Here's Why Health Care Costs Are Outpacing Health Care Efficacy
In the United States, health care technology has contributed to rising survival rates, yet health care spending relative to GDP has also grown more rapidly than in any other country. We develop a model of patient demand and supplier behavior to explain these parallel trends in technology growth and cost growth. We show that health care productivity depends on the heterogeneity of treatment effects across patients, the shape of the health production function, and the cost structure of procedures such as MRIs with high fixed costs and low marginal costs. The model implies a typology of medical technology productivity: (I) highly cost-effective “home run” innovations with little chance of overuse, such as anti-retroviral therapy for HIV, (II) treatments highly effective for some but not for all (e.g. stents), and (III) “gray area” treatments with uncertain clinical value such as ICU days among chronically ill patients. Not surprisingly, countries adopting Category I and effective Category II treatments gain the greatest health improvements, while countries adopting ineffective Category II and Category III treatments experience the most rapid cost growth. Ultimately, economic and political resistance in the U.S. to ever-rising tax rates will likely slow cost growth, with uncertain effects on technology growth.
This paper strikes me as sensible, explanatory, and non-ideological to the max. It would be nifty if the people who work in Washington read it, and thought about it, and maybe even acted on it. (And it would be nifty if the Knicks beat the Celtics too, but I’m not holding my breath for either outcome …)
Here’s a very good paragraph from the paper:
The science section of a U.S. newspaper routinely features articles on new surgical and pharmaceutical treatments for cancer, obesity, aging, and cardiovascular diseases, with rosy predictions of expanded longevity and improved health functioning (Wade, 2009). The business section, on the other hand, features gloomy reports of galloping health insurance premiums (Claxton et al., 2010), declining insurance coverage, and unsustainable Medicare and Medicaid growth leading to higher taxes (Leonhardt, 2009) and downgraded U.S. debt (Stein, 2006). Not surprisingly, there is some ambiguity as to whether these two trends, in outcomes and in expenditures, are a cause for celebration or concern.
And the authors offer good specific examples of what they built their argument on, noting the …
… wide heterogeneity in the productivity of medical treatments, ranging from very high (aspirin for heart attacks and surfactants for premature births) to low (stents for stable angina), or simply zero (arthroscopy for osteoarthritis of the knee).
This echoes our SuperFreakonomics chapter on cheap and simple solutions, including medical fixes:
Polio is a stark example, but there are countless cheap and simple medical fixes. New ulcer drugs reduced the rate of surgery by roughly 60 percent; a later round of even cheaper drugs saved ulcer patients some $800 million a year. In the first twenty-five years after lithium was introduced to treat manic depression, it saved nearly $150 billion in hospitalization costs. Even the simple addition of fluoride to water systems has saved about $10 billion per year in dental bills. As we noted earlier, deaths from heart disease have fallen substantially over the past few decades. Surely this can be attributed to expensive treatments like grafts, angioplasties, and stents, yes?
Actually, no: such procedures are responsible for a remarkably small share of the improvement. Roughly half of the decline has come from reductions in risk factors like high cholesterol and high blood pressure, both of which are treated by relatively cheap medicines. And much of the remaining decline is thanks to ridiculously inexpensive treatments like aspirin, heparin, ACE inhibitors, and beta- blockers.*
* Underlying research includes: Marc W. Kirschner, Elizabeth Marincola, and Elizabeth Olmsted Teisberg, “The Role of Biomedical Research in Health Care Reform,” Science 266 (October 7, 1994); and Earl S. Ford et al., “Explaining the Decrease in U.S. Deaths from Coronary Disease, 1980– 2000,” New England Journal of Medicine 356, no. 23 (June 7, 2007).