The analysis finds that the U.S. spends more than all other countries on health care, but this higher spending cannot be attributed to higher income, an aging population,
or greater supply or utilization of hospitals and doctors. Instead, it is more likely that higher spending is largely due to higher prices and perhaps more readily
accessible technology and greater obesity.
My problem with these sorts of analyses is that these sorts of indicators do not themselves account for enough NHE directly or correlate with NHE well enough to claim to account meaningfully for utilization and other major non-price drivers of NHE (if you wish to remove quantities of technology, prescription medicines, etc from “utilization” for semantic reasons). When (1) your utilization measures can only account for maybe 10-15% of the variance (2) only relates to a modest proportion of NHE in most developed countries and (3) one ought to know there are other major cost drivers to account for, it’s pretty silly to claim that your half-hearted attempt to explain the variance honestly means it cannot be utilization and that it must be (mostly) the result of some US specific prices.
My intuition and knowledge of the health care industry has long led me believe this likely not too dissimilar from what goes on in other developed countries (the young and/or reasonably healthy simply do not need or want much in the way of health care). If nothing else it seems unreasonable to use this data to argue the US is an outlier without at least going through the exercise of comparing it to other countries. Unfortunately the OECD and related entities provide little in the way of public data along these lines, so I have not been able to do this analysis myself.
However, I recently stumbled across a blog post from IFS regarding a study they published that speaks directly to these and related topics, so I thought I would briefly share this and related information in a quick-and-dirty blog post (full-text copy here).
However, because some people are inherently suspicious of consumption per se and because others are under the impression this is primarily about financing (health) consumption out of savings/debt, I think it useful to also demonstrate these patterns as it relates to householddisposable income (tl;dr they’re very well correlated and produce very similar results in the long term)
In my prior few posts I made a strong case that the United States’ exceptionally high health care expenditures are well explained by its unusually high material standard of living. In response to this several people I have interacted with have fallen back to the position that something still must obviously be uniquely wrong with the US health care system because US outcomes are significantly below what one might expect given its level of spending:
They believe it cannot be a coincidence that the country that spends so much more than expected (according to naive expectations) also gets worse outcomes than expected and generally gets worse outcomes than the most developed countries of predominantly European and Asian origin.
In this blog post I will address the so-called “outcomes” dimension and explain why these apparently sub-par outcomes are not only not otherwise inexplicable, but can actually be explained in a fairly straight forward and parsimonious fashion For the moment, I will narrow my focus on the subset of factors that drive US health outcomes significantly below naive expectations (not necessarily the full residual) and that I have good reason to suspect are significantly causally related to the expenditures issue. Later, perhaps in another lengthy blog post, I will address other factors that are mostly orthogonal to expenditures and that further affect US health outcomes.
In my prior post, wherein I argued at length that US health care expenditures are reasonably well explained by Actual Individual Consumption (AIC) and that GDP is an inferior predictor, I pointed out toward the end that the linear specification I used is likely to significantly overstate US residuals because there is good evidence for non-linearity and because the US is far out on the frontier vis-a-vis consumption.
This non-linearity can be seen pretty clearly if you look at the 2011 data derived from the World Bank (for AIC) and WHO (for HCE).
Since some people may (1) doubt the accuracy of these statistics outside of the few highly developed countries (2) imagine that these poor countries are somehow qualitatively different in a way that’s not well correlated with their level of economic development or (3) are particularly reluctant to accept non-linearity as a potential partial explanation for the US here, I thought I’d approach this from a somewhat different angle.
About two years ago I created a long blog post arguing that the United States is not an outlier in healthcare expenditures per capita. Following renewed interest from a link from Marginal Revolution recently and some criticism from a few people on various comment threads, I thought I’d take the time to update the evidence, address some areas of criticism, and muster yet more lines of evidence to support my argument. This post should largely make the earlier post obsolete, but I will keep the earlier post up for posterity and to retain data/information that won’t necessarily be perfectly duplicated in this post.
There exist several popular plots like these that people use to make the argument that the United States spends vastly more than it should for its level of wealth.
These plots and the arguments that usually go with them give the strong impression that US spends about twice as much as it should. However, these are misleading for several reasons, namely:
GDP is a substantially weaker proxy for “wealth” and a substantially weaker predictor of health care expenditures than other available measures.
The US is much wealthier than other countries in these plots in reality.
The arbitrary selection of a handful of countries tends to hide the problems with GDP in this context and, oddly enough, simultaneously downplay the strength of the relationship between wealth and health care spending
Comparing these two quantities with a linear scale tends to substantially overstate the apparent magnitude of the residuals from trend amongst the richer economies when what we’re implicitly concerned with is the percentage spent on healthcare.
When properly analyzed with better data and closer attention to detail, it becomes quite clear that US healthcare spending is not astronomically high for a country of its wealth. Below I will layout these arguments in much greater detail and provide data, plots, and some statistical analysis to prove my point.
Besides my previously mentioned objections with simplistic comparisons between healthcare systems, vis-a-vis naive economic comparisons and the effect of taxation on behaviors, it is very difficult to compare the actual performance of healthcare systems, in both financial and human terms (e.g., life expectancy, mortality rates, etc), without accounting for other differences in the populations (e.g., genetics, health/risk behaviors, lifestyle, etc). These simplistic comparisons of national health care systems based on crude mortality rates and the like are very much like comparing performance of goalies in various sports based on who wins the game alone, i.e., without making any real attempt to control for the performance of the rest of the teams’ defense, the performance of the offense, and so on, when what we really want to know, at bare minimum, is the number of saves as compared the number of shots on goal (and even then that’s an imperfect metric). Of course some goalies are likely to be somewhat more effective than others and, other things equal, goalies can have a pronounced impact on the outcomes, but you cannot simply assume that there are not any significant systematic differences between teams in general or on game day.
These are just a few relevant differences I can think of off the top of my head:
The United States population is not a mirror image of Europe: genetically, culturally, or otherwise
Much higher smoking rates historically
Relatively high rates of obesity (although other countries are starting to catch up to us now)
Much higher homicide rate.
Higher rates of sexually transmitted diseases (see the AIDS crisis)
More geographically distributed than most (as in, lower population density, significant populations living in rural locations, etc)
Higher rates of serious automobile accidents per capita
Here are some examples graphs used to make this point
These appear to be very convincing at first blush, but i never found these arguments particularly convincing due primarily to:
Imperfect comparability between the selected countries
Issues relating to comparing countries of the “same” GDP
cherry-picking of countries
I knew the proponents of single-payer were, at best, making an incomplete argument and that it invited an exaggerated impression of what we should likely expect from a country like ours, but, up until now, I lacked the data and the time to present these argument comprehensively. I recently got in an argument with someone over this subject and found a treasure trove of data all in one place (mostly) to thoroughly debunk this overly simplistic argument.
To make my points, vis-a-vis fundamental issues with naive treatment of GDP per capita and sensitivity to comparison countries, here is a quick chart showing National Healthcare Expenditure (NHE) as a percent of GDP by GDP per capita
One of the issues that I have when people assert that United States physician compensation is much higher than other countries is that they make terribly naive comparison. They compare, say, PPP-adjusted incomes to PPP-adjusted incomes in other countries without accounting for the fact that the “average” person in this country has a much higher PPP-adjusted income by most measures. Likewise, they’ll compare physician income to “average income” or “average wage” ratios without comparing it to the more relevant labor pool in each country, i.e., at least college graduates (or better). example
Average Physician Gross Income to Average College Grad Gross Income [apples-to-apples]
Note: In both cases, “gross” is pre-tax income, including social security/payroll contributions.