H1 has raised over $200m to build out a very comprehensive data set of physicians internationally. Those products were primarily aimed at pharma. Now they are moving into the world of managing physician data for plans and providers, primarily via the 2025 acquisitions of Ribbon Health and Veda Health. I spoke with CEO Ariel Katz, and he took me through a demo of their system. I’ve had a nerdy interest in physician data for quite a while (I actually sketched out this product on a whiteboard at Microsoft in 2009!!) and what H1 has built is very impressive–Matthew Holt
Above the Fold
Dr Kimmie Ng discusses young onset colorectal cancer
Dr Kimmie Ng discusses cancer with Dr. George Beauregard. Dr Ng heads the Young-Onset Colorectal Cancer Center, at the legendary Dana Farber Cancer Institute, and she treated George’s son who died age 32. Why are these cancers in younger people increasing so quickly? What can we do about it? What is connecting the environment, the immune system, mental health and cancer? What kind of early intervention can we advocate for? A fascinating conversation between two real leaders in this field.
Digital Health Hub Awards
They’re back and I’m an Executive Producer again (don’t ask what that means!). Entries are open now and close on July 31. Awards given out at HLTH on October 20. The team even made a spiffy video about it!–Matthew Holt
American Medicine’s Meagerness Paradox
By MARC-DAVID MUNK
In our palliative medicine clinic in the working suburbs of Boston, my colleagues and I tend to some of the sickest patients in the city. Through the window, I can see the afflicted pull up to our squat building in family sedans, wheelchair vans, and subsidized municipal ride cars. Few drive themselves: most bear terrible illnesses that make them too frail or sedated. I watch as patients who are barely able to dress themselves, somehow arrive in their Sunday best for clinic.
Our job, as their doctors, is to manage their pain and provide moral support and practical help with things such as rent and transportation, sometimes spiritual support too. It’s important work, among the highest callings in medicine. Yet, as noble as this work might be, our clinic doesn’t begin to support itself financially. If there was ever a reason to spend graciously on patients and their needs, these visits, with their sick and vulnerable patients, would be exemplars. In fact, we don’t receive enough payment from insurers to cover the costs of the complicated work that’s needed. Practically, this translates to few staff to help with appointments, not enough follow-up calls, nobody to help with insurance headaches or pharmacy shortages, nobody answering the phone. Our facilities are tired. The simplest niceties—coffee in the waiting room, magazines, a comfortable chair—are long gone.
There is a feeling of “meagerness” in the air. It’s the feeling of being rationed. It’s an absence of all but the truly essential; no plenitude, a lack of graciousness. I see meagerness when my friend, an emergency physician at a major trauma center, shares pictures of his decomposing ER: desk chairs held together with medical tape, rooms without functioning equipment. Medical supplies that are so scarce that doctors keep stashes in their desks and coat pockets.
The administrators will say that these barren conditions are a consequence of financial scarcity. There isn’t enough money to pay for more than skeleton support and upkeep. Hospitals are running deficits and downsizing. Keeping the lights on is apparently a question of saving pennies at every opportunity. And, with every cut, meagerness grows. This all sounds, on its surface, understandable till you take a step back and realize it isn’t. We know that American healthcare consumes more money than any other country, per capita. Money is pouring, truly flooding, into our healthcare system. Family health insurance premiums rose 7% from 2023, after another 7% increase the year before. The average family policy now costs around $25,000 per year.
Which leaves me wanting to reconcile how there can be so much money entering the system, with so little left for essential front-line care. I know that this isn’t a complicated answer.
Roy Schoenberg, AileenAI
Last week longtime AmWell CEO Roy Schoenberg announced, in the New England Journal of Medicine no less, that he was building a companion AI for the elderly called Aileen. We took a dive into the state of play for digital health, what happened at AmWell, and what the goal is for the AI companion. It’s early days but Roy has an interesting idea for how AI will work in the future to be the underlying platform to manage the elder consumer experience. Always a great conversation with Roy and this is no exception–Matthew Holt
How to Fix the Paradox of Primary Care
By MATTHEW HOLT
If health policy wonks believe anything it’s that primary care is a good thing. In theory we should all have strong relationships with our primary care doctors. They should navigate us around the health system and be arriving on our doorsteps like Marcus Welby MD when needed. Wonks like me believe that if you introduce such a relationship patients will receive preventative care, will get on the right meds and take them, will avoid the emergency room, and have fewer hospital admissions—as well as costing a whole lot less. That’s in large the theory behind HMOs and their latter-day descendants, value-based care and ACOs
Of course there are decent examples of primary care-based systems like the UK NHS or even Kaiser Permanente or the Alaskan Artic Slope Native Health Association. But for most Americans that is fantasy land. Instead, we have a system where primary care is the ugly stepchild. It’s being slowly throttled and picked apart. Even the wealth of Walmart couldn’t make it work.
There are at least 3 types of primary care that have emerged over recent decades. And none of them are really successful in making that “primary care as the lynchpin of population health” idea work.
The first is the primary care doctor purchased by and/or working for the big system. The point of these practices is to make sure that referrals for the expensive stuff go into the correct hospital system. For a long time those primary care doctors have been losing their employers money—Bob Kocher said $150-250k a year per doctor in the late 2000s. So why are they kept around by the bigger systems? Because the patients that they do admit to the hospital are insanely profitable. Consider this NC system which ended up suing the big hospital system Atrium because they only wanted the referrals. As you might expect the “cost saving” benefits of primary care are tough to find among those systems. (If you have time watch Eric Bricker’s video on Atrium & Troyon/Mecklenberg)
The second is urgent care. Urgent care has replaced primary care in much of America. The number of urgent care centers doubled in the last decade or so. While it has taken some pressure off emergency rooms, Urgent care has replaced primary care because it’s convenient and you can easily get appointments. But it’s not doing population health and care management. And often the urgent care centers are owned either by hospital systems that are using them to generate referrals, or private equity pirates that are trying to boost costs not control them.
Thirdly telehealth, especially attached to pharmacies, has enabled lots of people to get access to medications in a cheaper and more convenient fashion. Of course, this isn’t really complete primary care but HIMS & HERS and their many, many competitors are enabling access to common antibiotics for UTIs, contraceptive pills, and also mental health medications, as well as those boner and baldness pills.
That’s not to say that there haven’t been attempts to build new types of primary care
Continue reading…Matthew on the Inside Medtech Innovation podcast
I was a guest on Shannon Lantzy‘s podcast Inside Medtech Innovation. I went on far too long about my background but we had a very fun chat, including the real origin story of why I am in health technology, and a bit about my fascination with Japan. Plus some more health care stuff. I enjoyed it. Hopefully you will too–Matthew Holt
Can EHRs Expand to Become Health Systems’ “Platform of Platforms” (UDHPs)?
By VINCE KURAITIS & NEIL JENNINGS
In a previous post in this series, we discussed healthcare’s migration toward Unified Digital Health Platforms (UDHPs) — a “platform of platforms.” Think of a UDHP as healthcare’s version of a Swiss Army knife: flexible, multi-functional, and (ideally) much better integrated than the drawer full of barely-used apps most health systems currently rely on. We included a list of 20+ companies jockeying for UDHP dominance, including two familiar EHR (electronic health record) giants — Epic and Oracle. This raises the obvious question for today’s post:
Can EHRs level up into becoming UDHPs — becoming healthcare’s platform of platforms? Or are they trying to wear a superhero cape while tripping over their own cables?
We see good arguments pro and con, and like most things in healthcare “it’s complicated.” Some say EHRs are uniquely positioned to make the leap. Others believe the idea is like trying to teach your fax machine to run population health analytics.
Thus, we’ll lay out the arguments for differing points of view, and you can decide for yourself.
by Vince Kuraitis and Neil P. Jennings of Untangle Health
Here’s an outline of today’s blog post:
- A Brief Recap: What are UDHPs?
- Thesis: EHRs Can Expand to Become UDHPs
- EHRs Currently Own the Customer Relationship
- Many Customers Have an “EHR-First” Preference for New Applications
- Epic and Oracle Health are Making Strong Movements Toward Becoming UDHPs
- Antithesis: EHRs Can NOT Become Effective EHRs
- EHRs Carry a Lot of Baggage
- Customers are Skeptical
- EHR Analytics Are NOT Optimized To Achieve Critical Health System Objectives
- EHR Switching Costs are Diminishing
- Cloud Native Platforms Accelerate Innovation and Performance
- It’s Not in EHR DNA to Become A Broad-Based Platform
- Synthesis and Conclusion
This is a long post…over 4,000 words…so we’ve clearly got a lot to say on the matter. Hope you brought snacks!
A Brief Recap: What are UDHPs? (Unified Digital Health Platforms)
In our previous extensive post on UDHPs, we described them as a new category of enterprise software. A December 2022 Gartner Market Guide report characterized the long-term potential:
The [U]DHP shift will emerge as the most cost-effective and technically efficient way to scale new digital capabilities within and across health ecosystems and will, over time, replace the dominant era of the monolithic electronic health record (EHR).
The DHP Reference Architecture is illustrated in a blog post by Better. Note that UDHPs are visually depicted as “sitting on top” of EHRs and other siloed sources of health data:
We noted that almost any type of large healthcare organization — health systems, health plans, pharma companies, medical device companies, etc. — had a need for UDHPs. However, today’s focus is more narrow — we limit the discussion to UDHPs in hospitals and health systems, primarily in the U.S. We use the term “health system” to encompass hospitals and regional health delivery systems.
In this post, we focus on the two largest EHR vendors in the U.S. — Epic and Oracle Health; they have a combined market share of 65% of hospitals and 77% of hospital beds.
In the remaining sections, we will lay out arguments on both sides of the issue of whether EHRs can (or cannot) expand to become UDHPs. The graphic below is our crack at a visual summary. The balloons represent the thesis – that EHRs can expand to become UDHPs; the anchors represent the antithesis – that EHRs can not expand to become UDHPs.
Thesis: EHRs Can Expand To Becoming UDHPs
Let’s look at the case for EHRs expanding to become effective UDHPs.
How Did the AI “Claude” Get Its Name?
By MIKE MAGEE
Let me be the first to introduce you to Claude Elwood Shannon. If you have never heard of him but consider yourself informed and engaged, including at the interface of AI and Medicine, don’t be embarrassed. I taught a semester of “AI and Medicine” in 2024 and only recently was introduced to “Claude.”
Let’s begin with the fact that the product, Claude, is not the same as the person, Claude. The person died a quarter century ago and except for those deep in the field of AI has largely been forgotten – until now.
Among those in the know, Claude Elwood Shannon is often referred to as the “father of information theory.” He graduated from the University of Michigan in 1936 where he majored in electrical engineering and mathematics. At 21, as a Master’s student at MIT, he wrote a Master’s Thesis titled “A Symbolic Analysis Relay and Switching Circuits” which those in the know claim was “the birth certificate of the digital revolution,” earning him the Alfred Noble Prize in 1939 (No, not that Nobel Prize).
None of this was particularly obvious in those early years. A University of Michigan biopic claims, “If you were looking for world changers in the U-M class of 1936, you probably would not have singled out Claude Shannon. The shy, stick-thin young man from Gaylord, Michigan, had a studious air and, at times, a playful smirk—but none of the obvious aspects of greatness. In the Michiganensian yearbook, Shannon is one more face in the crowd, his tie tightly knotted and his hair neatly parted for his senior photo.”
But that was one of the historic misreads of all time, according to his alma mater. “That unassuming senior would go on to take his place among the most influential Michigan alumni of all time—and among the towering scientific geniuses of the 20th century…It was Shannon who created the “bit,” the first objective measurement of the information content of any message—but that statement minimizes his contributions. It would be more accurate to say that Claude Shannon invented the modern concept of information. Scientific American called his groundbreaking 1948 paper, “A Mathematical Theory of Communication,” the “Magna Carta of the Information Age.”
I was introduced to “Claude” just 5 days ago by Washington Post Technology Columnist, Geoffrey Fowler – Claude the product, not the person. His article, titled “5 AI bots took our tough reading test. One was smartest — and it wasn’t ChatGPT,” caught my eye. As he explained, “We challenged AI helpers to decode legal contracts, simplify medical research, speed-read a novel and make sense of Trump speeches.”
Judging the results of the medical research test was Scripps Research Translational Institute luminary, Eric Topol. The 5 AI products were asked 115 questions on the content of two scientific research papers : Three-year outcomes of post-acute sequelae of COVID-19 and Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease.
Not to bury the lead, Claude – the product – won decisively, not only in science but also overall against four name brand competitors I was familiar with – Google’s Gemini, Open AI’s ChatGPT, Microsoft Copilot, and MetaAI. Which left me a bit embarrassed. How had I never heard of Claude the product?
For the answer, let’s retrace a bit of AI history.
What AI and Grief-bots Can Teach Us About Supporting Grieving People
By MELISSA LUNARDINI
The Rise of Digital Grief Support
We’re witnessing a shift in how we process one of humanity’s most universal experiences: grief. Several companies have emerged in recent years to develop grief-related technology, where users can interact with AI versions of deceased loved ones or turn to general AI platforms for grief support.
This isn’t just curiosity, it’s a response to a genuine lack of human connection and support. The rise of grief-focused AI reveals something uncomfortable about our society: people are turning to machines because they’re not getting what they need from the humans around them.
Why People Are Choosing Digital Over Human Support
The grief tech industry is ramping up, with MIT Technology Review reporting that “at least half a dozen companies” in China are offering AI services for interacting with deceased loved ones. Companies like Character.AI, Nomi, Replika, StoryFile, and HereAfter AI offer users the ability to create and engage with the “likeness” of deceased persons, while many other users use AI as a way to quickly normalize and seek answers for their grief. This digital migration isn’t happening in a vacuum. It’s a direct response to the failures of our current support systems:
- Social Discomfort: Our grief-illiterate society struggles with how to respond to loss. Friends and family often disappear within weeks, leaving mourners isolated when they need support, especially months later.
- Professional Barriers: Traditional grief counseling is expensive, with long wait times. Many therapists lack proper grief training, with some reporting no grief-related education in their programs. This leaves people without accessible, qualified support when they need it most.
- Fear of Judgment: People often feel safer sharing intimate grief experiences with AI than with humans who might judge, offer unwanted advice, or grow uncomfortable with the intensity of their grief.
The ELIZA Effect
To understand why grief-focused AI is succeeding, we must look back to 1966, when the first AI-companion program called ELIZA was developed. Created by MIT’s Joseph Weizenbaum, ELIZA simulated conversation using simple pattern matching, specifically mimicking a Rogerian psychotherapist using person-centered therapy.
Rogerian therapy was perfect for this experiment because it relies heavily on mirroring what the person says. The AI companion’s role was simple: reflect back what the person said with questions like “How does that make you feel?” or “Tell me more about that.” Weizenbaum was surprised that people formed deep emotional connections with this simple program, confiding their most intimate thoughts and feelings. This phenomenon became known as the “ELIZA effect”.
ELIZA worked not because it was sophisticated but because it embodied the core principles of effective emotional support, something we as a society can learn from (or in some cases relearn).
What AI and Grief-bots Get Right
Modern grief-focused AI succeeds for the same reasons ELIZA did, but with enhanced capabilities. Here’s what AI is doing right:
- Non-Judgmental Presence: AI doesn’t recoil from grief’s intensity. It won’t tell you to “move on,” suggest you should be “over it by now,” or change the subject when your pain becomes uncomfortable. It simply witnesses and reflects.
- Unconditional Availability: Grief doesn’t follow business hours. It strikes at 3 AM on a Tuesday, during family gatherings, while you’re at work, or on a grocery run. AI works 24/7, providing instant support by quickly normalizing common grief experiences like “I just saw someone who looked like my mom in the grocery store, am I going mad?” AI’s response demonstrates effective validation: “You’re not going mad at all. This is actually a very common experience when grieving someone close to you. Your brain is wired to recognize familiar patterns, especially faces of people who were important to you… This is completely normal. Your mind is still processing your loss, and these moments of recognition show just how deeply your mom is still with you in your memories and awareness.” Simple, on-demand validation helps grievers instantly feel normal and understood.
- Pure Focus on the Griever: AI doesn’t hijack your story to share its own experiences. It doesn’t offer unsolicited advice about what you “should” do or grow weary of hearing the same story repeatedly. Its attention is entirely yours.
- Validation Without Agenda: Unlike humans, who may rush to make you feel better (often for their own comfort), AI validates emotions without trying to fix or change them. It normalizes grief without pathologizing it.
- Privacy and Safety: AI holds space for the “good, bad, and ugly” parts of grief confidentially. There’s no fear of social judgment, no worry about burdening someone, no concern about saying the “wrong” thing.
- No Strings Attached: AI doesn’t need emotional reciprocity. It won’t eventually need comforting, grow tired of your grief, or abandon you if your healing takes longer than expected.
AI Can Do It, But Humans Can Do It Better. Much Better.
According to a 2025 article in Harvard Business Review, the #1 use of AI so far in 2025 is therapy and companionship.
