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So this guy had a few twitter exchanges with Luigi and he thinks the US healthcare system isn't that bad? Doesn't really seem like an article for HN. But as long as we're here I think, sort of like Luigi, I'll let other people argue about whether the US healthcare system functions well or efficiently. But as for this:

>While it’s true that UnitedHealthcare has the highest denial rate for medical claims, the CEO doesn’t set the approval rate of a health insurance company’s payouts — that’s done by the actuaries, who themselves are constrained by various considerations, such as the need to keep costs low, including for policyholders.

By this logic, what can Brian Thompson be said to be responsible for? It's very strange to me to assign more responsibility for a companies denial rates to its actuaries than the actuaries' bosses bosses boss. So why exactly does UHC have higher denial rates than other companies? It just happens to be that it's actuaries are more frugal? This explanation doesn't hold water and I think it's a strange response to the shooting of a CEO to say, well actually CEOs aren't responsible for the things their corporations do. Of course they are, now they aren't solely responsible, but they probably have more responsibility than any other single individual. It can be completely true that killing Brian Thompson was wrong AND that he was no saint, being responsible for (and getting rich off of) large amounts of human misery inflicted on UHC policy holders by the organization he headed.


One of the author's points was that if United took no profit, it could only very slightly increase services. The only ethical thing that Thompson could have done is advocated for the dissolution of his and his competitors' firms, which would have had him out of a job quickly.

The actual problem is the system where United exists at all. Health insurance provides exceedingly little value for a very high cost.

One issue now is that being in the way of healthcare is now so large as to have its own gravity. Just healthcare administration (no caregiving or treatment) is now about 2% of GDP itself. Restructuring healthcare would mean tens of thousands out of a job.


No, you've misapprehended the critique; in fact, your comment here isn't even coherent. If you eliminate United altogether, you get a grocery store circular discount on health care; in other words: health care is still altogether too expensive. So the "actual problem" can't be the system supporting health insurance; the problem has to be elsewhere.

It's not hard to see where it is! Go look up the 2022 NHE, which includes a giant spreadsheet breaking down where all the spending is in the system (you want the "by type and program" sheet).


This comment is a riddle. Say it plainly.


"Insurers are clearly not the problem with our health care system, as you can plainly see from the NHE."


Like this one?:

https://www.macpac.gov/publication/national-health-expenditu...

Looked at the table and could not plainly see the problem. Would imagine that time series presented like with an analog of Tim Morgan's Energy cost of Energy for energy markets might help..


> The only ethical thing that Thompson could have done is advocated for the dissolution of his and his competitors' firms, which would have had him out of a job quickly.

Since UHC is a publicly traded company, this action would actually be illegal sice teh CEO's job is to protect the shareholder.

I can image many people here have stock in these companies. So, tell me who is responsible? There is greed everywhere you look if you are honest with yourself.


So a fraction of the number of tech employees out of a job in the last couple years due to interest rate increases and AI panic?

What’s the problem, again?


IT unemployment is currently under 4% because the folks that got laid off found new jobs. If you eliminate an entire industry, the unemployed will have a tougher time finding a new job.

The dislocation would be far larger than the tech layoff.


Regarding this part:

Clarification of specialty role

  - Less strict on the direct link between degree/job responsibilities

  - Recognizes that AI may require multiple academic background
You really won't need to clarify whether the role is a specialty one or not if you just increase the minimum wage for H1Bs. I really don't know why we don't have some rule that pins H1B wages to like the 90th percentile wage.


It would be exceptionally easy to solve the "H1B problem" by making sure that H1Bs are more expensive than local talent; then they really only would be used when local talent doesn't exist.


10 people died from the Boars Head contaminated meat. I guess I don't really mind if a few lawyers chase those ambulances and extract a lot of money out of that company?


A) It's not going to stop at the most egregious cases

B) I hope you like meat imported from China


I thought the issue was deregulation? Something like Trump rolled back some rules about oversight and then Biden never put them back into place? Does the USDA even have the power to fix this?

Anyways, having a pregnant wife right now, it's worrying that listeria is on the rise. We're already avoiding stuff like deli meat but when there's listeria in the frozen waffles, mushrooms, and vegetables you have to wonder what's really going on.


The USDA created the problem through regulating industry consolidation. The 'fix' is to reconfigure the economy to price in unpriced negative externalities and create sustainable industries. This of course won't happen.


I’m struggling to understand what you are advocating for in practice.

What was such a reconfiguration of the economy actually mean in real terms?


Ideally it would be possible to calculate the economic 2nd and 3rd order effects of commercial activity in order to price in externalities.

In practice the example I like to use is soil loss. Farming isn't sustainable because the soil literally blows and washes away and cannot be regenerated. The solution is to have forest patches to reduce the wind speed and marshes to hold the rain. All of this takes valuable land which cannot be used 'productively' but is vital to make agriculture sustainable.


It’s lucky when you can get the sign right on the first-order effects. Predicting 2nd order effects accurately enough to price them is economic voodoo.


Most 'economists' are not scientists and simply mash things together to justify whatever has already been decided.


He's pointing out that meat packing consolidated into a cartel (Tyson, JBS, Smithfield and Cargill), which has enough economic power to ignore or alter regulation. The solution is antitrust - break corporate power into small enough pieces that they don't have the resources to escape regulatory oversight.


That's absolutely part of it. Animals that are kept close together in cages and barns instead of roaming get sick and spread sickness far more quickly as well. We've created a million dangerous biolabs for diseases with biosimilarity to us.


Its basically arguing that meat needs to have more expensive production processes for better safety.


Simply reconfigure the economy, while it would be nice, is always harder to implement.


Yes and: IIRC, USDA lost their roster of experienced food inspectors (et al) when their headquarters moved from Metro DC to Kansas City. Below are the top hits via perplexity.

FWIW, While I'm generally in favor of (geographical) decentralization, I'm against abrupt changes to essential services. Obviously, a nice orderly transition would have been better. Plenty of staff, esp youngsters wanting a house and family, would relocate over time.

---

https://www.npr.org/2021/02/02/963207129/usda-research-agenc...

https://www.govexec.com/oversight/2023/01/although-usda-agen...

https://www.gao.gov/products/gao-23-104709


If you're the only one that can come close. Kaggle competition prizes are about focusing smart people on the same problem. But it's very rare for one team to blow all the others out of the water. So if you wanted to make a business out of the problem kaggle will (probably) show the best you could do and still have no moat.


>characteristic of these use cases is that there is no one right answer

I think what you mean is that they work best in cases where it's very hard to measure how well they are working.


And where it's also hard to tell who is doing the work! I'm reminded here of psychics and cold readers. They can easily convince people that they have great mental powers by outputting ambiguous text and letting the consumers of it do most of the work. You'll see similar effects with Meyers Briggs tests and other sorts of business astrology: some people feel like they get a lot of value out of them, but rigorous tests don't back that up.


Yeah but what made Twitter twitter wasn't really the usercount, it was the mix of established voices and complete randos mixing. If the journalists and economists and politicians go to Bluesky, it will win. I definitely don't think that's a given but it seems much more plausible now than it did a few months ago.


Bluesky is increasingly getting that way. Every time I check it this week I'm seeing new content from recognizable people. I think at some point there will be a tipping point where Bluesky will have more content and just win outside of alt right circles.


Until they start censoring. Some orgs (like Guardian,) don’t like getting fact checked in real time. Old Twitter is far worse than new Twitter. In the recent old days, you’d get suspended for even debating Covid vaccine safety. Couldn’t even debate it! They even colluded with the U.S. government to silence dissent. Crazy.


You are correct, that was a disgraceful thing for thing for the Trump 1.0 administration to do.


Kim Kardashian is much more important to a social network than any journalist, politician or economist. Perhaps more so than all of them combined.

There are many interest verticals on Twitter like politics, sports, celebrity, influencer, porn etc.


I mean what if it is a toss up? Were we talking about a literal, actual coin flipping, calling it as 50-50 is a better insight than calling it as either heads or tails.


I like the dashboarding more than the analysis lol. I think FL is just a red state now and positing it as anything else smells a little fishy to me. Also, I think there's a thing now where all sorts of analysts know they can get a name out of making one big correct prediction that everyone else got wrong. That's lead to a lot of predictions being made with the intention of being contrarian.


Judging by my twitter feed, some scientists are starting to push back on the use of UMAP (and t-SNE.)


I think a common problem is that these techniques get repurposed to solve problems that they weren't meant to. I have seen multiple people fall too often into the trap of using these visualizations to guess whether a dataset may be classified with high accuracy. I'm talking about cases where there already is a label - but viz. is used as a prior compute-cheap step to understand whether they would bother with classification at all, or should they pick a weak-vs-strong classifier, etc.

The problem of course is the insights from viz. provide "one-sided" information: IF your instances from different classes look separated, then you know that a decent classifier would do the job well. But if they don't appear separated, you don't know whether they can't be accurately classified: for all you know you don't have the right hyperparams. Also account for the fact that you're projecting d-dimensional data down to 2D/3D - this is heavily lossy; even with the right hyperparams there is a chance you won't see high separation. If you want to classify, just classify.


What do they suggest you use instead?


PCA for starting out


As a sibling comment already mentioned that doesn't really work for non-linear data. UMAP and t-SNE are techniques used on non-linear data.


PCA performs horribly on non-linear data.


How will you know if you have non-linear data....


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