Preeti Bhargava is CTO of Arintra. She is the living embodiment of my crack that the smartest people in the world spent the 2010s convincing people to click on ads and now spend their time figuring out how to bill payers more for providers doing the same work. Arintra is in the RCM business. It uses AI to read the medical chart and automatically generate claims using fewer human coders, and generating up to a 5% revenue uplift for one customer, Mercy Health. Of course those paying those claims may have noticed, so we had a chat about the emerging AI RCM arms race–Matthew Holt
Ratnakar Lavu, Elevance
Ratnakar Lavu is the Chief Digital Information Officer of Elevance, the holding company of Blue Cross and Blue Shield plans in some 14 states (usually called Anthem Blue Cross). We had a great chat about what the priorities are for Elevance, and Ratnakar’s goal is to use tech to make the member experience simple. They are leaning heavily on AI and chatbots to help members inform themselves, and to help providers speed up approvals for prior auth et al. We also discussed how they work with vendors and how they help them scale.–Matthew Holt
Liberal Arts Education As a Counterbalance To Trumpian AI
By MIKE MAGEE
What’s wrong in the social science realm of health? Consider for example the mental health crises affecting teens across the nation, or the sharp decline in relationships and child bearing in young adult men and women, or the attack on vaccine policy by the wayward Kennedy, or the attempted dismantling of ACA health insurance coverage for millions, or the outright cruelty of ICE agents toward citizens and legal aliens, or the callous attitude toward Middle East casualties of soldiers and civilians by the President and the “Secretary of War”… and I could go on.
How should our nation begin to address these grievances? With our grandchildren either in or fast approaching higher education, I’ve been making a related case (as I see it) for the value and importance of a liberal arts education. In a strange way, Trump, in his attacks on the law and democracy, has instigated a resurgence of interest in history, philosophy, religion, political science, literature and the arts – even in this age of fantastical AI exuberance.
My own alma mater has been steadfast in its vision. As they state on their own website, “The liberal arts education at Le Moyne is rooted in the Jesuit tradition, which emphasizes the education of the whole person and the search for meaning and value as integral parts of an intellectual life. This commitment to a liberal arts education allows students to develop a broad range of skills and knowledge, fostering ethical leadership, service, and a commitment to social justice. The college’s Core Curriculum is central to its mission, ensuring that all students receive a thorough education in the liberal arts, which includes knowledge across multiple disciplines and the confidence to engage in intellectual inquiry as members of a global community.”
In simpler terms, LeMoyne’s front page headlines “We strive for greatness always through the eyes of goodness.” I thought of this last week as I watched James Talarico’s speech accepting his Democratic Primary nomination for Senate in Texas. In part explaining his convincing victory numbers as a result of his ability to attract a large turnout of Democrats, Independents, and Republicans, he issued what will certainly be his rallying cry: “The people of this state have given this country a little bit of hope, and a little bit of hope is a dangerous thing.”
Who is in danger? Talarico has tagged not only billionaires, but especially Christian Nationalists who he says “divide us by party, by race, by gender, by religion so that we don’t notice that they’re defunding our schools, gutting our health care and cutting taxes for themselves and their rich friends. It is the oldest strategy in the world: Divide and conquer. But we will not be conquered.”
This week CUNY Political Scientist, Peter Beinart, laid out a remarkable opinion piece in the New York Times, leaning heavily on liberal arts to make a convincing case against empire building and king Trump. In opposing national sovereignty and international law conventions, he spotlights the President’s source of guidance – “My own morality. My own mind. It’s the only thing that can stop me.”
Beinart bolsters his case against Trump by digging deep into our own history, political science, literature and religion. Included in the journey are President William McKinley (intent on Caribbean Empire building), and his opponent, William Jennings Bryan, who claimed McKinley’s action “is not a step forward toward a broader destiny; it is a step backward, toward the narrow views of kings and emperors.” John Quincy Adams appears in 1821 stating such purposeful aggressions would undermine “the fundamental maxims of American policy (and) would insensibly change (democratic practice) from liberty to force.”
Others come forward as well including Frederick Douglass, Henry David Thoreau, Ralph Waldo Emerson, W.E.B. Du Bois, John Kenneth Galbraith. Taken into account Beinart’s impressive essay and Talarico’s acceptance speech, side by side in a short 24 hours, reminds us all that the soul of our democracy requires health, unity, and the capacity to awaken “our better angels.”
To paraphrase the LeMoyne motto, our greatness must flow from our goodness. The core of a well educated electorate is knowledge, wisdom, and values. In its absence, we are left with ignorance, greed, and hatred.
Mike Magee MD is a Medical Historian and regular contributor to THCB. He is the author of CODE BLUE: Inside America’s Medical Industrial Complex. (Grove/2020)
When Artificial Intelligence Starts Rewriting Reality
By BRIAN JOONDEPH
Artificial intelligence is quickly becoming a core part of healthcare operations. It drafts clinical notes, summarizes patient visits, flags abnormal labs, triages messages, reviews imaging, helps with prior authorizations, and increasingly guides decision support. AI is no longer just a side experiment in medicine; it is becoming a key interpreter of clinical reality.
That raises an important question for physicians, administrators, and policymakers alike: Is AI accurately reflecting the real world? Or subtly reshaping it?
The data is simple. According to the U.S. Census Bureau’s July 2023 estimates, about 75 percent of Americans identify as White (including Hispanic and non-Hispanic), around 14 percent as Black or African American, roughly 6 percent as Asian, and smaller percentages as Native American, Pacific Islander, or multiracial. Hispanic or Latino individuals, who can be of any race, make up roughly 19 percent of the population.
In brief, the data are measurable, verifiable, and accessible to the public.
I recently carried out a simple experiment with broader implications beyond image creation. I asked two top AI image-generation platforms to produce a group photo that reflects the racial composition of the U.S. population based on official Census data.
Continue reading…Will AI Solve Immunology’s Debate Over “Self vs. Non-Self?”
By MIKE MAGEE
In 1872, English mathematician and sometimes poet, Augustus de Morgan, wrote this catching rhyme: “Great fleas have little fleas upon their backs to bite ‘em, And little fleas have lesser fleas, and so ad infinitum.”
This truism about competition among species for access to nutrition and reproduction could have come in handy to Napoleon 60 years earlier when he tragically underestimated his enemies will to live. It wasn’t so much the stubborn Russians as it was microbes that were his undoing.
When he launched his invasion with a staggering force of 615,000 men, 200,000 horses, and 1,372 mobile guns, he appeared unstoppable. But on his way to Moscow, (according to Tolstoy’s account of the misadventure in “War and Peace”) he lost 130,000 men to Shigella dysentery. Confronted with harsh weather and a Russian force that refused to engage in defense of Moscow, Napoleon lost 2/3 of his remaining retreating force to Typhus, carried by Rickettsia prowazekki, housed in body lice embedded in his soldiers rancid clothing.
Under more favorable circumstances, the soldiers immune systems would have been their ally. Human bioengineering has evolved side by side with pathogenic microbes determined to chemically out smart their human hosts.
Humans rely on innate and adaptive mechanisms to detect and destroy pathogens. But to do so while sparing their own cells, they must be able to distinguish self from non-self. And they must adapt and remember, producing long-lived immune cells and protein receptors that allow them to “capture” and destroy repeat offenders.
If the system experiences a breakdown in self-tolerance, the protective processes may over-shoot and result in a chronic inflammatory response that destroys healthy tissues and marks the emergence of auto-immune diseases.
One special circumstance where immuno-tolerance is both normal and essential is maternal self-suppression during pregnancy which allows two separate immunologic organisms to survive intimate relations side-by-side.
Continue reading…Can We Ride the GenAI Wave Without Getting Subsumed by It?
By DAVID SHAYWITZ
“There are decades where nothing happens; and there are weeks where decades happen,” said Lenin, probably never. It’s also a remarkably apt characterization of the last year in generative AI (genAI) — the last week in particular — which has seen the AI landscape shift so dramatically that even skeptics are now updating their priors in a more bullish direction.
In September 2025, Anthropic, the AI company behind Claude, released what it described as its most capable model yet, and said it could stay on complex coding tasks for about 30 hours continuously. Reported examples including building a web app from scratch, with some runs described as generating roughly 11,000 lines of code. In January 2026, two Wall Street Journal reporters who said they had no programming background used Claude Code to build and publish a Journal project, and described the capability as “a breakout moment for Anthropic’s coding tool” and for “vibe coding” — the idea of creating software simply by describing it.
Around the same time, OpenClaw went viral as an open-source assistant that runs locally and works through everyday apps like WhatsApp, Telegram, and Slack to execute multi-step tasks. The deeper shift, though, is architectural: the ecosystem is converging on open standards for AI integration. One such standard called MCP — the “USB-C of AI” — is now being downloaded nearly 100 million times a month, suggesting that AI integration has moved from exploratory to operational.
Markets are watching the evolution of AI agents into potentially useful economic actors and reacting accordingly. When Anthropic announced plans to move into high-revenue verticals — including financial services, law, and life sciences — the Journal headline read: “Threat of New AI Tools Wipes $300B Off Software and Data Stocks.”
Economist Tyler Cowen observed that this moment will “go down as some kind of turning point.” Derek Thompson, long concerned about an AI bubble, said his worries “declined significantly” in recent weeks. Heeding Wharton’s Ethan Mollick — “remember, today’s AI is the worst AI you will ever use” — investors and entrepreneurs are busily searching for opportunities to ride this wave.
Some founders are taking their ambition to healthcare and life science, where they see a slew of problems for which (they anticipate) genAI might be the solution, or at least part of it. The approach one AI-driven startup is taking towards primary care offers a glimpse into what such a future might hold (or perhaps what fresh hell awaits us).
Two Visions of Primary Care
There is genuine crisis in primary care. Absurdly overburdened and comically underpaid, primary care physicians have fled the profession in droves — some to concierge practices where (they say) they can provide the quality of care that originally attracted them to medicine, many out of clinical practice entirely. Recruiting new trainees grows harder each year.
What’s being lost is captured with extraordinary power by Dr. Lisa Rosenbaum in her NEJM podcast series on the topic.
Continue reading…Carta Healthcare – AI for Registry Creation
It’s not well known but there’s a lot of people in hospitals who spend a lot of time creating patient registries for quality programs, CMS reporting, clinical trials and lots more. It requires extremely detailed abstraction of patient data from patient records and comparisons with registry demands. Wouldn’t it be clever if an AI system could read the chart and help the people doing that work (usually very expensive nurses) do it quicker? That’s the premise behind Carta Healthcare. Greg Miller and Jared Crapo from Carta demoed the system for me and told me about the market for it–Matthew Holt
Will HHS Enhance or Stall the Promise of Artificial Intelligence for Healthcare?
By STEVEN ZECOLA
In its Strategy for Artificial Intelligence (V.3), the Department of Health and Human Services (“HHS”) acknowledges that: “For too long, our Department has been bogged down by bureaucracy and busy work.” HHS promises that it will accelerate artificial intelligence (“AI”) innovation, including “accelerating drug and biologic approvals at the FDA.”
History shows that well-intended but cumulative regulatory intervention – more so than scientific complexity – is the primary deterrent to rapid technological progress. If AI is subject to the typical pattern of regulatory creep, its potential to accelerate drug discovery and development will be significantly reduced. To avoid this outcome, HHS should develop a plan that is premised on a zero-based regulatory approach. That is, each new technology such as AI should start with a clean slate and only the minimum requirements deemed necessary to show effectiveness and safety should be applied in the approval process for that technology.
The Pace of Innovation
Medical innovation has lagged the pace in the other sectors of the economy. As Dr. Scott Podolsky of Harvard Medical School observed: “Medicine in 2020 is much closer to medicine in 1970 than medicine in 1970 was to medicine in 1920.” Podolsky points to breakthroughs such as antibiotics, antihypertensives, antidepressants, antipsychotics, and steroids that have not been met with same impact as innovations in the later 50 years.
Two explanations have been offered for this phenomenon: 1) the inherent complexity of biological processes; and 2) the regulatory approval process.
As a benchmark for comparison to the following case studies, the development of 4G communications spanned less than a decade, with discussions starting around 2001, technical specifications being released in 2004, and the first commercial networks launching in 2009.
Regulatory Intervention in New Technologies
- The Human Genome (Great Science Leads to Regulatory Paralysis)
The Human Genome Project (HGP) ran from 1990 to 2003, and has been lauded as one of the world’s greatest scientific achievements. The project identified the specific location of genes and DNA, creating a “roadmap” of the human genetic code and facilitating the identification of disease-related genes.
The HGP focused on balancing rapid scientific progress with ethical safeguards. Oversight was primarily managed through internal ethical programs and international data-sharing agreements rather than a single overarching legislative or regulatory body.
Under this structure, the HGP beat its target date by two years. That is to say that the complexity of the problem did not cause any delays, and progress was not impeded by the standard drug-approval bottleneck.
However, once the genetic roadmap was handed off for drug discovery and development, progress slowed dramatically.
Continue reading…The Dimensions of Artificial Intelligence in the Healthcare Industry
By STEVEN ZECOLA
On December 19th, the Department of Health and Human Services (“HHS”) issued a Request for Information seeking to harness artificial intelligence (“AI”) to deflate health care costs and make America healthy again.
As described herein, AI can be used in many dimensions to help lower healthcare costs and improve care. However, to achieve significant breakthroughs with AI, HHS will need to completely revamp the regulatory approach to drug discovery and development.
Dimension #1. Incorporation of AI into Drug Discovery
The biggest benefit to the healthcare industry’s performance from AI is achievable from drug discovery. Accounting for the costs of failures, the average FDA drug approval costs society almost $3 billion and takes decades to reach the market from its inception in the lab.
In contrast, AI identifies potential treatments much faster than traditional methods by processing vast amounts of biological data, uncovering hidden causal relationships, and generating new actionable insights.
AI is particularly promising for complex, multifactorial conditions – such as neurodegenerative diseases, autism spectrum disorders, and multiple chronic illnesses – where conventional reductionist approaches have failed.
In the short-run, HHS should direct its grants toward AI-generated basic research, with a particular emphasis on the hard-to-solve illnesses. At the same time, the FDA should be putting into place a new approval system for AI-initiated programs to enable breakthrough treatments in a compressed timetable.
Dimension #2. Incorporation of AI into the Drug Development Process
Simply relying on AI for drug discovery, while subjecting its advances to the current approval process would undermine the use of the technology.
Rather, improvements from AI can already be had in fulfilling the exhaustive regulatory documentation requirements, which today add up to as much as 30% of the cost of compliance.
Continue reading…Kai Romero, Evidently
Kai Romero is Head of Clinical Success at Evidently. The company is one of many that are using AI to dive into the EMR and extract data to deliver it to clinicians. It works to get really great information from the EMR to various flavors of clinicians in a fast and innovative way. Kai leads me on a detailed exploration of how the technology gets used as a layer over the EMR. And Kai shows me the new version that allows and LLM to deliver immediate answers from the data. This is a demo you really need to see to understand how AI is changing, and improving, that clinical experience. Meanwhile Kai is fascinating. She was an ER doc who became a specialist in hospice. We didn’t get into that too much, but you can tell about her input into Evidently’s design — Matthew Holt
