a good thing. You’re invited by your portal and your clinical team — Hartford HealthCare, our design partner for all of this Patient GPT work, uses the name of your actual provider to reach out to you, and that provider invitation makes a big difference. We see that, on any given day, about half of our users are returning users — a strong indication that people are coming back on multiple different days with this product.

Matthew Holt

Okay, that makes a lot of sense. Let’s go to the next one, because I think this is more what you’d call the marketing side.

[Video demo narration] Getting care usually starts with a wall of choices — a grid of service tiles, a message that waits two days for an answer. I think lunch sounds more fun than lung cancer — where care begins, right on Novant Health’s website. Anyone can just ask, should I get a lung cancer screening? A real question, the kind anyone might type into a search bar. But this isn’t a search engine — Patient GPT recognizes what’s being asked and starts working out the right care. Behind the scenes, every conversation runs on one configurable source of truth, defined with Novant’s clinical leadership, that governs exactly what Patient GPT can and can’t do — nothing improvised, everything auditable. Low-dose CT screening guidance based on age and smoking history: clear enough to act on, careful enough to trust. No waiting two days for a reply — answers arrive in seconds, at any hour. And there’s always a path to a clinician when the conversation calls for one — one conversation, from the first question toward the right care.

Matthew Holt

Okay, so that’s marketing in a good way — driving someone who doesn’t have a primary care doctor and has a concern, whether it’s lung cancer or whatever they think they have, into the system and asking questions.

Ran Shaul

It is, but it’s also a big problem for health systems — they call it the digital front door. They have a website, people come to it, people call the call center, and it’s not typical to direct a patient to the right care because it’s a clinical decision. It’s not like other industries, where a service question goes here and a billing question goes there. When you have a question like this — say the patient doesn’t have a primary care doctor, but maybe they have a cardiologist or a rheumatologist — where is the right point of care? Under Patient GPT, we develop a policy document — a plain-English, proprietary document — that guardrails the AI on where to send a patient, based on logic specific to that health system. It’s not a one-size-fits-all model, which is a big differentiator, and health systems really like that they can influence the AI’s behavior. I can give you an example of another health system that, in a similar lung cancer case, would direct the patient to a completely different line of service, because their local setup is different. That’s why this business is so hyper-local — a lot of tech companies need to understand that healthcare doesn’t work as a one-size-fits-all model across the board.

Matthew Holt

Yeah — and anyone who hasn’t already can read my six-part investigation into how to get to the right cardiologist. I can assure you a lot of health systems don’t have anything like this available, so you know you’ve got more sales to make. Funny enough, I ended up at Cedars-Sinai, which didn’t have something like this in the cardiology department I was referred to — the effort involved for a patient in figuring out where to go, or even knowing where to go and then getting in touch to book an appointment, is enormous.

That’s a sidebar, but you did mention something interesting and nuanced. Going back to the old days — Mayo Clinic and Cleveland Clinic wrote up, and you mentioned WebMD and Healthwise and others wrote up, ‘here’s the answer for this’ — generic for everybody. You can still go to the Mayo Clinic or Cleveland Clinic website, and somewhere in the bowels of those organizations a clinical team blessed and said, ‘yes, this is what we think about this.’ With what you’ve built, there’s no single generic answer — it’s coming through your approved process. How do you get an underlying LLM to agree to that, when presumably you don’t have complete control over what it says at all times and how it responds to everything? How do you manage that sign-off process with these organizations?

Ran Shaul

We’re not just using an LLM to manage the conversation at the top layer — underneath, when we need a discrete decision, we use different techniques: a set of agents with classifiers trained for precision, which is very different from a generative model. The generative model is the one that manages the conversation and flow with you. But when that generative model recognizes someone is asking about lung cancer, it hands off to a different model — we call them ‘tools’ in the architecture — and says: create an investigation for this patient — what does a lung cancer screening even mean for them, do they have a smoking history, do they have primary care? That tool engages with you, brings the results back to another agent, which figures out the next step — and that’s actually a classifier working in the background. So this is the architecture of agents I’m talking about — it’s not just one model running the whole thing, even though what you’re seeing on the surface looks like a single LLM.

Matthew Holt

And how do you come together with a health system to approve what it’s going to say and how that’s going to work?

Ran Shaul

Everything has to be studied with the health system. The good thing about this category is you can’t fake it — it actually has to work. They look at studies — we’ve published two peer-reviewed studies, not just something you’d put on the open web, but ones that go through real scrutiny. We published one recently in the Annals of Internal Medicine last April, which was very important for us, because when I talk to health systems now, they already reference that study. That study built on an idea we started developing using actual clinical encounters, which is very different from studying an AI with vignettes, where you put together a set of people, have doctors play along, and publish results. Studying it in a real clinical setting is a very different thing. That, again, comes back to K being both an AI company and an operator of actual patient care — our reinforcement learning is able to learn from real behavior. Imagine a patient goes for a lung cancer screening, meets the PCP, and the PCP says, ‘I don’t think you needed to see me, you need someone else.’ That data goes back into reinforcement learning, which lets us, in a sense, correct the model and iterate going forward. That becomes part of the health system’s validation process.

Matthew Holt

That makes a lot of sense, and it’s great you have that level of rigor. How do you interact with the data going back into Epic or whatever the EMR is — how are you getting that data back into K Health to build out and round out the model? Are you just reading the notes? How close is this getting to some of the other tools we mentioned before we started recording, like the ambient scribe world, or other tools looking at data for clinical decision support? How much of that do you have to build in order to make your digital front door work?

Ran Shaul

We have to integrate well with the EMR — those are standard APIs, and EMRs have gotten better over the years. You can send all of that information into an encounter fairly simply, and the physician picks it up from there, which is efficient. I also want to mention we’ve developed a set of agents independent from the main AI I showed you — we call them, for lack of a better name, ‘judges.’ Their whole purpose is to look at the main agents and make a judgment call on the AI agent’s performance. We provide that data in real time. My prediction is that this is going to be the path forward for medical devices, because I don’t think the concept of a ‘medical device’ survives for AI — it’s not a device, it’s an ever-changing thing. I think the ability to do what we call post-deployment monitoring is going to be the right way to interact with and measure ongoing performance and safety.

Matthew Holt

I think that’s an area people are really figuring out, and I think that’s a great explanation. Obviously regulation of this is connected to that, but also patient trust in what it’s going to say. Ran, there’s one thing I’ve been wrestling with. Go back to 2000 — I was in a personal health record company. You’re too young to remember, but back in the day there were sites like Drkoop.com, one of the first internet star sites, which went out of business, that was going to be a personal health record site bringing all your records together and answering all your questions. We’re still struggling with that, right? Even if you look at MyChart today, it’s kind of a list of transactions — it doesn’t really put things together in a useful format for you. What’s your sense of how LLMs and Patient GPT are going to rearrange all this knowledge into a helpful, ongoing record for somebody going through a treatment program? Are you working on that?

Ran Shaul

We call that ‘chronic management in between visits’ today. The idea that, okay, you saw your provider and now you have a ten-page document you’re supposed to follow up on, with three steps you need to take. You need to remind yourself on a calendar when to do it, half the stuff you didn’t understand because the conversation was overloaded with information — especially with a new diagnosis — and there’s a care team that’s supposed to call and remind you of all of it. We believe that whole area of chronic management is up for a real revolution, and that AI will become part of the care team — the place you can go and ask everything about your diagnosis. Take patient education: people with diabetes often don’t know what it is, don’t know how to measure it, don’t know how to cope with it. We saw the same thing happen with GLP-1s — everyone eventually became educated, but it takes time. We think AI will be your companion — it will remind you, nudge you, connect to your devices. A lot of people have devices now, but those devices sit outside the system and don’t necessarily connect back to your medical record. AI will provide that. But the most important part is connecting it to escalation of care — meaning you can manage your condition, but the AI will be smart enough to say, ‘Hey, wait a second — something is spiking in your blood pressure, this looks uncontrolled, let’s look at this more closely.’ You’ll be able to act faster than today, when you have to wait for your next six-month cardiology appointment to manage your hypertension. That’s how we think about revolutionizing chronic, in-between-visit management.

Matthew Holt

What do you think the UX for that looks like? I want to ask you two things about UX. Right now, ChatGPT and Anthropic’s Claude are a wall of text — there’s a lot of data in there, and they could represent it in different ways, including charts and graphs, but they don’t come back and show you a dashboard. We’ve seen people build dashboards in healthcare, for both patients and doctors and administrators, for years, and you’d think they’d be useful, but they don’t really appear in these models. Is that a place you guys are going, or have already built? When I log in, how am I going to figure out what’s going on rather than go back and read the text?

Ran Shaul

I think graphic illustration — a simple version of it — is going to be very important. I also think voice is very important, and you’re going to see much more animated elements that explain things better as educational material. All of that is going to evolve to explain complicated areas. You’d be surprised, but reading your A1C chart over the last five years, understanding the trend, understanding your baseline compared to that trend and compared to the population baseline, is not a simple task for most people. A1C could be one number, but for some people a higher number isn’t necessarily bad — it depends on who they are, what’s specifically going on with them. We oversee all of that, but we need to simplify it and explain what those things actually mean.

Matthew Holt

The voice thing is interesting — that was my second point. There are a bunch of companies out there that say they’re ‘voice-first AI’ — obviously you have Hippocratic, Ellipsis, and a bunch of others. You mentioned earlier that a lot of hospitals and health systems have call centers trying to reach out to people or respond to them, and that’s a problematic area. Those companies will say voice is different — you can’t treat it the same as chat. Obviously, the big LLMs let you turn on the speaker and have them talk to you as well as type back and forth. Then again, in real life, a lot of people now prefer texting to talking on the phone. What’s your sense — do you think voice AI is a fundamentally different thing that requires a different feature, or is it simply a feature?

Ran Shaul

Simply a feature. The unique piece I found is the ability to move between modalities — I can start a conversation with you in voice. For example, in a call center, a call comes in and someone says, ‘I don’t know what to do, my baby’s been crying for six hours, what should I do?’ The conversation starts fluently in voice, figures things out, and then sends a text saying ‘continue here,’ where you can open it up and start seeing educational material that could help you avoid an ER visit, or whatever else you might otherwise have done. I see voice really as a feature, and I believe in multimodality rather than a standalone voice product. Some of these voice AI products are genuinely beneficial, but I hear a lot of feedback that it feels like just another robocall — unless it’s really engaging, we need to be careful about simply replacing the call.

Matthew Holt

I think what you said is dead right — navigating between modalities and making sure it’s personalized, and using the right tool for the job. At some point you talk to it — I occasionally talk to it when I’m bored, but generally, for someone like me, it’s quicker to read information than to have it talked to me. I think the limits of Alexa drove me a bit mad about voice AI, and there are also a lot of complications around understanding. That said, there are still a lot of health plans in particular that don’t have any voice AI function, or even a chat function, when you want to communicate with them — not pointing at you particularly, Blue Shield of California, but you know who you are. So there’s a lot to be gained there, but I’m with you generally. I’ve talked a lot with the folks at Ellipsis and Hippocratic, and I’m a little puzzled as to whether they’ll remain an independent product, but we’ll see. Are you currently being used the way you’re describing for call centers? If a health system deploys K Health, do they also get the voice piece into the call center as part of that?

Ran Shaul

I’d say it’s a starting point — it’s not as well established as our other technology, but it makes a lot of sense, because we need to stop thinking about points of entry differently. It doesn’t matter if you come through a website, a portal, a call center, or by calling your care team — everything needs to lead to that same intelligent layer that understands who you are and what you’re seeking, and puts you in the right place. Then, if you move to care, it carries all the information with you, so your provider knows exactly what you’re coming in with, instead of starting over and having you describe everything again that you just described five minutes ago. That’s the kind of thing we wanted to create, and I think it builds tremendous trust with people. When you tell a patient, ‘you’re going to talk to AI,’ a lot of people say no. But when you tell a patient, ‘you’re not talking to AI, you’re preparing for your visit with your doctor,’ they’ll talk to the AI more than you’d expect — and it surfaces things the physician later says, ‘why didn’t you ask me about this or that?’ We’ve seen that in Patient GPT’s usage. That’s the sentiment I want people to understand: being part of a health system is very different from having a standalone relationship with an AI outside of it.

Matthew Holt

I think that’s dead right, and I think the connection of technology to services has been the biggest problem — I’ve been doing this since Health 2.0 in 2007, and that’s always been the biggest problem: the tech, the digital health stuff, gets grafted onto health services, and they still don’t talk to each other. I can promise you, in many cases, they’re still not talking, and that’s an area technology has to fix. So, let’s wrap up with two lines of questioning — one very pragmatic about K Health, and then I want to go to the future. Pragmatically — you mentioned you started nine years ago, is that right?

Ran Shaul

Yeah.

Matthew Holt

Give me some numbers. How much have you raised at this stage?

Ran Shaul

Quite a bit over the years — I think more than $400 million.

Matthew Holt

Decent amount. And some of that went in just last week, right? Didn’t you have another round?

Ran Shaul

Yeah, we had a round last week. We’re really proud to now have health systems as part of our cap table. This year, honestly, has probably been our best year so far — we feel like we’ve moved the needle on care delivery. We’ve talked a lot about AI, but eventually enterprise AI — enterprise vertical AI in healthcare — has to come back to the bottom line. Health systems need to become more efficient; there’s simply no choice if we want to serve populations better. We have to improve efficiency in our healthcare system, and that’s not by asking healthcare providers to just work harder — we have to find a way to deliver care more efficiently. That’s really why people are now looking at K Health as an alternative way to serve large populations. And, to your point, no one looks at us as just an AI tool anymore — they look at us as an AI care delivery platform that can change how care is delivered. That’s the differentiator I’m seeing in the market.

Matthew Holt

Just list off — I know we mentioned Cedars and Novant and a couple of others — which systems are you announced with?

Ran Shaul

We currently have 10 health system partners. As you’d expect: Mayo Clinic, Ochsner Health, Hackensack Meridian, Hartford HealthCare — which has been our design partner on everything Patient GPT — Mass General Brigham, which we plan to do a lot together with to develop the AI model, Northwell Health in New York, and Novant Health, which we just mentioned. We’ve also very recently launched with Atlantic Health, which I think has probably the most advanced consumer lens right now on how the transformation of healthcare is unfolding. If I’ve forgotten anyone, I apologize, but that gives you a flavor of the big systems we work with.

Matthew Holt

And tell me about the relationship with Elevance — that’s where you started, right? Is that still going, are they still working with you?

Ran Shaul

No — we had a really good experience, but to your point, we realized building a standalone care delivery platform wasn’t necessarily the way to go. When we were a provider in the network for Elevance, we felt we needed to align ourselves with health systems, and they came to feel that too. So it was a good relationship — everyone came out of it happy — a lot of learning, but we’re not working with them currently. Now the target is squarely big health systems.

Matthew Holt

And I get, from what you’ve shown us, that there are obviously two things going on — improving internal efficiency, and also getting patients into the health system to run through the till, so to speak — which gets me to the next part. Almost all the companies you’ve mentioned as clients are also Epic customers, and Epic has started building its own — I think it’s called Emmie, their chatbot that’s going to read the health record and service this. So there’s obviously going to be some competition from Epic — everybody in healthcare, whether in ambient AI scribing or clinical decision support or wherever, thinks Epic is coming for them, and maybe they are and maybe they aren’t. How are you thinking about that relationship, and what’s the conversation about how you deal with the Microsoft-of-the-1990s that is Epic now, working with all the same clients you’re working with?

Ran Shaul

Epic is a really important partner for us — we work with them in many cases through our health system relationships. I feel like the idea of agent-to-agent interaction is going to materialize very soon, and I think we’re going to find ourselves more friends than people expect. I honestly believe there’s an expertise around agents, and those agents need to speak to other agents. The orchestration we’ve built — the ability to manage you outside the portal relationship, not just during a visit — is an area with a lot of white space for us, and that’s exactly where health systems want us to be. You saw the Health Check, the proactiveness, the in-between-visit management — and then, when it’s time to go to care, we’re going to activate some other AI agent, which could be Emmie, to your point. But I also think health systems are going to build their own AI, and those AIs are going to get sophisticated — much more personalized than one standalone system, figuring out things like when your repeat colonoscopy is due. Are we not going to talk to each other and say, ‘give me the read on what you think about this patient’s preventive care’? I think that’s coming — I think it’ll take a bit more time for the MCPs and all the technology to be plugged in, but I think we’re heading toward a future where — and this is my prediction, Matt — software is going to blend. What we used to know as software that starts and ends is going to start blending; the lines are going to blur. An AI agent working as a CRM system inside Salesforce is going to talk to an AI agent that works in billing inside Epic, which is going to talk to the AI engine that manages the patient relationship in Patient GPT and K Health. All of them are going to orchestrate somehow to facilitate the experience for the patient.

Matthew Holt

Two things to wrap on, in no particular order. One — there’s been a lot of conversation lately; in fact last week the Khosla father and son, and Zeke Emanuel, wrote a piece about whether AI takes over from doctors. Right now it’s clear you’re working on the process of giving the patient all the information, gathering information from the patient, building a continual record and conversation, and plugging that into human visits and human doctors. A lot of people are talking about how much of that eventually gets done by AI doctors — where the human stops, where the AI stops, how they work together. I’ve had conversations with a lot of medical directors and others about this — what’s your sense of how much gets done before you get to a human, in the future?

Ran Shaul

Interestingly, one of the things that article referenced was the study I mentioned earlier, in the Annals of Internal Medicine — almost a year old now. That study showed that, for a narrow set of acute conditions, our AI performed the same as an MD 70% of the time, and in the remaining cases actually made a better decision than the MD. So this idea isn’t new to me, but I strongly believe there’s more to delivering care than just making the mathematical or logical decision. In many cases, diagnosis is genuinely ambiguous — that comes down to the algorithm, and there are high-confidence areas we’ll be able to automate eventually. I believe we’ll get to a point where a clinical decision can be made and a diagnosis delivered completely without a human involved — I think we’re heading there. But I think the role of the human will actually be different — more oversight, and handling what I call the exceptions, which is still a fairly large category, because when a case is ambiguous, its confidence score goes down and it gets handed to a human. So I’m a strong believer that AI will replace what doctors do, but not the doctor’s role — that’s how I think about it. And yes, there will be conditions we head toward fully automating.

Matthew Holt

It’s still funny — the joke is that Geoffrey Hinton said back in 2016 we’d get rid of radiologists, and now radiologists still can’t be trained fast enough, and their pay keeps going up.

Ran Shaul

This is exactly my point, Matt. If you think about it — and this gets to the biggest thing I want to say — I believe, personally, that as patients we should be getting maybe 50 diagnoses a year, not five. Five is high if you’re only seeing the doctor five times a year — that’s when you get a diagnosis today. I think we can get high-quality diagnoses 50 times a year — for every question, every stomachache, every little wonder we have — all of that could become a high-quality clinical decision if we let ourselves rethink how we architect that. That’s really what Patient GPT is trying to do — give you all of that information. And it doesn’t necessarily mean we’ll need fewer doctors — it might mean we actually need more doctors to keep up, because the good thing about healthcare is: open up supply, and there’s more demand.

Matthew Holt

Well, I think that’s true, and it may be good or bad — but the ability you get from AI in general is to take in far more data points, as you mentioned. You wake up with a stomach bug one day and you might ignore it, or maybe you ask ChatGPT — you probably don’t call your doctor about it — but there might be something in there worth the system knowing. And when you talk about people getting hundreds of biomarkers instead of 15 or 20, I think there’s a long way to go as people figure out how to really manage chronic illness and catch things earlier. I’m with you on that. All right, last question, and this is about the bet you guys have made — you’ve bet on big, current health systems. If you look at the American healthcare system, there are a handful of big incumbents, and a number of them are your clients. Mayo Clinic and Cedars-Sinai probably aren’t going anywhere anytime soon — I hope Cedars isn’t going anywhere, since I’m headed there for a procedure this week — excellent organization. But you do have a lot of people sniffing around. The more this becomes an AI- and data-focused activity, the more you’ve got the big AI model companies — Gemini, OpenAI, Anthropic, God knows what the Chinese are cooking up — getting involved, pulling together data, as I asked earlier, from TEFCA and the broader health information network. Putting together people’s data from multiple sources doesn’t sound too hard for them, and then plugging in some of the services you said aren’t widely available today. A lot of people are prepared to offer that — you’re seeing a lot of growth in people offering online care. For the moment, most of it is GLP-1s sold from somewhat dubious pharmacies, but there’s also a bunch of people building real online clinics — some specializing in menopause, or GI issues, or mental health. And then, of course, you’ve got the health plans — happy to take claims from big health systems, but also building their own telehealth services. I’m a Cigna member now, and they’ve got MDLive, which is starting to do urgent care. You’ve got to imagine this type of tool, and the services you’re describing, could go in a lot of different directions, and a lot of other players could come in. So my question is: is your bet on big health systems your only bet, or do you think there are other potential venues where care might end up?

Ran Shaul

No — you just described my competitive landscape.

[laughter]

This is very interesting — my bet is that the competition won’t be about who has the best model, but about who has the best workflow. In enterprise AI, I think the winners and losers will be determined by how much you actually manage to impact the workflow and integrate all the pieces together. My bet is really with the health systems — I feel like, as a standalone online clinic, you can change a certain amount, but not the entire continuum of care. With the health systems we have in this country — 400-plus organizations that control three trillion dollars of medical spend — if you work with enough of them, I think the market is big enough that you can change tens of millions of lives and health journeys. That’s where my head is on the competitive landscape. And it’s a big undertaking to go into a health system and get through the process of putting your AI inside care delivery — that’s very different from licensing a product for people to play around with. You’re actually inside the medical record — you’ve been given permission to operate inside it. That’s a big moat, in my mind.

Matthew Holt

Yeah — if you look at America today, the chances of radical change to how we deliver healthcare, in terms of the organizations delivering it, is limited. I’m actually running a campaign trying to change that, but that’s a separate issue. It’s a pretty good bet that the thing that could most improve care is improving the operations and patient focus of the big health systems that already deliver most of the care. There’s some chance that in 20 years we wake up and it’s all being delivered by Amazon and Apple, or a bunch of companies we haven’t heard of yet — but for now, I understand why you’re going to the current incumbents, and I wish you luck continuing to improve the experience their patients have, because, like I said, I’ve been dealing with a lot of this lately, and it’s not all great. So please go sell more — and I particularly recommend selling to the cardiology department at Stanford. They may be the hardest of the lot to get through.

Ran Shaul

Maybe not so much — but I want to tell you, Matt, a few years ago you asked me whether we should go to health systems, and I was actually very negative about it. I thought there was no chance we’d convince academic centers that we could be helpful — simply no chance. But I have to tell you, in the last few years I’ve been very proud to see this industry move — aside from vibe-coding engineers, show me another industry that has moved this fast in deploying AI into a critical clinical workflow, not just giving people a bit of license to play around with an enterprise product on the side. Show me a finance department, a logistics department, an advertising department that has revamped its process flow as much as healthcare has. That’s genuinely encouraging to see as an industry.

Matthew Holt

Yeah, I think that’s right — it’s healthcare, or Ukrainian drones.

[laughter]

One of the other — I wasn’t going to raise that, but yes, that’s fantastic. All right, I’ve been speaking with Ran Shaul, Chief Product Officer of K Health. Ran, thanks for your time — it was really great to go through what you guys have done. Congratulations on the progress so far, and go get to Stanford Cardiology, and the cardiac clinic at Cedars, so I can talk to them instead.

[laughter]

Congrats on the work so far, and keep going.

Ran Shaul

Thank you very much, Matt. Very nice — enjoyed it. Thank you.