Let me first reiterate that I’m not interested in defending the United States’ current private health care system per se. Ideally, I think we should like to put aside any idealogical predispositions and let the empirical evidence guide us. The problem, of course, is that the empirical findings are far from clear.

While I don’t know the numbers myself, I’ll take your word that the U.S. spends twice much as France on healthcare but has comparable outcomes. Unfortunately, we can’t draw the conclusions we’d like to draw from that, either. Take, for example, an interesting paper I saw a while back: Bo E. Honore and Adriana Lleras-Muney, “Bounds on Competing Risk Models and the War on Cancer” <http://www.princeton.edu/~honore/papers/comp_risk.pdf. The paper notes a similarly simplistic argument alleging that cancer research has been ineffective: Nixon declared the “War on Cancer” 35 years ago, and since then we’ve invested incredibly sums in cancer treatment and research, yet the mortality rate from cancer now is largely the same as it was in 1970. The paper argues that what really happened is that we became much more successful at treating cardiovascular disease, and as a result many of the people who previously would have died of cardiovascular disease now die from cancer instead. It alleges that we have gotten significantly better at fighting cancer, but this effect is being obscured in the data by an increase in sickly people dying of cancer rather than cadiovascular disease. The paper then goes on to try and demonstrate this empirically with some rather fancy econometrics that I’ll admit are over my head, but I’ll trust the authors, who are talented econometricians.

I suppose that the conclusion to reach from this example is the same as one from my previous comment: we can’t use outcomes to compare the relative efficiency of different health care systems unless we know that the prior health profile of their respective populations are roughly similar. Recall that high infant mortality rates in the U.S. might be due to its higher incidence of low-birth-weight infants, rather than – or perhaps in spite of – any differences in quality of care. Because we wouldn’t seem to be justified in assuming that the French and American populations are equally healthy to begin with, I’m doubtful that we can draw any conclusions from the comparison here.

I hope this doesn’t lead us to a sort of empirical nihilism, but at the moment I’m afraid that there is precious little empirical data to go on.

Let me first reiterate that I’m not interested in defending the United States’ current private health care system per se. Ideally, I think we should like to put aside any idealogical predispositions and let the empirical evidence guide us. The problem, of course, is that the empirical findings are far from clear.

While I don’t know the numbers myself, I’ll take your word that the U.S. spends twice much as France on healthcare but has comparable outcomes. Unfortunately, we can’t draw the conclusions we’d like to draw from that, either. Take, for example, an interesting paper I saw a while back: Bo E. Honore and Adriana Lleras-Muney, “Bounds on Competing Risk Models and the War on Cancer” <http://www.princeton.edu/~honore/papers/comp_risk.pdf. The paper notes a similarly simplistic argument alleging that cancer research has been ineffective: Nixon declared the “War on Cancer” 35 years ago, and since then we’ve invested incredibly sums in cancer treatment and research, yet the mortality rate from cancer now is largely the same as it was in 1970. The paper argues that what really happened is that we became much more successful at treating cardiovascular disease, and as a result many of the people who previously would have died of cardiovascular disease now die from cancer instead. It alleges that we have gotten significantly better at fighting cancer, but this effect is being obscured in the data by an increase in sickly people dying of cancer rather than cadiovascular disease. The paper then goes on to try and demonstrate this empirically with some rather fancy econometrics that I’ll admit are over my head, but I’ll trust the authors, who are talented econometricians.

I suppose that the conclusion to reach from this example is the same as one from my previous comment: we can’t use outcomes to compare the relative efficiency of different health care systems unless we know that the prior health profile of their respective populations are roughly similar. Recall that high infant mortality rates in the U.S. might be due to its higher incidence of low-birth-weight infants, rather than – or perhaps in spite of – any differences in quality of care. Because we wouldn’t seem to be justified in assuming that the French and American populations are equally healthy to begin with, I’m doubtful that we can draw any conclusions from the comparison here.

I hope this doesn’t lead us to a sort of empirical nihilism, but at the moment I’m afraid that there is precious little empirical data to go on.

And a predictable review it is; endless pontifications interspersed with the occasional mention of the books they are supposed to be reviewing. The reference to any dollar not subject to a tax as “subsidized” is our assurance that, indeed, Paul Krugman was here. Anyway, this quote is a classic Krugman:

“Yet another problem with consumer-directed care is that the evidence says that people don’t, in fact, make wise decisions when paying for medical care out of pocket. A classic study by the Rand Corporation found that when people pay medical expenses themselves rather than relying on insurance, they do cut back on their consumption of health care—but that they cut back on valuable as well as questionable medical procedures, showing no ability to set sensible priorities.”

In one fell swoop, we learn that we are too stupid to manage our money or our health. One suspects Mr. Krugman feels this way because we were too stupid to follow his advice the last two presidential elections. The two back up this we’re-too-stupid assertion with a reference to a “classic study by the Rand Corporation”. Unless thee is another classic out there, I believe he is referring to a 1992 report which was based on a study undertaken in response to a Nixon administration request. The study encompassed some 5,800 people and was concluded by 1981. The better health care results from “free” care was limited to blood pressure control, corrected vision and oral health. But interestingly, it also found that certain helth habits – including diet, exercise and smoking – were worse among those provided with free health care.

So the duo of Krugman & Wells advise: “it would be politically smarter as well as economically superior to go for broke: to propose a straightforward single-payer system, and try to sell voters on the huge advantages such a system would bring.”

You would think that even more recent empirical evidence (Hillary’s Health Plan) might counter the “politically smarter” conclusion but maybe they think the “huge” advantages outweigh all the negatives – you know, the efficiencies that other federal agencies bring to the programs they manage – places like HUD and the Department of Education.

I imagine that, along the lines of your comment, you might join the public health crowd and point out that there are many, many more determinants of health than health care expenditures. Inequality of income, for example, is key, as Wilkerson and the Whitehall studies have shown.

But it’s a bit ironic to use that body of data to cloud our assessment of the current crisis. I’ll close this reply with an account of epidemiologist Nancy Krieger’s work (URL source below). In 1994, Krieger wrote “Epidemiology and the Web of Causation: Has Anyone Seen the Spider?”, and a reporter offers this summary:

“Drawing deeply on history and philosophy, the article in Social Science and Medicine dismantles the central tenet of modern epidemiology: the belief that population patterns of health and disease spring from a complex (and rather gauzy) “web” of risk and protective factors. Krieger suggests the web approach is both short-sighted and cowardly because it focuses on individuals and ignores how and why diseases vary and shift across populations and over time. It looks at lots of narrow mechanisms and not at the overarching forces that set those mechanisms into play.

Instead, she asks, “Who or what is the ‘spider?’” What societal forces create the risk factors that eventually sift down to the organs and cells and DNA in our bodies? And how are those forces sowing disease across populations?”

from:

http://www.harvardmagazine.com/on-line/030636.html

Eberstat points to two problems with simply comparing infant mortality rates for America with other countries:

(1) The U.S. uses a much wider measure of infant deaths than other countries, which generally don’t count infants with extraordinarily low birth rates and had little chance of survival after birth. In Switzerland, an infant that is less than 30 cm long (which includes virtually all infants weighing less than 1 kg) at birth isn’t counted as “living,” so its “death” is not recorded in the infant mortality numbers. Italy has similar reporting procedures, and data from France, Sweden, Japan, and Hong Kong suggest they have a similar practice (though unofficially). Compare this to the rigorous reporting procedures in the U.S. and their impact on the numbers: “In 1988, for example, U.S. vital statistics registered almost 24,000 infants weighing less than one kilogram (about 2.2 pounds). Survival rates for this high-risk cohort are extremely low. Though the group accounted for just over one-half of one percent of that year’s registered births, it accounted for over a third of registered infant deaths in 1986.”

(2) Even when we exclude infants with extraordinarily low birth rates, the distribution of birth weights in the U.S. is far, far lower than in other countries, and birth weight is perhaps the most important factor for infant viability. If you group the infants by birth weight and then compare mortality rates within those group, you find that infant mortality rates in the U.S. are actually far better than in many other counties: “If Japanese babies had enjoyed U.S. birth-weight-specific survival odds, their perinatal-mortality rate would have been cut by over a third. This fact is all the more striking because Japan already reports virtually the lowest perinatal-mortality rates in the world.” It’s not clear why birth rates in the U.S. tend to be so low. One possibility is that pregnant women are doing a poor job of caring for their well-being, result in unhealthy infants: the U.S. has a very high rate of unwanted children, of pregnancies in poverty, and of pregnant women who smoke. Another possibility is that the high infant mortality numbers may ironically come from superior pre-natal care, allowing low-birth-weight infants to come to term when they might not have survived to birth elsewhere.

I’m not trying to express support for the status quo, which has all kinds of problems. But health care economics is a remarkably complicated field (especially in the U.S., thanks to some political and historical quirks), and you have to be very careful when looking at these numbers to be sure that you’re actually measuring what you want to be measuring.