Comment by somenameforme | Hacker News Reader

Comment by somenameforme | Hacker News Reader

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Again, feel free to provide data instead of lighting strawmen alight. In general you are already speaking of things that are primarily relevant for people critically ill in senescence, which is both a fringe scenario and also (I think obviously) not the general case sort of scenario I'm speaking of. But even there! Out of curiosity, I decided to look up data on e.g. sepsis readmission rates vs hospital quality. [1]

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"One third of sepsis survivors were readmitted and wide variation exists between hospitals. Several demographic and structural factors are associated with this variation. Measures of higher quality in-hospital care were correlated with higher readmission rates. Several potential explanations are possible including poor risk standardization, more research is needed."

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As they're implying, this is likely due to biasing and not a causal observation. One possible explanation is that higher quality hospitals may be able to keep people knocking on deaths door a bit longer than lower quality hospitals, but it's not like night and day - they're still knocking on that door, just a bit longer. And so it makes sense that they'd actually have worse outcomes on discharge, including higher overall readmission rates. But once again the picture between the quality of hospitals is not this tremendous dichotomy that many try to frame it as.

Billionaires, in general, seek out the highest quality care money can buy, and have no limitations on the meta-factors that also improve longevity including activity, relationships, healthy food, exercise, etc. Yet their life expectancy (~85) is comparable to the life expectancy of Hispanics in America. The "Hispanic Paradox" [2] again emphasizes that longevity isn't about premium healthcare and money.

[1] - https://journals.lww.com/ccmjournal/abstract/2017/07000/seps...

[2] - https://en.wikipedia.org/wiki/Hispanic_paradox

https://pubmed.ncbi.nlm.nih.gov/28060228/

MI, HF, sepsis, pneumonia, respiratory failure are among the most common reasons for inpatient admission, not fringe.

Equating acute decompensation of chronic illnesses requiring inpatient admission to "knocking on death's door" is a bit simplistic.

No data has been provided showing how the relevance of outcomes based on institution of first presentation (not definitive management) for breast cancer, that is usually managed outpatient on an elective basis, has anything to do with outcomes for the "overwhelming majority of things people to go to the hospital for".

Even pre-pandemic the life expectancy of Hispanics was not as high as billionaires. Speaking of "deaths door" perhaps at least QALY, or something else is a more appropriate metric.

Cheers on the study!

Let me first describe what I meant by fringe though. Take a random adult going to the hospital, not elderly, with no other major health conditions. When he walks in the door, what are the distributions of issues that he might end up having? Sepsis is going to have a probability of near 0. By contrast the typical patient that might present with sepsis - elderly, other major health conditions, well into senescence - he is generally indeed 'knocking on deaths door.' He might not answer this time (though there's a decent chance he will!), but he will imminently.

Your study compared hospitals based on a number of factors. The most significant was high volume, but in that case the difference between the highest volume hospitals and lowest was a 13.3% rate of readmission vs a 11.2% rate of readmission for hip replacement, and 12.4% vs 11% for knee replacement. Again I think this is another example of when you look at the actual data, outcomes fall quite close.

Beware their method of taking a sampling and breaking it into buckets and comparing those buckets. If even hospitals/patients were identical (which I'm certainly not claiming) and so the results were literally just random noise on a distribution, you'd see a major difference between the top and bottom buckets due to the nature of random distributions - 68-95-99.7 and all that. Their results show a signal beyond that, but it's generally a very misleading way of presenting data because of this issue.

Pre-pandemic hispanics had a life expectancy of about 82, which I described as comparable to the 85 of billionaires. I'd certainly expect billionaires to be higher for the endless reasons outlined in the already linked Hispanic paradox. The fact that it's only 3 years, less than 4% longer, is the point.

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