Increasing health insurance costs and the decline in insurance coverage

Health Services Research, August, 2005 by Michael Chernew, David M. Cutler, Patricia Seliger Keenan

The 1990s were a decade of relative prosperity, yet the percentage of Americans without health insurance coverage rose over 17 percent between 1990 and 1998. This decline generally reflects a drop in the rates of employer-sponsored coverage, a trend that began in the late 1970s (Farber and Levy 2000). The drop in coverage has raised concern among policy makers in light of a variety of studies that highlight the difficulty that the uninsured have in accessing care, and their resulting poorer outcomes (Institute of Medicine 2002; Serafini and Stone 2002). Designing policies that will effectively address this problem requires understanding why coverage rates have fallen and anticipating how coverage will change in the future. Despite a relatively large literature investigating the determinants of insurance coverage, relatively few studies use multivariate techniques to examine factors contributing to the decline in coverage over time. These studies show that increased reliance on part-time workers (Fronstin and Snider 1996), industry shifts (Long and Rogers 1995), a combination of labor market factors (Kronick and Gilmer 1999; Glied and Stabile 2000; Glied and Jack 2003), or crowdout (Curler and Gruber 1996a, b; Currie and Yelowitz 1999; Blumberg, Dubay, and Norton 2000) only partially explain the decline in employer-provided insurance.

An alternative explanation is that coverage has dropped because the cost of insurance has risen. In contrast to substantial media coverage linking rising premiums to declining coverage rates, empirical evidence quantifying the relationship between premiums and coverage is limited. The studies that use multivariate techniques to examine the relationship between health care costs and coverage rates find support for the view that increasing costs decrease coverage (Fronstin and Snider 1996; Kronick and Gilmer 1999; Curler 2002; Glied and Jack 2003). Kronick and Gilmer (1999) rely on national measures of health care costs, relative to income, and generate most of the variance in the cost to income ratio from variation in income, not health care costs. Fronstin and Snider (1996) analyze state-level data from 1988 to 1992 and include only one cost proxy, the price of a hospital day. Cutler (2002) uses national-level data on employee contributions. Glied and Jack (2003) use state-level Medicare per capita spending excluding home health, adjusted by the ratio of private spending per enrollee to Medicare spending per enrollee. Thus these studies do not directly measure the effects of rising premiums on coverage, nor do they attempt to adjust for potential reverse causality that arises because declining coverage may lead to higher premiums. Further, existing studies typically focus on employer-sponsored coverage, which, although important, does not give a full picture of the effects of rising premiums on coverage because some individuals may substitute public for private coverage. Finally, these studies typically do not devote substantial attention to controlling for potential confounding explanations for the decline in coverage such as the expansion in Medicaid or changing tax policy.

This paper explores the relationship between health care premiums and coverage rates. It takes advantage of wide geographic variation in changes in premiums and coverage rates. Thus the variation in premiums that we use is broader than that used in existing literature and less likely to be confounded with other secular trends. In contrast to existing work, we also use instrumental variable (IV) techniques to address the potential for reverse causality between rising costs and coverage rates. The IV techniques also adjust for potential measurement error in our premium data.

We focus on coverage from any source, which gives a more complete picture of coverage because some individuals may switch from private to public coverage. We also focus only on the ultimate coverage decision, without attempting to explain the detailed set of decisions such as employer offer or employee take-up, which lead to coverage. Finally, we control for a wide range of factors associated with alternative explanations of coverage declines. We thus quantify the link between rising health insurance premiums and rates of insurance coverage, addressing limitations of the existing literature.

CONCEPTUAL FRAMEWORK

The price of insurance can be measured in several ways. Economics textbooks define the price of health insurance as the loading fee, or the difference between the premium and expected payout (Phelps 1997; Feldstein 1999). (1)

An alternate approach uses premiums or costs to measure price. In contrast to a price measure based on the load, the use of premiums as a measure of price captures the effects of rising medical expenditures on coverage rates. (2) Standard economic theories of insurance coverage predict that as the magnitude of the potential loss rises, demand for coverage would increase. Interpreting rising premiums as an increase in the potential loss is reasonable because most research examining the causes for rising expenditures attributes spending increases to advances in medical technology. Therefore rising premiums may reflect services individuals value (Newhouse 1992; Curler 1995; Chernew et al. 1998). This analysis would lead one to expect coverage rates would increase as medical expenditures rise. For certain medical services this has certainly been true. For example, coverage rates for pharmaceuticals have risen as pharmaceutical expenditures have risen.