Historically, insurance has paid for activity: time spent in visits, RVUs generated, and minutes logged. This was a reasonable starting point, but the flaw is that there's no strong incentives to be efficient.
ACCESS is explicitly a "deflationary" approach. Medicare has set the payment rates high enough to be viable for startups, but low enough that you have to use software (including AI) to deliver a large part of your program.
So Medicare has basically created economic incentives to reward software without prescribing the exact shape of the programs. I thought it was a really interesting approach and builds on 15 years of lessons from CMMI (Medicare's innovation group).
That would put hospitals somewhere between churches and offices in terms of the impact they have attracting attendance.
This was a feature, not a bug. More inefficiency means more profit can be captured.
Remember: this is just v1. In theory Medicare Access will learn to weed out the bad actors and get better at focusing on progress that matters and can't be faked, and the AI companies will get better at reaching more people.
This kind of work is profoundly unrewarding: hand-holding chronic patients and sorting out medical and personal logistics is no one's calling.
Right now Pair Team has 3 engineering positions (~170K), but 14 for case workers that get to work from home for ~$50K (outside the bay area).
I could see them pivoting to social services, with health care being just one aspect.
(As a reminder, the homeless problem is driven by mental health issues blocking people from adapting economically, for which social services cannot keep up. I'd love to see a program offering free phones for daily AI discussions that surface some cheap partial solutions.)
When you throw such a tool into the existing incentive structure, that already produces inhumane atrocities, i wouldnt be that optimistic.
They’ll just start cherry picking their patients, finding ways to squeeze out the people just that little bit lower on the prognosis curve. Or at least that will be the risk in a setup like that.
The program sounds reasonable until you become aware that the patients most in need are often the ones least likely to improve. It also ignores the reality that sometimes even the most rigorous, well reasoned treatment plans fail for unpredictable reasons. Do you punish providers and patients for that?
If they can cure 80% of the entire caseload with 20% of the total estimated cost of the entire caseload, you'll want to be in that 80%.
Real bummer.
They are absolutely correct about this mathematically, you can’t solve problems you don’t have data for
The question is what organization would I trust with the full context of my life. None. Zero.
**future headline: Consumer warning: The panopticon(tm) product is embedded into your care plan, insurance is only available for panopticon subscribers.
Wouldn't this mean you'd rather interact with an AI, if it meant whatever you said was provably shown that it could never leak (though the medical conclusions would be documented in your HIPAA-protected record)?
But if it’s in someone else’s computer? thats gonna be a no from me dawg.
People don't seem to realize that this is both coming and that before long people will be defending AI "persons" because of this reason (OpenAI is already complaining about people doing this). Nobody's going to deliver this level of care using humans. It's not going to happen.
A lot of people needing care are deeply isolated and will be of the opinion that AI changes that.
First the title: "Medicare's new payment model is built for AI. Most of the tech world has no idea", classic AI tell. The by-line is by the editor-in-chief.
Em-dashes everywhere, including in this quote, somewhat unusually: “The best solution wins, which, in regulated industries like healthcare — that’s not been the case.”
Oddly-short paragraphs: "That payment structure is the real news."
Rule of threes: "Pair Team launched in 2019 with a specific kind of patient in mind: people managing chronic conditions who were also dealing with unstable housing, too little food, or lack of transportation"
This whole paragraph: "There are real risks. Participants are feeding extraordinarily sensitive patient data — intimate conversations about housing and diseases and mental illness — into a federal infrastructure with a documented history of breaches, including exposed Social Security numbers. For the vulnerable populations ACCESS is designed to serve, that's not an impractical concern."
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I haven't opened a TC article in years and I think I'll return to that practice.
I think there's an ongoing conversation about whether we should accept all LLM-generated text without commentary.
I write this comment because I have some sympathy for a Show HN with AI-assisted writing, but I will not spend time enriching TechCrunch's use of machine-generated text anymore than I would scroll through an ad block at the end of any other article.
(Just for the sake of comparison, here's something by the same writer from a few years ago - https://techcrunch.com/2022/11/16/boompop-gains-traction-by-...
You can see more examples here, too https://techcrunch.com/author/connie-loizos/page/16/ )
(There is such a thing as Medicare advantage, where a patient can choose to put their Medicare dollars toward private insurance, but it's not part of the initial launch of this program.)
Any attempt to use LLMs as a substitute for personal interaction is playing an incredibly dangerous game that will probably make them a lot of money, while hurting a lot of people.
Oh and taking sycophancy out of a model is easy. Just finetune out that they (have to) agree with everything. Plus every new model has less of it, or at least masks it better.
One step further would be robots that take people to the bathroom, clean them and other stuff. Having this done by humans is either extremely expensive or it will not be done properly.
Some people are horrified by the loss of human touch but for most old people human touch is a luxury they can't afford.
Look at all the "AI psychosis" problems with people going into a conversation loop that amplifies their worst thought patterns. Now consider the same where the person in this loop is already having delusions and other cognitive decline. It seems to me that it could spiral in the wrong direction quite easily.
It's quite difficult for human caretakers to navigate this space too. That is part of why it is so exhausting. You're constantly trying to make judgement calls and implicitly predict the unreliable response of the dementia sufferer.
I think there is a large uncanny valley between having some facsimile of human interaction in a short session and having some kind of trustworthy caretaker that can consistently respond in a way that promotes health and safety. I think it involves a lot of subjunctive interpretation and reasoning to navigate all the mixed up layers of fact, fantasy, and simply aphasic expression that come from dementia.
That said, Pangram agrees and its track record is pretty good.
I'm not saying the quotes are fake, that would be horrific. I'm saying the rest of the article appears to have had minimal human intervention.
The other uses are honestly pretty standard rhetorical patterns; they do not seem especially AI-flavored to me.
Put another way, search out the great vowel shift. That happened over more time but then again the contact with different speakers wasn’t as constant as every day on the internet. It’s just what happens, how things spread. No different and maybe to a further degree than typical memes.
Coincidentally I just read a blog post today that explained this in a way I always struggled to: https://www.astralcodexten.com/p/nostalgebraists-hydrogen-ju...
And if we're using machines to assess this, the appropriate action is to look at the author's writing from before the time of LLMs and compare it to now.
For hospital stays, I may be outdated in this, but Medicare pays a lump sum DRG which doesn't tend to go up much, so the longer the patient is in the hospital, the less money the hospital makes.
Short story is the biggest pressures from the higher-ups is for us to see more volume outpatient, and cut duration of stays inpatient....
First: of course this is fixable.
Second: As opposed to the damage of no attention at all? Because you act as if the alternative is that a professional therapist will be helping the homeless, walking around in the cold. I've never once seen that happen.
There've been third-party evaluations of Pangram, e.g., https://bfi.uchicago.edu/wp-content/uploads/2025/09/BFI_WP_2.... I personally do not think I could achieve that rate of accuracy, if you made me read a bunch of text samples and guess whether humans or AIs wrote them. Do you think you could?
> Do you think you could?
Not the right question. I am saying that this particular article based on its tendencies and the historical writings of this author are LLM-assisted if not wholly generated.
The author's name in the article is linked to a list of articles attributed to her, and it's easy to advance through the list by editing the URL, like so: [0]. As other commenters point out she's the editor-in-chief so maybe she could put her name on an AI article. But I'm assuming she would not put her name on another human's work.
This lead me to [1], an article from 2018. And when comparing the old article to the OP ... I'm stumped.
They both rely on quotes from a company founder. This is a bit intentional, I wanted to pick similar articles.
They are both somewhat .. dry? They have a sincere tone, devoid of hyperactive meme-speak or jokes (presumably the hyperactivity is reserved for the advertising). The older article has one oddly casual line: "What has changed since then is, well, not much, argues Sims." The newer article has an extremely short paragraph that sticks out visually: "That payment structure is the real news." But otherwise I don't see any super-obvious difference.
They both used em-dashes.
To be honest, I could be convinced that the OP is written by the same human who wrote [1], some humans just write like LLMs after all. My intuition isn't really helping me out here, if I wanted to go further "manually" I'd have to break out Wikipedia's list of AI tells or something like that.
(EDIT: and just to be clear, Pangram also thinks the old article is human-written, which I guess is our control case).
(EDIT: in your earlier comment, you mentioned the rule of three as a sign of AI writing, but it's a pretty common pattern in human writing as well and appears in the older article: "A second offering is Codecademy Pro Intensive, which is designed to immerse learners from six to 10 weeks (depending on the coursework) in either website development, programming or data science.").
[0] https://techcrunch.com/author/connie-loizos/page/45/
[1] https://techcrunch.com/2018/10/04/as-some-pricey-coding-camp...
Do you have any suggestions for identifying AI writing, other than relying on intuition or going through the points of Wikipedia's list [0]?
[0]: https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing
I'm not in a position to evaluate whether they were right, but you've presented this as if it proves them wrong when it's barely related to what they said.