By JOE FEGHALI

Healthcare has become very good at producing disclosures. It is much less good at producing understanding.

A hospital posts a price file. A health plan publishes negotiated rates. A provider gives an estimate. A patient portal contains a document somewhere. A consent form is signed. The box is checked.

But the patient may still not understand what they are being asked to approve, what the likely cost pathway looks like, or what happens when treatment changes.

This is the quiet failure of healthcare transparency. We have spent years trying to make prices more visible. That was necessary. But visibility is not the same as usability. A price that exists somewhere is not the same as a patient understanding the financial commitment they are making before care begins.

Price transparency matters. It is just not enough.

The next frontier is not whether healthcare can disclose more numbers. It is whether healthcare can explain what those numbers actually mean.

The price is rarely the product

Most consumer markets understand the difference between a price and a purchase. A flight price means one thing if it includes luggage and another if it does not. A construction quote means one thing if it includes materials, labor, permits, and cleanup, and another if each of those becomes an add-on.

Healthcare often asks patients to make decisions with less clarity than they would expect in much simpler markets.

The deeper problem is not only that prices are hidden. Sometimes the prices are visible. The problem is that the object being priced is unclear.

A patient does not experience healthcare as a billing code or a machine-readable file. A patient experiences healthcare as a journey: consultation, diagnosis, imaging, procedure, medication, facility involvement, follow-up, revision, complication, recovery, and sometimes a second opinion when the first pathway becomes confusing.

Yet transparency policy often focuses on isolated prices rather than the care pathway the patient is actually buying into.

CMS hospital price transparency rules and Transparency in Coverage rules were major steps compared with the old world of near-total opacity. But they do not automatically solve the patient’s real question: “What will this episode of care likely cost me, and what exactly is included?”

A machine-readable file may be useful to researchers, employers, regulators, or third-party tools. It is not necessarily useful to a patient deciding whether to proceed with surgery next month, start orthodontic treatment, deliver at one hospital rather than another, or move forward with a diagnostic workup that may trigger a chain of follow-up costs.

The file exists. The confusion remains.

Estimates can become compliance theater

The No Surprises Act moved the discussion in the right direction by making good faith estimates part of the conversation for uninsured or self-pay patients. Again, this is progress. Patients should not be asked to walk into care blind.

But an estimate can still fail if it behaves more like a legal artifact than a communication tool.

There is a difference between saying, “Here is our best estimate based on the information we have,” and saying, “Here is what this pathway includes, what it does not include, where uncertainty lives, and when you will be asked to make another decision.”

The first version discloses. The second version explains.

Healthcare tends to be more comfortable with the first.

Medicine is genuinely uncertain. A surgeon may not know exactly what will be required until the procedure begins. A pregnancy can become complicated. A diagnostic scan may reveal the need for more tests. A medication may fail and require an alternative. A dental implant plan may change after imaging or grafting needs become clear.

No serious person should expect healthcare to guarantee the unknowable.

But uncertainty should not be used as a shield against explaining the foreseeable. There are predictable points where costs often change. There are common exclusions. There are typical add-ons. There are follow-up needs that may not be optional in any meaningful clinical sense.

Patients do not need false certainty. They need honest uncertainty.

“Available” is not the same as “understood”

Healthcare’s favorite defense is that information is “available.” That usually means the patient could technically find it, request it, download it, read it, interpret it, and connect it with other pieces of information from other entities.

That is a very low bar.

Patients are not confused because they are lazy. They are confused because healthcare information is often fragmented by design. The hospital knows one part. The physician group knows another. The insurer has its own view. The lab has a separate bill. The anesthesiologist may be a different entity. The pharmacy benefit sits somewhere else. The patient is then expected to assemble the truth from pieces that were never designed to fit together cleanly.

This is how a transparent system can still feel opaque.

A maternity patient may know the hospital’s posted charge but not understand how anesthesia, neonatal care, complications, or out-of-network professionals could change the final bill. A patient getting an MRI may know the scan price but not the downstream cost of specialist interpretation, follow-up imaging, or the procedure that the scan triggers. A patient starting a specialty medication may know the sticker price but not the real cost after formulary rules, prior authorization, copay assistance, deductible resets, or insurance changes.

Dentistry makes the issue especially visible because patients often pay directly and compare offers across clinics. But the problem is not unique to dentistry.

In dental care, two implant quotes may look comparable while one includes the crown and the other only includes the surgical placement. One orthodontic plan may include retainers, refinements, and follow-up visits, while another treats them separately. One veneer quote may include temporary restorations and planning, while another adds them later.

The lower number is not always the lower cost. Sometimes it is simply the less complete explanation.

That same pattern appears across healthcare: what looks cheaper may only be less bundled, less explicit, or less honest about what is likely to happen next.

Cost confusion changes care

This is not a paperwork problem. It changes patient behavior.

KFF has reported that many adults skip or postpone needed healthcare because of cost, with the burden especially severe among uninsured adults and still significant among insured adults. When people do not trust the financial pathway, they delay. When they delay, conditions can worsen. When conditions worsen, treatment becomes more complicated and more expensive.

Then the system laments late presentation.

But late presentation is not only a clinical access problem. It is also a trust problem. Patients are more likely to move forward when they understand what they are committing to. They are more likely to avoid care when the first number feels like the opening bid in a negotiation they do not understand.

Healthcare has spent a lot of time asking how to make patients better consumers. The harder question is whether healthcare has made itself possible to consume intelligently.

In many cases, it has not.

Quote transparency is the missing layer

The next phase of transparency should focus less on publishing more disconnected numbers and more on making the treatment quote understandable.

That does not mean turning clinicians into accountants or forcing providers to predict every possible complication. It means creating a clearer standard for financial communication before care begins.

A usable quote should explain the care pathway, not just the headline price. It should distinguish between included services, excluded services, likely add-ons, conditional costs, and true unknowns. It should make clear when a patient will be asked for new consent if the plan changes. It should show whether follow-up is part of the treatment or a separate financial event.

This would not only protect patients. It would protect good providers.

Right now, providers who explain costs carefully can look more expensive than competitors who advertise incomplete prices. The honest quote loses to the attractive fragment. That is a perverse incentive. A transparency standard should reward completeness, not punish it.

In my own work around dental cost transparency, the most important lesson has not been that patients need a single magic number. They do not. The lesson is that patients need to understand why numbers differ, what is inside them, and what questions remain before they commit.

That is true far beyond dentistry.

Healthcare transparency should not end at disclosure. It should end at comprehension.

Until then, the system will keep congratulating itself for publishing prices while patients continue asking the only question that really matters:

“What am I actually agreeing to?”

Dr. Joe Feghali is an orthodontist and founder of LumiQuest Dental Circle, an independent patient-guidance platform focused on helping patients compare dental care more safely and transparently.

By EMANUEL SARKEES

The United States is in the middle of what researchers are calling one of the most significant pharmacological developments in modern medicine. GLP-1 receptor agonists, the drug class behind Ozempic and Wegovy, have become able to reduce obesity, lower cardiovascular risk, control blood sugar, and show signals improving areas like addiction and dementia. It is backed by large scale clinical trials and is actively reshaping how physicians think about chronic disease management. The accessibility, however, is not keeping up with the science. The people who will benefit most from GLP-1s are the same people who have no path to receiving them.

This is not a coincidence. It is the outcome of a pricing structure, an insurance system, and a policy environment that have consistently made the same choice, which is to let cost determine who receives care.

What GLP-1s Actually Do

GLP-1s were originally developed to treat Type 2 diabetes. They work by acting similarly to a hormone the gut naturally produces after eating, which signals the brain to reduce appetite, slows digestion, and stabilizes blood sugar levels. The effects have been significant enough that the medical community’s interest has expanded well beyond diabetes management.

A 2023 clinical trial, known as the SELECT trial, found that semaglutide, the active ingredient in Wegovy, reduced the risk of cardiovascular issues like heart attacks and strokes by 20% in patients with obesity who did not have diabetes. That finding alone drew serious attention from cardiologists. Early research is also exploring GLP-1s in alcohol use disorder, sleep apnea, chronic kidney disease, and Alzheimer’s. The amount of potential application is unlike anything seen from a single drug class in recent times.

The Price Problem

The issue is not whether these drugs work. It is whether the system is built to let people use them. Wegovy, the FDA approved version specifically made for weight management, holds a price of around $1,300 per month in the United States without insurance coverage. Ozempic, technically approved for Type 2 diabetes but widely prescribed off label for obesity, runs at a similar cost. As one analysis noted, GLP-1 pricing “increased 442% between 2021 and 2023, creating a market three times larger than cancer spending, with list prices reaching $1,400”. Novo Nordisk and Eli Lilly, the two companies that dominate this market, charge American patients prices that are dramatically higher than what patients pay for the same medications in other countries.

The actual price a patient pays has very little to do with that $1,349 list price and almost everything to do with how they access the drug. With commercial insurance that covers obesity, costs can fall to around $25 a month, though that requires a plan that actually covers weight loss medications and prior authorization that actually gets approved. The Wegovy pill is available directly through NovoCare at $149 per month, the lowest price point ever for an FDA-approved GLP-1 weight loss medication. Zepbound starts at $299 per month through LillyDirect for patients who pay out of pocket. The government’s TrumpRx platform offers GLP-1s at around $350 per month for cash-paying patients who do not have coverage. Compounded versions through telehealth platforms like Ro and Hers run anywhere from $99 to $349 per month, though the FDA is actively restricting that market. And as of July 1, 2026, eligible Medicare beneficiaries can access Wegovy, Zepbound, and Foundayo at a flat $50 per month through the new Medicare GLP-1 Bridge program. That is a 27-times spread between the lowest and highest price for the exact same drug, determined not by what the medicine costs to make, but almost entirely by who you are when you walk up to the pharmacy counter. And for the uninsured, low income patient with no Medicare, no qualifying commercial plan, and no compounding option, none of those prices are on the table at all. 

At $1,300 per month, the annual cost of Wegovy exceeds $15,000. For millions of Americans, that number is not just high, but is completely out of reach. That gap in pricing is not accidental. In countries where governments negotiate drug prices directly, the same medication costs a fraction of what Americans pay. The United States remains one of the only developed nations that does not regulate pharmaceutical pricing at the federal level, and patients suffer the difference.

Insurance coverage for GLP-1s follows a path that is both frustrating and familiar.

Most private insurers will cover these medications when prescribed for Type 2 diabetes. For obesity, even clinically severe obesity, the kind directly associated with cardiovascular disease and early mortality, coverage is inconsistent, frequently denied, and in many cases nonexistent. Medicare was prohibited from covering weight loss drugs for years, and while recent movements have begun to change that, the coverage aspect remains unresolved for a large portion of the population.

The contradiction here is hard to ignore. Insurers who decline to cover a $1,300 monthly medication are regularly paying for the hospitalizations, cardiac procedures, and diabetes complications that untreated obesity produces. The long term math does not support the denial, but the short term cost containment logic continues to make coverage decisions. What results is a system where the financial burden gets deferred rather than eliminated, and the patient absorbs the cost in the meantime.

Obesity in the United States disproportionately affects lower income populations and communities of color, the same populations that are most likely to be uninsured or underinsured. It reflects the same pattern shown across almost every dimension of American healthcare: the people who need the most support are consistently positioned with the least resources to receive it.

This is not a new observation, but GLP-1s make it very urgent. For a long time, the standard interventions for obesity, diet counseling, behavioral therapy, bariatric surgery, have each carried their own access barriers. GLP-1s were supposed to be different. A weekly injection, manageable side effects, dramatic results. Instead, the same economic wall that blocks access to everything else is blocking access to this too, and the populations most affected by obesity are once again left watching a solution exist just out of reach.

During a national shortage of semaglutide, compounding pharmacies began producing unregulated versions of the drug at lower price points, and a large number of Americans turned to them as an alternative. The quality and safety of those products varied greatly. The FDA has been steadily restricting that market, which means even the workaround that lower income patients relied on is narrowing. What remains is a coverage gap with no current policy designed to close it.

Where Things Stand

There are signs of movement, and one of them is genuinely significant. On July 1, 2026, Medicare launched the GLP-1 Bridge program, a pilot that gives eligible beneficiaries access to Wegovy, Zepbound, and Foundayo for obesity at a flat $50 monthly copay. For a drug that costs $1,300 a month at list price, that is a meaningful shift, and for millions of older Americans who have never had any coverage path for these medications, it represents something that did not exist before. But it is not enough, and it is worth being direct about why.

The $50 copay sounds accessible until you consider who Medicare’s lowest income beneficiaries actually are. A quarter of Medicare enrollees had incomes below $24,600 in 2024, and for someone living on a $750 monthly Social Security check, an extra $600 a year for a single prescription is not a minor expense. The low income subsidy program that normally reduces drug costs for the poorest beneficiaries does not apply to the Bridge program. And the program itself expires December 31, 2027, with no guaranteed path to permanent coverage after that.

Beyond Medicare, the picture is worse. Only 13 states currently cover GLP-1s for obesity under Medicaid, down from 16 states just a year ago, as budget pressures force states to pull back. For the uninsured working-age population, the compounded semaglutide that made the drug accessible at around $200 a month is being steadily restricted by the FDA, and no affordable replacement has emerged.

What would actually move the needle requires policy action on multiple fronts. The Treat and Reduce Obesity Act, which would permanently lift Medicare’s statutory ban on obesity drug coverage, has bipartisan support but has stalled over cost concerns  despite studies projecting over $18 billion in healthcare savings over a decade. Medicaid coverage of GLP-1s for obesity needs to be made mandatory at the federal level rather than left to individual states to opt into and out of based on budget cycles. And federal drug price negotiation, which began in a limited way under the Inflation Reduction Act, needs to be extended aggressively to this drug class before the compounding window closes entirely.

The Medicare GLP-1 Bridge is a start. It is not a solution. A breakthrough that is accessible only to some Medicare beneficiaries for 18 months, in 13 states through Medicaid, and at $200 a month through a compounding market being shut down is not a healthcare policy. It is a placeholder. The drug exists, the evidence is overwhelming, and the cost of inaction keeps accumulating in emergency rooms and late stage diagnoses. What is missing is not the science. It is the political will to match access to what the medicine can actually do.

Emanuel Sarkees is a high school student with a strong interest in medicine, healthcare, and innovations that improve patient care and access to treatment

By JOHN SAMARAS

Ask what Ozempic costs. The honest answer runs from $25 a month to $1,100 a month, and every number in that range is real, published, and defensible. A phrase that covers a forty-four-fold spread is not a price. It is a fog, and patients make four-figure annual decisions inside it.

I run GLP Chart, an independent GLP-1 price index. The index shows that “the price of Ozempic” fails as a concept for three stacked reasons. The molecule sells in five forms under four names. Each form sells through different channels at different prices. And the advertised price rarely survives to month four.

One molecule, five forms

Ozempic is semaglutide, branded for type 2 diabetes. The same molecule is Wegovy when approved for weight loss, sold as a weekly pen and, since 2026, a daily pill. It is Rybelsus in the older oral form. And 503A compounding pharmacies still sell it as compounded semaglutide where the rules allow, though the FDA’s compounding restrictions and the manufacturer lawsuits thinned that market through 2025 and 2026.

When someone says “Ozempic price,” they almost always mean “what will semaglutide cost me.” Those are different questions with different answers.

Same molecule, seven prices

Here is the current board from our price index. Every cash figure comes from the seller’s own published pages. The last two rows are copays.

Every row is “the price of Ozempic” in somebody’s mouth.

One row is worth a second look. Novo Nordisk cut its own direct-to-consumer pen price from $499 to $349 in November 2025, a 30 percent cut. The pharmacy-counter price above did not move. The gap between those two rows is not a market inefficiency. It is the business model.

The membership layer

A telehealth program that prescribes the Wegovy pill routes you to the same $299 NovoCare price you could get yourself. What the program adds is a membership fee, $74 to $149 a month across the programs we track, covering the prescriber, the app, and refill logistics. Whether that fee buys anything you need is a fair question, and it is a different question at $74 than at $149.

Two design choices in this layer deserve more attention than they get, because they work together.

First, starter-dose pricing. The pill that costs $149 in month one costs $299 at the dose you will actually stay on.

Second, lock-ins. Eight of the 29 programs we track commit patients to a contract, three of them for a full year. A teaser price plus a contract is a retention machine, not a discount.

The pricing is also granular enough that even the sellers engage with it line by line. This week, Ro’s communications team wrote to flag that an annual prepaid medication plan cuts their Wegovy pill price to $249 a month. They were right. Their published pricing page confirms it, and our listing now says so. It takes that level of specificity to state one program’s one price for one form of one molecule. “The price of Ozempic” was never going to survive contact with this market.

What to check before paying anything

Five questions, in order:

1. Which form of the molecule is the quote for: Ozempic, a Wegovy pen or pill, Rybelsus, or compounded?
2. Is that the starter dose or the maintenance dose? Ask what month four costs, not month one.
3. Does the number include the membership fee, or is that billed separately?
4. Can you leave month to month, or are you signing a contract?
5. If you have insurance, has anyone actually run the prior authorization? A $25 copay beats every cash price on this page.

“The price of Ozempic” will keep showing up in headlines because it is short. But it hides the two numbers that decide whether treatment is affordable: the maintenance-dose total after the teaser expires, and the fee stack on top of the medication. Name the form, name the channel, name the month. Then you have a price.

John Samaras is the founder and editor of GLP Chart, which tracks what every major GLP-1 program charges, checked every Monday, with the methodology public. No program pays to be listed or ranked.

By KIM BELLARD

The most (unintentionally) amusing story I read this week was Tim Higgin’s Wall Street Journal article Alex Karp Is Saying What Every Angry CEO Is Thinking About AI. Dr. Karp (yes, he has a Ph.D.), co-founder and CEO of Palantir Technologies, is upset about how AI companies are using relationships with their business customers to harvest data and business insights from those customers. “Something has gone completely wrong,” he fumed.

Now, this is Palantir, mind you; it may not have invented surveillance capitalism but it might have perfected it. It has become essential to government and large corporations across the world. Most of us are aware of how tech companies like Meta or Google give us “free” services that exist primarily to collect more data on us, which they then use to target ads to us, but Palantir’s data collection and analysis operate at a level we often don’t recognize.  But make no mistake; it is using our data, and not necessarily in our best interests.

Mr. Higgins quotes former White House AI czar David Sacks in support of Dr. Karp’s concerns:

Anthropic has launched Claude Science, Claude Security, Claude Legal, and of course Claude Code—each expanding into categories previously served by companies building on top of their models. The pattern is consistent: Watch where value is being created, then move in directly. Dominate the model layer, then use that position to capture the most lucrative verticals.

So it is delicious irony that Dr. Karp and others are finding themselves at the wrong end of the power inequality with their data.

I find myself thinking about healthcare when I think above this new wave of data collectors/ synthesizers. It seems pretty clear that the AI companies aren’t going anywhere, and are expected to reshape most industries, including healthcare. Lots has been written about AI’s use in healthcare, including by me. It is both inevitable and, in many cases, desirable. Now this issue of AI’s insatiable appetite for data makes me wonder if we’re looking at things wrong.

I’ve worked in healthcare for longer than I care to admit, and at no point did people not complain that healthcare in general, and health insurance in particular, was too expensive. And yet, costs have kept rising. We’re closing in on $6 trillion in U.S. healthcare expenditures. No matter what kind of health insurance you have – large employer, small employer, ACA Marketplace, Medicare Advantage, even Medicare Supplements for traditional Medicare – your premiums (and/or out-of-pocket costs) are likely going up at rates we haven’t seen in years.

Two well known facts about rising costs are, one, that it is not so much we’re using too many services as it is that Americans pay way higher prices for healthcare than in most countries, and, two, that a relatively small percentage of people account for the vast majority of healthcare spending. The latter has an insidious effect on health insurance premiums, as people with fewer expenses are less likely to have or keep health insurance, making premiums for the remaining people higher. Nobody wants to pay for the people who use a lot of health care, but they want other people to help pay if they end up being one of those people. It’s a conundrum.

Now, optimists hope that AI can do a better job of identifying all the wasted, unnecessary, or inappropriate care we use – estimated as much as one-third – and help make administration more efficient; current levels are estimated as 15-30% of spending. Good goals, both of them, and it is entirely plausible that AI can help with both. But it would still remain that sick people are the “problem” with our health care spending and health insurance premiums, and I want to propose a different way of looking at them.

Healthcare generates massive amounts of data, increasing all the time. Some estimates put it well in the exabyte level, which, trust me, is way more than any of us can comprehend. We generate data when we go to the doctor, when we get lab work, when we fill a prescription, when we go to the hospital, even when we use a wearable like a smartwatch. All those health insurance claims and all those healthcare bills generate data. And, yet, most of that data isn’t effectively used, which I sure hope AI does something about.

So we have a system in which the people who use more health services generate more data, and an AI industry that craves data. This seems like it should be a match made in heaven.

Why couldn’t we have a healthcare system in which AI companies pay people generating healthcare data for that data? I.e., instead of heavy users of healthcare being drivers of spending, they become a valuable resource? And, oh-by-the-way, why aren’t we being paid for our data?

Our data, healthcare data included, is being shared, bought and sold now. Sometimes it is deidentified (supposedly), sometimes not. Either way, we’re not the ones getting paid for it. That should change.

Now, realists will point that that “value” of our healthcare data is nowhere near the costs of our health care, so paying for the latter with the former is impractical. I’ll grant that is currently true, but I’ll also ask: why is that?

I’d argue that our health data is grossly undervalued, because the companies using it are used to getting it so cheaply, and that our health services are wildly overpriced. Reorienting the system so that the former funds the latter should bring them closer into equilibrium.

If data is, as has been said, the new oil, then I’ll point out that oil was also once very cheap, until enterprising people figured out that they could control the supply and thus raise the price virtually at will. We should be those people when it comes to our data, especially our healthcare data.

So I’ll be amused at Dr. Karp being faux outraged at other data companies profiting off of his company’s data, and I’ll hope that we have a fundamental rethinking about who generates value in our data world and how that value is realized. There can’t be a better place to do this than in healthcare.

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

By CRAIG HAUBEN

Ask anyone outside healthcare who resists clinical AI and you’ll get a confident answer. The older doctors. The ones who spent thirty years building expertise and now see a machine coming for it. The story writes itself, which should have been the first clue it was wrong.

I’ve spent thirty years in healthcare, and I now run a company that builds and runs AI inside provider and payer organizations. At Clutch we use AI’s data analysis to solve engagement challenges. Who is the patient today? What message will land with them? When do they want to read it? Get those right and you can drive the kind of sustained behavior change that moves clinical outcomes like drug adherence, care plan adherence, and gap closure.

So I’m not working from theory. I watch this land in real workflows, and here’s what I see. The clinicians most enthusiastic about AI are usually the ones who’ve done the job the longest. The resistance comes from somewhere else. If you run a health system, that difference should change how you plan your next deployment.

Start with the adoption numbers, because they already break the resistance story. The AMA’s latest survey found four in five physicians now use AI in practice, up from 38 percent in 2023. That’s not a profession digging in against a threat. That’s a profession that found something useful.

Now the veterans. A doctor with three decades in a specialty can see, better than anyone, what these systems are good at. Pattern recognition at scale. Catching the thing that should have been flagged two visits ago. Surfacing what was already sitting in the data: the missed finding in last year’s imaging, the lab trend across eighteen months that looked unremarkable one value at a time, the three ED visits in six weeks nobody had the time to connect.

This isn’t hypothetical. The Nature study of Google’s breast cancer screening system showed a 9.4 percent drop in false negatives for US patients, the cancers human readers missed. The largest NHS evaluation to date, across 175,000 women, found AI caught more invasive cancers with fewer false positives than human readers. The harm these systems go after, information that existed and never got connected, is one experienced clinicians know cold. They’ve spent careers watching its absence hurt people.

Here’s one from our own work. We’re working with a national government programs payer on some of their hardest members to engage, the high intensity ones who need contact four or five times a day for six months or more. We got engagement to 95 percent, measured by the customer, and adherence to 93 percent. The result was a 0.8 average drop in HbA1c and an 18 percent reduction in symptoms.

When a system takes the mechanical load off so the judgment work gets more attention, the thirty-year clinician doesn’t feel threatened. They feel relieved. Their expertise is the judgment, not the data retrieval, and they’ve always known the difference.

Now look at where the fear actually lives. It comes from the middle.

The people who built careers on being the synthesizer, the translator between systems, the one who pulled information from six places and assembled it into a picture. That role is under real pressure, not clinical judgment. Anthropic’s labor market research points the same way, finding AI exposure concentrated in exactly this kind of assembly work rather than in judgment-heavy roles. The synthesizer is scared. And the synthesizer is right to be, because synthesis is what these systems do best.

Both responses are rational. That’s the point. Your workforce isn’t split into the enlightened and the fearful. It’s split by what people do all day, and the line doesn’t run where the conventional wisdom says it does.

If you run a health system, that has three consequences.

First, your deployment champions aren’t who your consultants think. The standard playbook recruits young physicians as AI ambassadors, on the theory that digital natives adapt faster. Recruit the thirty-year veterans instead. They have the credibility, they can say exactly where the system helps and where it can’t be trusted, and their word carries different weight in the staff lounge. A skeptical senior clinician turned into a precise, conditional advocate is worth ten enthusiastic residents.

Second, the people in the synthesis layer deserve honesty, not slogans. Telling a care coordinator or a utilization review nurse that AI will simply make their job easier is how you destroy your own credibility, because they can see the mechanism as clearly as you can. The honest conversation is about which parts of the role are moving into the machine, what the role becomes after that, and what the institution will do to carry people across the gap. Most organizations aren’t having that conversation. The ones that do will keep their best people. The ones that don’t will lose them at exactly the wrong time.

Third, stop measuring adoption and start measuring trust, in both directions. Nearly every Fortune 500 company now tracks employee AI usage, and healthcare is copying the habit. Usage is the wrong metric. A system clinicians use reluctantly under mandate is a risk. A system clinicians trust past its real performance envelope is a bigger one. The AMA’s sentiment data captures the right posture better than any dashboard. Roughly two in five physicians say they’re equally excited and concerned, and that ambivalence isn’t a problem to manage away. It’s the right response to a powerful tool with uneven performance, and it’s exactly the disposition good governance should be built on.

The veterans are your asset here too. The clinicians most excited about these tools are often the most precise about their limits, because real expertise includes knowing what the tool can’t do. Build your oversight around that precision instead of around utilization dashboards, and you get an early warning system staffed by the people best qualified to run it.

The coverage of AI in medicine keeps offering two stories. The machine that replaces doctors, or the machine that destroys medicine. People who run things don’t get to live in either one. The real version is more granular, in places really good, and it starts with noticing that the people we expected to resist this are the ones quietly showing us how to use it well.

That gap, between the two clean stories and what happens on the floor, is what got me writing the book. The AI: Migration is a novel about how AI is disrupting work. Every AI system and clinical event in it is drawn from the documented record, so while the characters are fiction, the AI stories are real.

Craig Hauben is CEO of Clutch and has spent thirty years as a healthcare operator and executive. His novel The AI: Migration publishes in July 2026.

By DAMIAN WONJO

Every clinician keeps a private list of the patients they don’t see. Not the ones who cancel, the ones who never book. The shift worker who reschedules the same appointment three times and then quietly gives up. The parent who can’t justify half a day off and a waiting-room afternoon for a routine refill. The patient whose condition carries enough stigma that the friction of a face-to-face visit becomes, in itself, a reason to do nothing. These people don’t show up in no-show statistics. They show up later, as complications, as emergencies, as avoidable deterioration.

This is the access gap, and from where I sit as a physician in Europe, it has less to do with the raw supply of doctors than with the cost of reaching one, measured not only in money but in time, distance, and effort. When that cost climbs higher than a patient’s tolerance, care simply doesn’t happen. Online prescription services and remote consultation won’t fix every part of this problem. But they target precisely the variable that most reforms ignore, which is friction.

The patients who fall through

It is tempting to frame telemedicine as a convenience for the already-healthy and already-connected. In practice, the people who benefit most are often those with the least slack in their lives. A patient stabilised on the same antihypertensive for three years does not need a fresh diagnostic odyssey to continue it, they need a prescription before they run out. A working adult who recognises a recurring, familiar problem does not always need a physical examination to be helped safely. Forcing every such encounter through the narrow door of an in-person appointment does not raise the standard of care, it raises the rate at which people abandon it.

Continuity is where this matters most. Chronic conditions are managed in refills, and a missed refill is not a clerical event but a gap in treatment with real physiological consequences. Lowering the barrier to that refill is not a luxury. It is, quietly, one of the highest-yield interventions available.

What changed in Europe

The pandemic did not invent telemedicine, but it normalised it, and it accelerated the infrastructure underneath it. Poland is a useful case study. Electronic prescriptions became the national standard in 2020, and today essentially every prescription is issued digitally, retrievable by the patient through a government health account and dispensable at any pharmacy with a code. The clinical encounter and the prescription were decoupled from a single physical location without being decoupled from a licensed prescriber.

That distinction is the whole argument. A responsible online prescription service is not a vending machine. It is a licensed physician, working within the same legal and ethical framework as any clinic, using a different channel to reach the patient. The technology is mundane. The consequence, that a patient who would otherwise have gone without is now seen, is not.

The honest limits

I want to be precise about where this model should not go, because credibility depends on it. Remote prescribing is appropriate for continuation of stable therapy, for clearly defined and low-risk presentations, and for situations where a careful history is genuinely sufficient. It is not appropriate as a substitute for examination when red-flag symptoms are present, for escalating or undifferentiated complaints, for most controlled substances, or wherever the absence of a physical exam meaningfully raises risk. A good service builds those boundaries into its triage and refers patients onward when the safe answer is that this needs to be seen in person.

Telemedicine that ignores those limits does not close the access gap, it relocates risk. The clinicians and platforms doing this well are the ones most willing to turn patients away from the online channel when that is the right call. Convenience is the feature. Clinical judgment is still the product.

What the conversation often misses

Debates about online prescribing tend to collapse into a binary, either it is dangerous shortcutting or it is frictionless progress. Neither framing is useful. The more honest question is narrower. For which patients, and which problems, does removing the friction of an in-person visit improve outcomes without degrading safety? For a large and underserved middle, meaning stable chronic patients, predictable refills, and conditions people are reluctant to present in person, the answer is increasingly clear. For acute, complex, or high-risk care, it remains no.

Health systems on both sides of the Atlantic spend enormous energy expanding capacity and almost none reducing the friction that wastes it. A patient who never books is invisible to a system optimised around the patients who do. Online prescription services, used within proper limits, make some of those invisible patients visible again. That is not a revolution. It is something more durable, a quiet correction to a gap we had simply stopped noticing.

Dr Damian Wojno is a physician who collaborates with the Polish telemedicine service eRecepta Online24.

By MATTHEW HOLT

It’s hard to imagine but I may now be in possession of the stupidest letter I’ve ever received from an American health insurance company–-and I’m the guy who got five identical letters on one day from Blue Shield of California telling me that they had changed my primary care doctor when I had initiated the change.

A little backstory.  As those you’ve been following along with my various telenovelas may remember that last year I was diagnosed with a failing heart valve.  I also have a failing left knee due mostly to snowboarding into a tree 24 years ago.

I was attempting to put off doing anything about the heart valve for as long as possible because it sounds painful and unpleasant, and I was hoping that I could go ahead with a knee replacement so that my snowboarding can continue apace. My doctors are at UC San Francisco and they agreed that I should have the knee replacement on July 6th, assuming that my heart valve had not got much worse. On June 16th I went into UCSF for a bunch of knee replacement pre-workup and they also checked my heart.

However, my new insurance company, thanks to my wife’s new job, is Cigna. Those of you in California may know that Cigna was having a big dispute with the University of California Health system and that its contract with them was due to expire on June the 30th of this year. Why a health plan and a big provider organization have contracts that expire in the middle of the year when the employers and people who use the health plan network buy them on an annual basis starting in January I don’t know –  and it’s ridiculously stupid. But let’s not get distracted cause I’m not talking about that here!

Because of the fact that they’d be out of network, the ortho team made the obvious suggestion that I move the knee replacement a little earlier, In fact it was planned for June the 22nd. This did not upset me too much as you may have seen that some corrupt Italians have organized a soccer tournament that would give me plenty of games on TV to be entertained by while I was lying around recovering.

Sadly one of the pretests I had on June 16th was an echocardiogram that indicated that my heart valve was in even worse shape than it had been earlier in the year.  After quite a lot of back and forth between the cardiac team, the knee team and the anesthesia team, everyone agreed to put off the knee surgery until we figured out my heart.

Meanwhile sometime late on Thursday the 25th or early on Friday the 26th of June, UC Health and Cigna stepped back from the brink and came to an agreement that will continue the UC system being in Cigna’s network.

Which all brings me to July 6th when I received a letter from Cigna

This is the one that contains more stupidity per square inch than any other communication I’ve had from an insurance company.

First things first; Cigna has a semi-decent website which I have accessed on many occasions. Cigna knows my email. Cigna knows my phone number and also that I can receive a text from them. 

The letter was dated June 25th but I received no email, no text, no carrier pigeon message on that date. And if you go to the messages section of the website which I’ve copied for you below you’ll see that the only communication they have sent me shows that I can get a good deal on joining a fitness club. Although sadly the local one I use isn’t in this deal….

So we’ve established they could have communicated with me on June 25th but instead I received their letter on July 6th.

What did the letter say?

Well to be helpful I have scanned a version of it for you below

The first incredibly stupid thing is that they sent me a letter.  This cost them presumably rather more than sending an email or a text and it also arrived after the period discussed in the letter had ended.

The next incredibly stupid thing is that they told me that UCSF was not in their Network on 6/25/2026.  This is wrong. Even under the contract that was about to expire UCSF was in Cigna’s Network on 6/25/2026 and was going to be for another 4 days. 

Now I’m not sure if the next incredibly stupid thing was Cigna’s fault or UCSF’s.  Apparently UCSF had requested Cigna to cover the surgery I need, which is an aortic valve replacement and by the way involves me being on a heart-lung machine which doesn’t sound like a lot of fun.

But what’s incredibly stupid is that the approved effective dates for this were June 30 through July the 4th. Now there are two things worth knowing about here.  Even though it was probably still the case that on June 25th when this letter was written UCSF was about to be kicked out of the Cigna Network on July 1st,  on June 30th they still were in the network. So for the letter for say they were out of network when it was written was wrong. And as it turns out UCSF is still in the network now.

The second incredibly stupid thing is that at no stage did I have scheduled or planned to have surgery in those few days (June 30-July 4) for which this approval was effective.  I’m also pretty certain that no one at UCSF thought I was going to have surgery on that date mostly because on June 30th I actually had a coronary angiogram as continued prep for the surgery. A surgery planned for a date to be named later this summer. The angiogram was not the procedure mentioned in this letter.

Finally, although Cigna has approved this procedure, albeit for a date on which it was never going to happen, they approved it at an out of network rate, and stated that there was a maximum amount that they will pay. Very helpfully on the second page of the letter it says that “I may be able to save money by seeing a health care provider who is in my network” and “to see a list of these professionals I should look at the Cigna website”.  It then scolds me by telling me that I chose a health professional who isn’t in the network. Of course they’re not telling me how much they are going to pay or how much less I would pay out of pocket if I went to an in-network provider. 

Except of course I already was and now am doing exactly that.

So to sum up. 

• Cigna sent me a letter that took 11 days to get to me as opposed to sending an email or text. 
• The information in the letter was incorrect regarding Cigna’s provider network
• The period for which it approved the requested procedure was also incorrect
•  And that period ended 2 days before I got the letter

I guess we should congratulate them on getting the procedure roughly correct

It would be churlish for me to point out that Cigna’s CEO David Cordani got paid $23 million dollars last year. I can only assume the Cigna board compensation committee was not rewarding him based on the level of accuracy of the customer service his company provided. On the other hand it’s not clear what necessary services his company or its health insurance competitors actually do provide.

And it would be equally churlish for me to point out that no one else in the world outside of the US has to deal with this.

Matthew Holt is publisher and author of THCB

By KIM BELLARD

Well, let’s see. Last week much of the U.S. and parts of Europe were under a crippling heat dome. The U.S. celebrated its 250^th birthday. And there’s something called the World Cup going on, for those of you who care about such things. But, I mean, really, the news of the week? SpudCell.

OK, maybe you missed that one. If you are not a fan of science, or of synthetic biology in particular, news about it might not have shown up in your feeds, or perhaps you thought it was another ploy by the Potato Association of America to get you to buy even more potatoes. SpudCell is something truly new: “the world’s first synthetic cell with a complete life cycle, built entirely from non-living chemical components.”

Take a minute to take that description in.

“SpudCell performs the behaviors often used to tell the living from the inert — it feeds, grows, replicates its genome, divides and undergoes selection — yet it is far simpler than any natural cell and was assembled, part by part, by hand,” the project researchers wrote in a statement.

It was designed and built by researchers at the University of Minnesota, announced last week along with a preprint of their paper.The team was led by Professor Kate Adamala, and the name is either due to its supposed resemblance to a potato or it’s a play on “Sputnik.”

“This is likely the most exciting project I’ve ever worked on,” said Professor Adamala. “We’ve replicated in chemistry what only used to be possible in biology: the complete set of behaviors of a cell. It proves that the most fundamental functions of life, like growth and replication, do not need a mysterious magical spark.”

Scientists have been working for decades on stripping away genetic material from living cells to try to find the minimum necessary for life, but Professor Adamala and her team went the other way, gradually building up genetic material until it started behaving in ways we’d expect cells to.

The impressive thing is that the team engineered everything SpudCell does. As The Economist put it: “Everything the resulting cells do, they do because of molecules that Dr Adamala’s team put there. That leaves no room for mysteries.” That’s not true when researchers start with living cells.

Drew Endy, a synthetic biologist at Stanford University, told Carl Zimmer of The New York Times, “It’s a cell that was built, not born. It’s constructed, but it does what cells do.”

SpudCell is very basic.

The human genome has about 3 million kilobase pairs (kbp); SpudCell has 90. And, instead of a single chromosome, SpudCell’s genome is split across seven separate DNA plasmids, while allows researchers to program various cell functions independently.

Whether SpudCell qualifies it as “life” is murky. Professor Adamala cautioned: “Life is not binary. That’s why I’m hesitant to call this ‘alive.’ There’s no clear line, as much as we would love it to be.”

For example, SpudCell doesn’t make its own ribosomes, using ones from e coli bacteria instead, which means it can only replicate for 5-10 generations before things degrade. It also needs some help feeding, with nutrient-carrying liposomes having to be added regularly. But, still; not bad for 90 kbp.

Other scientists are pretty impressed. “Kate Adamala’s team designed and built a nonliving synthetic cell that is much closer to being ‘alive’ than anything else produced by the bottom-up synthetic cell field,” said John Glass, who leads synthetic cell research at the J. Craig Venter Institute. “It is dazzling that she has put these things all together.”  

“This is a stunning scientific achievement,” says Roseanna Zia, a computational cell biologist at the University of Missouri.

Prof Tom Ellis, at Imperial College London, told The Guardian the work was probably the field’s “biggest breakthrough in recent times,” further explaining: “Making a synthetic cell helps us understand the exact minimum requirements for life and how life might have emerged from chemistry. It’s also useful as it provides a fully understood system for testing biological circuits and computer models of cellular life.”

Professor Adamala admits that in some ways SpudCell is “as dumb as it gets,” and likens it to the Wright brothers’ first airplane, noting that researchers who start with real cells are “like an engineer that’s given a full Dreamliner without all the plans.” Dr. Endy also used the Wright brothers analogy, telling Mr. Zimmer: “The Wright flyer flying for 12 seconds doesn’t get you a 737. This is just the beginning.”

Professor Adamala, along with Professor Endy and two other researchers, have founded Biotic, a public-benefit nonprofit research organization to further the research. They hope to create a shared technical infrastructure for synthetic cell engineering, with a mission “to responsibly enable and steward foundational advances in bioengineering.”

To help other scientists use SpudCells in their research, the Biotic site includes detailed protocols for building SpudCells. It notes: “While our motivation for this research is to make biology a general-purpose technology, usable freely by all, we are currently operating in the sandbox environment.” 

Early days.

Professor Adamala says:

This work is just the beginning. We are showing it’s possible to engineer the basic functions of the cell. To fully realize the promise of this technology – to make it robust and practical – we need combined international effort. The role of Biotic is to focus engineering efforts and make them compatible with a shared chassis. SpudCell is that chassis, and with Biotic setting the protocols for collaboration, we are eager to start applying this technology to serious challenges.

“This work demands our attention, not for what has been produced but for where it leads,” Dr. David A. Relman, a microbiologist at Stanford University, told K.R. Callaway of NYT, adding: “It is creative, disruptive and provocative in revealing what might be possible in the not-so-distant future.”

“Creative, disruptive, and provocative” — music to my ears.

The University of Minnesota announcement makes clear the hope for synthetic biology in general, and SpudCell in particular:

Cells built from scratch could perform molecular transformations industrial chemistry cannot. That could first transform molecular medicine, building precise therapeutic molecules including drugs incorporating amino acids evolution never used. We could see materials that are grown, rather than synthesized, and manufacturing approaches that operate at biological temperatures, not industrial ones. Underneath it is a truly engineerable platform, which SpudCell provides for the first time.

OK, maybe the researchers didn’t “create life,” but the Wright brothers crashed many times before they succeeded. I love this idea of building from the bottom, and I’m rooting for SpudCell to grow up.

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