An anonymous author analyzes US health care costs, crime, and school funding with data and charts, often disputing conventional views.
Commenters cite it as an excellent, well-sourced analysis, especially the piece on racial differences in homicide rates, and it comes up in US health care cost debates.
> This argument uses average income as proxy for what health care spending in the US should be.
> That seems clearly wrong given that with US now having a GINI coefficient, high level of income inequality, median household income would be a better thing to measure health care spending, since every individual has to spend money on staying healthy.
The author responds to that criticism in the following comment[1]:
>> Two, I don’t understand why you’re using mean rather than median AIC throughout.
> Several reasons.
> 1) We don’t have good internationally comparable statistics for income or consumption at various points in the distribution...
> 2) When I’ve looked into this I have not found measured differences in the distribution or the median to be particularly informative...
> 3) This makes sense because there is approximately no relationship between individual income and health spending in the developed world, including the United States...
As for your second argument:
> The argument generally seems wrong too. The need for health care isn't elastic - if someone need care, they need care and people going without needed health care is a humanitarian crisis (a situation that the US is arguable in - see the people giving free dental in a stadium a few years back).
I'm not sure I follow your argument. RCA is saying that, as a country, the U.S. spends more on healthcare because we consume more health care than other countries. The U.K. kept their prices low for a long…
> Really? That is news to me, as a dual US|EU (Croatian) citizen, who is culturally American--but currently living in Croatia.
Yes, and just like that health policy analyst, I can attest to it. I've read more than enough plan documents, and work with health actuaries every day.
> Also, just in case you want to blame this on "lifestyle factors" (which means that this is a public health matter, which the United States has severely underfunded--locally, state, and nationally for more than a few decades now), the third leading cause of death is believed to be preventable medical errors. (The source I provide has been verified by several follow-up studies.)
Actually, there's a fantastic analysis that addresses this point head on, even analyzing the IHME data: https://randomcriticalanalysis.com/2017/05/16/the-explanatory-power-of-drugs-car-accidents-and-homicides-on-us-life-expectancy-gaps/
The vast majority of the variance in average life expectancy is attributable to lifestyle factors. As long as you stay away from drugs, you don't participate in a gang, or you take the bus (or any public transit), you're on roughly equal footing with the rest of the OECD.
"The data suggests motor vehicle accidents, homicides, and drug overdose deaths can explain a large fraction of the US life expectancy gap as compared to several highly developed countries. Obviously this does not account for obesity, diabetes, (historical) smoking, and related lifestyle differences that are likely to…
> Your findings are not mutually exclusive with other theories about the underlying causes of high U.S. healthcare expenditure, such as a chronic lack of price transparency.
My findings strongly agitate against the notion that high US health spending is a product of idiosyncratic features of our system. Presumably most of these critics believe we'd spend much less if only our system looked more like other countries, but my evidence indicates we'd spend very similar amounts in the long run regardless. Further, we'd likely have similar outcomes and many other similar healthcare attributes (prices, intensity, health worker density, etc). Most of the things about US healthcare people believe to be important and unique (i.e., not explained by income) just aren't.
> The more money is in the pot, the greater the incentives to pilfer it, and, in lieu of adequate controls, the more it will be pilfered
I wouldn't argue there's no "pilfering" or that more money doesn't create more opportunity for this, but the high income elasticity likely has little to do with pilfering. Where are these ill-gotten gains going? I certainly don't think you'd have much success in showing this if you look at, say, the growth in physician incomes, pharma/biotech industry profits, and so on. The data are much more consistent with mundane explanations like rising technological sophistication, higher intensity, and so on (ultimately much of this being driven by some combination of patient/family…
I was only talking about the US. I am not familiar with European problems, my outside view is if Europe were more like the US perhaps it wouldn't be poor compared to the US, but I don't know for sure.
In the US, you gave me a short term data and I just gave you a longer term view than gives a fuller picture, as you've tried to discount my taxes data before (even though that data included relevant tax reform years).
Moreover I gave you BLS consumption data. Spending on housing went from 29 to 32% from 1960 to 2000, with no obvious changes in trend. While the median house is 1.5-2x big and quality and safety regulations became more strict. Oh and household sizes decreased iirc. Housing may be becoming less accessible since covid, sure. Any 1980ies welfare state etc changes don't have much to do with that.
Then, Detroit in fact has a massive number of abandoned houses, so yes prices did effectively go to zero. Presumably if they could be sold to anyone they would be, but they are not worth owning https://detroitmi.gov/news/deputy-mayor-detroit-land-bank-authority-community-celebrate-impact-more-12000-completed-vacant-home
Thanks for providing me with this great argument for supply and demand, I will use it in future ;)
"Market gud, democracy bad and I am very smart”, I see"
Vibes, vibes. There's tons of data on this, from micro data to between city comparison. There's even more data on costs, delays and cancellations for larger projects due to reviews and lawsuits.…
>That isn't a thing. You can argue this specification minimizes the residuals at the high end if you want,
No, but yes.
>> So if you have data about healthcare prices not being out of order, that seems a lot more relevant
> https://randomcriticalanalysis.com/2018/01/06/its-not-the-pr...
> It is the consensus view amongst researchers that have published long-run analyses:
>https://www.cms.gov/research-statistics-data-and-systems/statistics-trends-and-reports/nationalhealthexpenddata/downloads/tech_2000_0810.pdf
So I think it's interesting here that you make no mention of the explanation for HCE increases provided in the "consensus view" link.
>In health care research, the impact of medical technology on health care cost increases has always been a great unknown. Yet 81 percent of the leading health economists agreed with the statement, “The primary reason for the increase in the health sector’s share of GDP over the past 30 years is technological change in medicine”.1Growing attention to the role of technological change in driving growth in health spending, and to the costs and benefits associated with new medical innovation reflects an acknowledgement of the long-term dilemma posed by historically unsustainable rates of growth in medical costs, combined with an increasing consensus that technological advance is a major factor in driving this growth. The current acceleration in health spending growth - following the quiescent period accompanying the spread of…
The title doesn't make it at all obvious what or who this is about. It appears to be a followup to https://randomcriticalanalysis.com/why-conventional-wisdom-on-health-care-is-wrong-a-primer/ , recently posted at https://news.ycombinator.com/item?id=41870858 (and also several other times since the original publication, but this is the first time it got traction on HN).
The thing that isn't clear to me in the author's model is why it should make sense to see this kind of power-law result (it obviously cannot extend indefinitely, since at some level of income, health care spending would be predicted to exceed 100% of income). This should be at least as much of a problem as the "poor countries are predicted to have negative health care expenditure" problem that the author points out with linear models.
(If we're concerned with out-of-sample data in judging the soundness of a model, then presumably we should also be concerned with these sorts of hypotheticals. The author does seem to note the concern, but IMO dismisses it too readily.)
A more intuitive model, IMO, would be a fixed percentage of income in excess of some threshold - but this is also problematic in that our "threshold" for covering basic needs is apparently highly variable (given how poor some countries are compared to the US).