The RAND Health Insurance Experiment is referenced in the academic literature as a “gold standard” study, and the main conclusion it reached aligned perfectly with what Econ 101 teaches us — when people have to pay for stuff, they buy (significantly) less of it. It also confirmed that “outcomes” were not worse for those poor devils that are forced to participate fully in a market system (meaning having to pay for things.)
This conclusion was reached again when the results of a two-year Oregon Health Study were announced. Free health care did not result in clear improvements in physical health for the participants.
Another Econ 101 principle shown to be highly applicable in other markets is that when things are free, demand increases. And when demand increases, prices tend to go up. The paradox is that while places like France and the U.K. are regarded as highly socialized in the delivery of health care, their costs are well controlled compared to the “free market” of the U.S.
The question is, how do you define a market as “free” vs socialized? Many would say that you’d be hard pressed to come up with a better metric than the percentage of health costs paid directly to health care providers out of patient’s own pockets.
Luckily The World Bank has calculated that for us. I found the numbers surprising — that is until I realized they aligned perfectly with what Econ 101 tells us.
According to World Bank, over 50 percent of costs are paid out of pocket in the U.K. France? 32 percent. Canada? 49 percent. The free market “wild west” that is the U.S.A.? A measly 21 percent. That’s right. Thanks to the collectivization we call insurance, the vast majority of services are delivered to people who don’t care about the bill.
OK, so I’ve tossed out a few examples here, but what does the data tell us? Let’s compare the two data sets linked above. Prices vs. out of pocket. Here is the pattern:
That’s a correlation coefficient of .51. Compare to the correlation of I.Q. to income, which is estimated to be .40 to .50.
I’d be interested to see other data sets that have been correlated with health care costs. I think one would be hard pressed to find a relevant set with a higher alignment.