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Category: Health Tech

HealthEx — The Demo with Claude & the CEO Speaks!

I spent some time figuring out and getting a little help in uploading my health records to Claude, using HealthEx. I did the demo with Ruheed Mohamed, the head of technical services, and then I interviewed CEO Priyanka Agarwal, MD. This shows how Healthex gets data and incorporates it into Claude, and where Priyanka thinks the business is going, and why she wants to change the way consumers get health care data.–Matthew Holt

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?

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Know Thyselves

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.

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Owen Tripp, Included Health–How to Fix AI

It’s been a while since I talked with Owen Tripp, CEO of Included Health. They’ve now introduced Dot their AI companion which had a big upgrade last week. We talked a little about that and I snuck in their video comparing the Dot Experience with a standard LLM. But the conversation really got into how do we make AI safe and trustworthy–which is definitely the hot topic these days. Owen is putting together a coalition of the willing to work on that exact topic. I’ll be watching closely–Matthew Holt

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.

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Whack-a-Mole AI – The Hugging Face Problem

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.

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Gozio – Patient Navigation & Directions!

I had a great conversation and demo with Katie Logan and Christine Smith from Gozio a while back. Finally got it up on THCB. Gozio provides two types of patient navigation for health systems. One as a digital front door helping patients navigate to doctors, services and tools like virtual care and appointments from the hospitals, and actual navigation from the parking lot to the clinic/bedside. Why should hospitals hire Gozio (and spent a few $100k+) when some of this stuff is buried in MyChart in a typical health system? Calls go down, visits go up and Google ratings go up. They are in 25-35 systems now and aiming for many more.–Matthew Holt

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.

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Start Counting Your Days

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.

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Ran Shaul, K Health

K Health started life as symptom checker and spent a lot of time working with Elevance/Anthem. But in recent years has become a sophisticated LLM tuned to patients and now is working exclusively with major health systems as a front door including Mayo, Cedars Sinai and now Atlantic Health providing PatientGPT and Virtual Primary Care. I had Ran Shaul, Chief Product Officer come on THCB Spotlight to show how K Health is being used in various ways across health systems. He showed me various demos and I also asked him about the relationship with Epic, and what the future of care delivery with LLMs is going to be. Ran thinks we might need more doctors not less!–Matthew Holt

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.

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The Pandemic Risk of “What I’ve Never Seen Before”

By MIKE MAGEE

The world of medical science largely closed ranks last month in defense of Tony Fauci. Dr. Fauci had been hauled before the Senate Homeland Security Committee to face hostile entrapment by long time critique Senator Rand Paul of Kentucky. Taking no chances, his lawyers had the former head of NIH’s Infectious Disease division plead the 5th to avoid entrapment, fines, and even imprisonment.

It has been five years since Dr. Fauci appeared on MSNow (formerly MSNBC) and encourage viewers to “keep an open mind” when it came to “gain-of-function” research and the origins of the Covid pandemic. Since then, a 2025 WHO report stated “As things stand, all hypotheses must remain on the table.” That includes the possibility that the viral tragedy resulted from the inadvertent release of a genetically engineered virus from the Wuhan, China, laboratory of Shi Zhengli, a virologist trained at the University of North Carolina.

The risky experiments, termed “gain-of-function” studies, were justified as super-secure, safe, predictive, and preventive. Shi returned to her labs in 2018 and 2019 with grant funding from the National Institute of Allergy and Infectious Disease and the Department of Defense via an intermediary, the New York based non-profit EcoHealth Alliance,whose funding was retracted in 2024.

Their coordinator-in-chief was one Peter Daszak. Daszak is known for adopting militarized terms in the battle against global infectious diseases. In 2020 he wrote in the New York Times, “Pandemics are like terrorist attacks: We know roughly where they originate and what’s responsible for them, but we don’t know exactly when the next one will happen. They need to be handled the same way — by identifying all possible sources and dismantling those before the next pandemic strikes.”

Daszak’s argument that risks involved in Shi Zhengli’s Wuhan bat virus research were justified as defensive and preventive was convincing enough to the NIH and the Department of Defense that his EcoHealth Alliance was funded from 2013 to 2020 (contracts, grants, subgrants) to the tune of well over $100 million – $39 million from Pentagon /DOD funds, $65 million from USAID/State Dept., and  $20 million from HHS/NIH/CDC.

Daszak’s position within the scientific community was controversial. In fact, in 2014, a group of concerned scientists called the Cambridge Working Group issued this statement: “Accident risks with newly created ‘potential pandemic pathogens’ raise grave new concerns. Laboratory creation of highly transmissible, novel strains of dangerous viruses, especially but not limited to influenza, poses substantially increased risks. An accidental infection in such a setting could trigger outbreaks that would be difficult or impossible to control.”

All of this, it seems, would be “old news” except for last week’s dramatic announcement that “For the first time, scientists have used artificial intelligence to create new kinds of viruses, raising hopes for medical advances while also raising the disturbing possibility that the technology could someday be used to invent dangerous pathogens.”

It has been 23 years since scientists first constructed a synthetic viral genome. But Evo, a creative science AI newcomer, produced by OpenAI has apparently broken new ground – on its own. Well not completely. Its’ masters primed the pump by feeding the AI engine with nine trillion nucleotides (the human genome has 3 billion) obtained from millions of diverse species.

The scientific engineers focused down on a well-known virus that is generally active primarily in attacks on the bacteria, E-coli. It’s called Phi X-174. It has been utilized for some time in genetic engineering exercises. But in this case, it (along with some 15,000 close chemical relatives), was feed into Evo with the instruction to create new novel viruses of its own. 

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Big Bucks, No Whammies: Patient Access Was Never the Finish Line

By STEPHEN FARBER

If you grew up in the 1980s, you probably remember Press Your Luck. Contestants stood in front of a flashing game board chanting, “Big bucks… no Whammies… STOP!” hoping the next square held cash instead of the mischievous cartoon character that erased everything they had won.

For years, assembling your own medical history felt remarkably similar.

You knew you had been treated at one hospital years ago, had imaging performed somewhere else, saw specialists who later retired, and changed insurance more than once along the way. One patient portal showed part of the story. Another required a password you hadn’t used in years. A medical records department offered to mail you a PDF after you completed a release form. Somewhere there was still a CD that no computer in your house could read. None of this meant your information had disappeared. It simply meant that putting it together depended almost as much on persistence as process.

That has always been one of healthcare’s great ironies. The industry became exceptionally good at documenting encounters. Every office visit, laboratory result, prescription, imaging study, discharge summary, and insurance claim was carefully preserved somewhere. What it never became particularly good at was helping individuals assemble those encounters into a coherent picture of their health over time.

For years, most of us accepted that as an unavoidable consequence of a fragmented healthcare system. In reality, it reflected a combination of technical limitations, business incentives, and regulatory uncertainty that made sharing information far more difficult than creating it. Patients often became the courier between organizations because there were few practical alternatives.

Quietly, that has begun to change.

While much of the industry’s attention has shifted toward artificial intelligence, another transformation has been taking place beneath the surface. The 21st Century Cures Act, Information Blocking regulations, standardized FHIR APIs, CMS interoperability requirements, and the continued evolution of TEFCA have collectively changed the trajectory of patient access. None of those developments solved the problem on their own, but together they have created an environment in which individuals can retrieve far more of their own health information electronically than was practical only a few years ago.

Although we’re still in the early stages, the technology has matured to the point where individuals can increasingly assemble and steward their own longitudinal health record. That changes the conversation. For much of the past decade, patient access was largely a policy discussion centered on whether people should have meaningful electronic access to their own information. Increasingly, the more interesting question is what becomes possible once they do.

As the market has evolved, complementary approaches have emerged. Some companies focus on helping individuals retrieve records directly from the organizations that hold them. Fasten Health is an interesting example because it begins with a simple premise: individuals should be able to assemble a record they control. Other organizations focus on discovering where records exist through exchange networks, while infrastructure companies simplify connectivity so developers can build applications without creating thousands of individual integrations. These approaches solve different problems, but they increasingly reinforce one another instead of competing.

That convergence has quietly moved the industry across an important threshold. For years, success was measured by our ability to collect fragmented data. Standards had to mature, regulations had to evolve, organizations had to expose information electronically, and software developers had to build practical ways of retrieving it. Much of that work occurred outside public view, but together it has made something increasingly realistic that once felt aspirational.

Bringing information together is a significant achievement because it gives people, often for the first time, a more complete picture of their interactions with the healthcare system over many years. A longitudinal health record tells us where someone received care, what diagnoses were made, which medications were prescribed, and what procedures were performed. Those are essential building blocks, but they rarely explain why decisions were made, what alternatives were considered, who participated in those conversations, or what mattered most to the individual at that point in life. Records preserve information extraordinarily well. Context has always been more difficult to preserve.

Healthcare has good reasons for operating around encounters because that is how care is delivered, documented, and reimbursed. People, however, experience their lives as a continuous story in which one decision influences the next, often over decades.

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Pre-Surgical Complications (Part 6) — The Decision

By MATTHEW HOLT

Strap in for the tale of why your hero is spending most of his life down YouTube rabbit holes of cardiology videos while blundering his way around many many medical centers and exposing many problems with American health care even before he gets close to the operating table. Yes it’s Matthew Holt’s pre-surgical complications – the complications that have arisen before he even gets his failing aortic valve fixed. And yes this is the last for now of a multi-parter! Part 1, Part 2, Part 3, Part 4 Part 5

By now I have met with expert physicians and their teams at 5 major medical centers (UCSF, Stanford, Cleveland Clinic, Cedars Sinai & West Virginia University). I have spent hours talking to the AI gods at Claude, ChatGPT and Inciteful Med, annoyed the hell out of all the cardiologists and other doctors I know, and basically got enough contradictory advice that it’s all up to me.

The main decision comes down to whether I should get a TAVR or the RAVR. And because I approached Cedars about the BELIEVERS clinical trial rather than going direct to Dr Makkar, they put me into that process. The trial randomizes patients into either TAVR or RAVR, likely performed by Dr. Dominic Emerson who is the Director of Robotic Cardiac Surgery, Smidt Heart Institute, and one of the surgeons mentioned by Dr Badhwar. (I had a quick chat with him after he called me while I was on a ski boat in Lake Tahoe, although due to the shoulder pain I had not gone wakeboarding!)

The study documentation stressed – and this was backed up unprompted by one of the study coordinators – that I could back out at any time. So if I were randomized into the RAVR cohort, I still had the choice to pull out and ask Dr Makkar to do a TAVR on me anyway, or of course go to West Virginia and get surgery there.

And of course there is still the question of how risky a TAVR on my valve will be. I did take Dr Yeung’s advice seriously, and a study that Dr Makkar oversaw back in 2020 did show that (for patients considerably older than me) the risk of all cause mortality at 2 years in bicuspid valve TAVR patients was higher with bad calcification (like me). On the other hand, Dr Makkar told me that his unpublished data between TAVR and SAVR at 5 years showed no difference. He also directly told me that I was a good candidate for a TAVR and he has done more bicuspid TAVRs than anyone else. He’s also working on techniques that break up the calcification on the “join” before the TAVR, although it’s unclear if he’ll do that in the BELIEVERS trial and to me

I originally wanted a TAVR because it was a much easier recovery than surgery. I also have two more major surgeries to go through within the next few months, and it would be a big stress on me and my family to make that three. Plus, I both would be happy to contribute to a medical study and am pretty confident that in a decade or so, cardiology will have advanced a lot more and I probably wouldn’t need open heart surgery even if the TAVR valve fails sooner than the 10-15 years I am hoping to get out of it.

So I crossed my fingers and hoped that the computer would randomize me into the TAVR group at Cedars and obviate the need for any uncomfortable decisions about pulling out of the trial. And it did. I’ll be getting it done in early September.

This isn’t exactly Lebron James making The Decision, although that show lasted only 75 minutes and also went on way too long!

Some concluding thoughts

I would obviously rather have not had to write this little memoir. But given I went through it, there are several conclusions smacking me in the face.

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