Thursday, February 6, 2014

health care spending vs. outcomes

The following was dropped in the editing process from my Independent Review article or my Cato Journal article on health care/insurance.
I can understand why my three "starting points" were cut-- in the interest of space trade-offs within a journal. For economists, these are examples of "re-creating the wheel"-- and thus, not a good choice for inclusion in a journal article. But for the unwashed, these are important points to make. (They are a frequent part of my public presentations or at least the Q&A afterwards.)
So, I'll publish them myself! ;-)
Below is "starting point" #3. Follow this link for #1 and this link for #2. 


Why is U.S. health care spending so high, while certain health outcomes seem so low (relative to other developed countries)?

First, recall that health care and health are not the same. All things equal, more health care should lead to more health. But all things aren’t equal.

Cutler (1995) observes that higher national income will reasonably result in a higher percentage spent on health care—and presents regression results to back up the theory. So, wealthier countries are more likely to spend a higher percentage of their GDP on health.

Cutler also notes that the impact of increased spending on the insured is not effective—not a particularly surprising result, given that health insurance is so strongly subsidized and the price of heavily-insured care is artificially low for the insured. After all, how many people will pay attention to price and cost if someone else is picking up the bill?

Another consideration is the manner in which health outcome statistics are defined. For example, the United States is more liberal in accounting for pre-mature births. Since “premies” are more likely to die, this increases infant mortality and lowers life expectancy. A broader critique of these statistics comes from Whitman (2008) who critiques a World Health Organization report (2000) and its implicit assumptions: “some of them are logically incoherent, some characterized by substantial uncertainty, and some rooted in ideological beliefs and values that not everyone shares”.

Whitman also takes the WHO report to task because it makes no reference to variance in lifestyle choices between countries: “The WHO approach holds health systems responsible not just for treating lung cancer, but for preventing smoking in the first place; not just for treating heart disease, but for getting people to exercise and lay off the fatty foods.” Of course, such problems are largely beyond the control of a health care system and such an analysis is clearly inferior in that it ignores individual and cultural preferences—as well as the inherent trade-offs between health and other economic goods.

Lifestyle choices are important, but systematically ignored in these discussions. Proponents of more government intervention point to European countries with heavier government involvement and better health outcome statistics. But Singapore has considerably less government involvement in health care—with one-fifth of U.S. expenditures per capita and one-fourth in terms of GDP (Weber, 2008). Clearly, the level of government involvement is not the primary explanation.[4]

It’s worth noting that one would expect government intervention to be relatively effective within a smaller, more homogeneous population. But neither of those characteristics describe America. If one wants more government activism on that basis, then advocacy of small, local, and state experiments makes far more sense than leaping into one, grand, risky, federal experiment.

One other difference has received a lot of attention: differences in Medicare spending by region. The assumption is that medical decisions are driven by “cultural” factors of a sort—that doctors and patients grow accustomed to levels of health care not found in other areas of the country. Moreover, these higher spending levels do not seem to be correlated with better health outcomes. For example, Wennberg et. al. (2002) find that rates of illness do not explain differences in spending across regions.

Taken at face value, this calls for decreased Medicare spending in those regions—an opportunity to reduce expenditures without compromising health care. Again, this is consistent with Cutler’s (1995) observation that the impact of spending on the insured is not correlated with outcomes. Rettenmaier and Saving (2009a) note that this is “one of the leading rationales for reform” in Medicare. But this factoid could be more easily used to motivate less rather than more government involvement—with Medicare in particular and health care in general.

They observe that “some of the variation in Medicare spending can be linked to a state’s income, demographics, health market conditions and the population’s underlying health risks”. They also acknowledge that “there remains some persistent variation that has often been attributed to differences in the way health care is practiced”. But they find that “the same pattern of regional variation observed for Medicare spending does not necessary hold when other measures are used.”

They also investigate the percentage of uninsureds as an explanatory variable. “As expected, a higher uninsured rate is associated with lower state health care spending in the non-Medicare/Medicaid population. In contrast, a higher percent of the population with no insurance resulted in higher Medicare spending per enrollee, indicating cost shifting to Medicare.”

In any case, this debate underlines the importance of closely equating care with costs—restoring “price tags” to health care. This can only be accomplished through market-based incentives.

[4] Lifestyle choices also extend beyond “health”. Krug et. al. (1998) finds that firearm mortality rates are eight times higher in America than in its economic counterparts (14.24 vs. 1.76 per 100,000)—and the rate in the Americas exceeds those in Asia by 95-fold.


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