Estimating the Cost of Racial and Ethnic Health Disparities

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Abstract

This analysis estimates cost burdens of racial and ethnic disparities in a select set of preventable diseases including diabetes, hypertension and stroke. Excess rates of these diseases among African Americans and Latinos relative to whites will cost the health care system $23.9 billion dollars in 2009. Medicare alone will spend an extra $15.6 billion, and private insurers will spend an extra $5.1 billion. Over the next decade, the total cost is approximately $337 billion. Left unchecked, these annual costs will more than double by 2050 as the representation of Latinos and African Americans among the elderly increases.

Background

The problem of disparities in health between racial and ethnic groups in the United States is well known. (Mead et al. 2008; Agency for Healthcare Research and Quality 2008; Halle, Lewis and Seshamani 2009) A goal of federal health policy is to reduce those disparities, and federal and state offices of minority health guide those efforts. While the moral case for these policies is straightforward, it is also likely that excess disease burden imposes economic costs, which is an important element in making the “business case” for reducing disparities. (Leatherman et al. 2003; Bovbjerg, Hatry and Morley 2009) The goal of this analysis is to quantify this cost burden to the health care system as a whole and to the Medicare and Medicaid programs in particular. As Congress and the administration make decisions about budgets and national health reform legislation that affect disparity reduction efforts, knowledge of the potential economic benefits of those programs is crucial.

Tabulations of disease prevalence based on the 2003–5 waves of the Medical Expenditure Panel Survey (MEPS), shown in figures 1 and 2, demonstrate the nature of disparities in several chronic diseases. For example, diabetes prevalence increases with age for all race/ethnicity groups, but it does so much more rapidly for African Americans and Hispanics than it does for whites. For those 65–74, the prevalence among whites is approximately half that of the other two groups. High blood pressure prevalence also increases more rapidly for the two non-white groups, but the differences are not as dramatic, and the disparity between Hispanics and non- Hispanic whites does not become apparent until very old ages. The disparity pattern for heart disease is quite different, with the prevalence among whites growing more rapidly than for the other two groups, most dramatically relative to Hispanics. The remaining two conditions related to high blood pressure and diabetes—renal disease and stroke—are relatively rare in the sample population, so they are combined in our analysis. Both are very costly as well. The disparity pattern for these conditions is similar to that of high blood pressure in that Hispanics tend to look more similar to whites, while African Americans have generally higher prevalence throughout the age distribution. Figure 2 shows patterns of disparity for three other conditions, all of which have higher prevalence among whites than among the other two groups. These findings from the MEPS are similar to those in the larger National Health Interview Survey. (Pleis and Lucas 2009)

Because the focus of national policy on disease disparities is to reduce the prevalence among minorities when they exceed that of non-Hispanic whites, we focus our analysis in this paper only on such conditions: diabetes, hypertension, stroke and renal disease. Along with heart disease, these conditions are thought to be among the most amenable to reductions in prevalence through disease prevention and management. (Aldana et al. 2006; Levi, Segal and Juliano 2008) To capture health disparities not specifically defined by these conditions, we also include a commonly used self-reported measure of general health status, and measure disparities in the fraction of respondents rating their health as either fair or poor on a scale from poor to excellent. This measure has been shown to be predictive of not only higher medical care spending but future mortality. (Idler and Benyamini 1997)

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