Health insurance level was randomized, actual medical treatment was not. Thus one should be careful when making causal inferences regarding increased medical usage in this study.

I admit to the existence of the biases you bring up in regards to the medical literature, but you can’t be so quick to dismiss other explanations when people were in control of making decisions regarding the actual amount of medical treatment they received.

In addition, an increase in doctor and ER visits is not equivalent to an increase in medical treatment. Not every time you go to the doctor do you receive medicine. Also, people with less of a cost to seeing a doctor are likely to go to the doctor for less severe conditions than those who must weigh the financial cost against their perceived need. We can go on and on thinking of other explanations in this study… such is often the heavy burden in an observational study… confident conclusions cannot always be made when other logical conclusions are plausible.

Aside, with a mean age of 31, how much of a benefit measured in terms of overall health should one have expected to see over a 3-5 year period?

Is there evidence that increasing medical spending actually makes people worse off, or just that it stops having a benefit?

If there’s a point where spending more actually makes you die earlier, then we’re presumably in a world where there’s a rate of medical error that kills you, and a diminishing rate of improved survival from medical care. When the two curves cross is the optimal benefit from medicine; after that, you’re getting marginal care and dying of it. (Think of purely cosmetic procedures here.)

If the response goes flat at some point (more spending has no effect on life expectancy, what I think the RAND study demonstrates within a certain range), then the model is a bit harder to understand. We know there’s a rate of medical error. Maybe professional judgement and regulation and fear of lawsuit chop out most of the procedures/treatments that have a higher rate of killing you than saving you?

Anyway, which model is a better description of reality is very important, because it tells us where to focus energy. In the first model, regulators/payors/etc ought to be excluding the worst treatments. In some sense, that’s easy to do, because it’s just applying existing statistics and some level of judgement–you don’t need to do anything new.

In the second model, that’s already been done, and all that’s left is to make the treatments more effective or safer. That’s worth doing, but is hard, in the sense that you actually have to do something clever and new; it’s a research and teaching and best-practices kind of problem, not a straightforward regulatory problem.

“Dr. Lung: Research is a real problem. Doctors just make up the data. They don’t report negative side effects, no question about it. I used to write the results on my reports that were negative and nobody printed them. Only if it’s positive does it get published in a journal. A doctor I know used to publish papers like nobody’s business, and all the doctors who came and left told me he made up data to satisfy NIH grants and pharmaceutical grants. He was and still is very popular.”

Everything else is me.

Dr. Lung: Research is a real problem. Doctors just make up the data. They don’t report negative side effects, no question about it. I used to write the results on my reports that were negative and nobody printed them. Only if it’s positive does it get published in a journal. A doctor I know used to publish papers like nobody’s business, and all the doctors who came and left told me he made up data to satisfy NIH grants and pharmaceutical grants. He was and still is very popular.

And we’ve already heard that two thirds of the “statistically significant” reports don’t replicate, negative papers don’t get published, multiple studies are done, and nobody bothers with replications anyway. And the ability to get bogus results by fancy statistics is so severe that the control variable weightings of papers that were supposed to be looking at something else are consistent among themselves, but completely out of whack with the papers that are supposed to be investigating the main result.

Perhaps we should not be so puzzled that we have all these wonderful papers showing individual medical procedures as effective, and yet in the aggregate, marginal extra spending on them has a (net!) result of nothing.

According to a recent RAND study, the uninsured only get about 53.7 percent of the care that experts say they should get. But what’s stunning is that patients with private, fee-for-service insurance are “even less likely to receive the proper care.” Likewise, it’s true that lack of health insurance causes about 18,000 premature deaths annually. But about 98,000 people are killed each year by medical errors, and 126,000 die “from their doctor’s failure to observe evidence-based protocols for just four common conditions: hypertension, heart attacks, pneumonia, and colorectal cancer.”

The root problem here, Longman argues, is that doctors tend to perform lots and lots of unnecessary treatments–partly because they get paid per service, and have no real economic interest in their patients’ long-term well-being. Dr. Elliot Fisher, a Dartmouth researcher, estimates that “30 percent of all Medicare spending goes for unnecessary operations and procedures.” (Notably, an oversupply of specialists will often create its own demand: Per capita Medicare costs for terminally ill patients in Miami are $50,000 more per year than in Minneapolis, but patients in Miami don’t live any longer–the city’s high concentration of specialists are just providing more treatments that simply aren’t needed.)..

Robin,
You also don’t have any evidence from the Rand study which suggests that you could “cut very deep with little or no loss.” As you have said before, the Rand study is about the marginal benefits of more medicine on top of what you would have received if you had to pay for it yourself.

Increased healthcare usage with no signficant positive benefit is not equivalent to suggesting that we could significantly decrease medicine usage without lowering health.