www.cato-unbound.org/2007/09/10/robin-hanson/cut-medicine-in-half
Robin Hanson Lead Essay September 10th, 2007 Car inspections and repairs take a small fraction of our total spending on cars, gas, roads, and parking. But imagine that we were so terrified of accidents due to faulty cars that we spent most of our automotive budget having our cars inspected and adjusted every week by PhD car experts. Obsessed by the fear of not finding a defect that might cause an accident, imagine we made sure inspections were heavily regulated and subsidized by government. To feed this obsession, imagine we skimped on spending to make safer roads, cars, and driving patterns, and our constant disassembling and reassembling of cars introduced nearly as many defects as it eliminated. Our public today is like a king of old whose military advisors spent most of their time and budget reading omens and making sacrifices, to gain the gods' favor, instead of hiring soldiers and talking battle strategy. These advisors knew omens and sacrifices mattered little, but they saw the king was comforted, and feared losing favor by talking of battle strategy. A truly loyal advisor would have told the king what he did not want to hear: "You are obsessing about the wrong thing." King Solomon famously threatened to cut a disputed baby in half, to expose the fake mother who would permit such a thing. The debate over medicine today is like that baby, but with disputants who won't fall for Solomon's trick. The left says markets won't ensure everyone gets enough of the precious medical baby. The right says governments produce a much inferior baby. I say: cut the baby in half, dollar-wise, and throw half away! Our "precious" medical baby is in fact a vast monster filling our great temple, whose feeding starves our people and future. Then let me speak plainly: our main problem in health policy is a huge overemphasis on medicine. The US spends one sixth of national income on medicine, more than on all manufacturing. But health policy experts know that we see at best only weak aggregate relations between health and medicine, in contrast to apparently strong aggregate relations between health and many other factors, such as exercise, diet, sleep, smoking, pollution, climate, and social status. Cutting half of medical spending would seem to cost little in health, and yet would free up vast resources for other health and utility gains. To their shame, health experts have not said this loudly and clearly enough. Non-health-policy experts are probably shocked to hear my claims. Most students in my eight years of teaching health economics have simply not believed me, even after a semester of reviewing the evidence. Heroic medicine is just too central to our culture, a culture where economists like me have far less authority than doctors. Worse, even most standard textbooks in health economics fail to make the point clearly. Children are told that medicine is the reason we live longer than our ancestors, and our media tell us constantly of promising medical advances. Millions of doctors are well aware that most medical journal articles describe gains from particular medical treatments, and these doctors usually give patients optimistic views about particular treatments. In contrast, few doctors know that historians think medicine has played at best a minor role in our increased lifespans over the centuries. And only a few health policy experts now know about the dozens of studies of the aggregate health effects of medicine. Worse, these studies can seem muddled, with some showing positive, some showing negative, and some showing neutral effects of medicine on health. So I want to say loudly and clearly what has yet to be said loudly and clearly enough: In the aggregate, variations in medical spending usually show no statistically significant medical effect on health. I want to dare other health policy experts to either publicly agree or disagree with this claim and its apparent policy implications. By "variations" I mean the large changes in medical spending often induced by observable disturbances, such as changing culture or prices, and by "aggregate" I mean studies of the health effect on an entire population of disturbances that affect a broad range of medical treatments. In contrast, the vast majority of medical studies look at the effects of particular categories of treatments on particular classes of patients. Note that a muddled appearance of differing studies showing differing effects is to be expected. After all, even if medicine has little effect, random statistical error and biases toward presenting and publishing expected results will ensure that many published studies suggest positive medical benefits.
Auster, Leveson, & Sarachek, Journal of Human Resources, in 1969 . It found that variations across the 50 US states of 1960 age-sex-adjusted death rates were significantly predicted by variations in income, education, fractions of white collar and female workers, and the existence of a local medical school, but not by variations in medical spending, urbanization, and alcohol and cigarette consumption. Later studies using robust controls to compare similar regions tend to give similar results.
a Byrne, Pietz, Woodard, & Petersen Health Economics 2007 study found no significant mortality effects of funding variations across 22 US Veterans Affairs regions over six years.
Skinner and Wennberg 1998 study, which together used the largest dataset I know of: five million Medicare patients in 1989 and 1990 across 3,400 US hospital regions. Regions that paid more to have patients stay in intensive care rooms for one more day during their last six months of life were estimated, at a 2% significance level, to make patients live roughly forty fewer days, even after controlling for: individual age, gender, and race; zipcode urbanity, education, poverty, income, disability, and marital and employment status; This same study, using the same controls, also estimated that a region spending $1,000 more overall in the last six months of life gave local patients somewhere between a gain of five days of life and a loss of twenty days of life (95% confidence interval).
study in the Journal of the American Medical Association of 3,600 adults over 75 years found large and significant lifespan effects: a three year loss for smoking, a six year gain for rural living, a ten year loss for being underweight, and about fifteen year losses each for low income and low physical activity (in addition to the usual effects of age and gender). Note that someone willing to pay $1,000 to gain 25 days of life should be willing to spend about $1,000,000 to gain six years by living rurally, and $2,000,000 to gain fifteen years via high exercise. These figures seem to me to overestimate the observed eagerness to live rurally or to exercise. Of course all of these studies look at correlation, not causation, between health and medicine. So they all leave open the possibility that someday studies with better controls will show stronger effects. For this reason, discussion of the health effects of medical spending variations usually turns eventually to our clearest evidence on the subject: the RAND health insurance experiment. From 1974 to 1982 this experiment spent about $50 million to randomly assign over two thousand non-elderly families in six US cities to three to five years of a specific medical price, ranging from free to full price, provided by the same set of doctors.
Being assigned a low price for medicine caused patients to consume about 30% (or $300) more in per-person annual medical spending, though less for hospital spending and more for dental and "well care." The RAND experiment was not quite large enough to see mortality effects directly, and so the plan was to track four general measures of health, combined into a total "general health index," and also 23 physiological health measures. Their main result: "For the five general health measures, we could detect no significant positive effect of free care for persons who differed by income ... At a 7% significance level they found that poor people in the top 80% of initial health ended up with a 3% lower general health inde...
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