www.overcomingbias.com/medicine/index.html
studies, We the undersigned petition the US to publicly conduct a similar experiment again soon, this time with at least ten thousand subjects treated for at least ten years, which should be feasible for a half billion dollars, or one part in forty thousand of annual medical spending. Whatever other purposes such an experiment pursues, it should try to make clear the aggregate health effects of variations in aggregate medical spending, variations induced by feasible regimes of quality control, including free patient choice induced by a varying aggregate price.
Experiment seems clear evidence that medicine is a huge scandal. Readers of the medical literature, as well as readers of medical media coverage and students in health and medicine, have all been given the strong impression that in the aggregate, more medicine produces more health. This was the impression thirty years ago as much as today.
typical result of aggregate correlation studies: we see no such relation. Thus the medical research literature must suffer from severe biases, such as fraud, funding bias, treatment selection bias, publication selection bias, leaky placebo effects, misapplied statistics, and so on. How else can we square the usual positive benefit found in medical publications with a net zero benefit? Furthermore, what else but education and media biases can explain why this experiment, very expensive, well published, and the most important medical study ever, remains mostly unknown to medical students, professionals and the public? Further evidence of bias is found in the shameful way many try to claim the RAND experiment shows that medicine helps, via noting "significant" results, using statistical tests that do not correct for the data mining required to find those results. For example, if you look at thirty outcomes, and are willing to break subjects down by both poor/rich and good/bad initial health, you should on average see six results "significant" at the 5% level, even if there were no effects.
Fiefdom Syndrome gives an example of a sales manager whose regular presentations to his manager usually focused on how sales were up for particular customers groups on particular products, and who didn't want to talk about why total sales continued to fall. This sales manager might complain "I keep telling you all this good news; Similarly, studies of the aggregate effects of medicine are not just one more kind of medical study; they are a crucial check on biases in all the other studies.
I said: Medical expenses now eat 16% of US GDP That percentage has doubled every thirty years; it was 8% thirty years ago, and 4% thirty years before that. It will probably double again, to 32%, in the next thirty years. For many years policy makers have warned of an upcoming "Medicare Train Wreck," when rising medical costs collide with a surge of retiring baby boomers.
reminds us again: A recently released report by the program's trustees found that within seven years Medicare taxes will fall short of Medicare expenses by more than 45%. Until a few years ago, Social Security and Medicare were taking in more than they spent, on the whole. That situation is now reversed, and last year the combined deficits in the two programs claimed 53% of federal income tax revenues. In 15 years these two programs will require more than a fourth of income tax revenues: ... these two programs will require almost one out of every two federal income tax dollars. If the world stays relatively boring, this will be the biggest US politics issue over the next twenty years. The key questions: 1 Who will pay: raise taxes, limit treatments covered, tax docs, or cut off the richer & younger? Added: Income tax is only half of federal taxes, but most of Medicaid, which is about as big as Medicare, also goes to the elderly.
RAND Health Insurance Experiment II I reported yesterday on the RAND health insurance experiment: Thousands of people randomly given free medicine in the late 1970s consumed 30-40% more medical services, paid one more "restricted activity day" per year to deal with the medical system, but were not noticeably healthier. So unless the marginal value of medicine has changed in the last thirty years, if you would not pay for medicine out of your own pocket, then don't bother to go when others offer to pay. The extra medical care induced by free medicine seems to have no health value. But what do we know about the value of common medicine, used by both those with free medicine and those who shared costs in this experiment?
recent summary: Cost sharing reduced the use of effective and less-effective care across the board. For hospitalizations and prescription drug use, cost sharing likewise reduced more-effective and less-effective care in roughly equal amounts for all participants. the appropriate use of visits and diagnostic tests by providers and the appropriate use of therapeutic interventions after participants sought care. cost sharing did not significantly affect the quality of care received by participants. People with free medicine made 30%+ more doctor visits than those who had to pay, but those extra visits were not just trivial visits for sniffles or warts. The extra visits were just as often to the hospital, their condition was at a similar "stage of disease presentation", and the treatment was later evaluated by panels of doctors to be just as appropriate. By all of these measures extra and common medicine looked the same to doctors. So if common medicine is more valuable than extra medicine, it must be that patients somehow know when they really need help, and make sure to get care no matter what the cost.
How useful is medicine, to the average person, wondering if he should go to the doctor or skip it? We have perhaps a million medical studies, but how do we combine them into a total estimate of the value of medicine? It is hard to see how to correct for many potential biases such as fraud, funding bias, treatment selection bias, publication selection bias, and so on. These biases can be partially overcome by focusing on studies of the aggregate effects of medicine on the general population, some of which compare millions of people over years.
usually find no health effect of more medicine, but most are correlation studies, so one may doubt if they controlled for enough relevant factors. Fortunately, there has been one large randomized experiment on aggregate medicine.
RAND health insurance experiment, where from 1974 to 1982 the US government spent $50 million to randomly assign 7700 people in six US cities to three to five years each of either free or not free medicine, provided by the same set of doctors. The plan was to compare five measures of general health, and also 23 physiologic health measures.
New England Journal of Medicine article: For the average person enrolled in the experiment, we observed two significant positive effects of free care relative to cost-sharing: corrected far vision ... was better by 01 Snellen lines (p = 0001) and diagnostic blood pressure was lower by 08mm HG (p = 003). any true differences would be clinically and socially negligible. For the five general health measures, we could detect no significant positive effect of free care for persons who differed by income .. Among participants who were judged to be at elevated risk with respect to smoking habits, cholesterol levels, and weight, free care had no detectable effect. For persons who were in the upper quartile of the distribution of risk factors included in the risk of dying index, the risk of dying was 10 percent lower on the free than the cost-sharing plans (p = 002). It has long been obvious that eyeglasses help people see better, and eyeglasses are basically physics, not "medicine," so that result should be set aside. Since this experiment looked at thirty measures in total then just by chance one of them should seem significant at the three percent level, explaining the blood pressure result.
The bottom line is that thousands of people randomly given free medicine in the late 1970s consumed 30-40% more medical services, paid one more "restricted activity day" per year to deal with ...
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