NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH
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Frontiers in Health Policy Research

October 14, 2009
William B. Vogt, Organizer

Tomas Philipson, University of Chicago and NBER; Eric Sun; Anupam Jena, Harvard University; and Dana Goldman, University of Southern California and NBER
A Re-Examination of the Costs of Medical R&D


Kenneth Chay, Brown University and NBER
Medicare

Chay and his co-authors examine changes in hospital utilization and mortality rates occurring after the original introduction of Medicare in July of 1966. Their analysis uses the "age discontinuity" design of recent studies, but also accounts for pre-existing trends, as is done in another set of more aggregated research. They find: i) clear evidence that Medicare increased hospital care utilization and costs among the elderly, but at a lower rate than previously found; 2) significant reductions in the mortality of the eligible population that exhibit an age discontinuity only after the introduction of Medicare – patterns not found in nations that did not introduce a Medicare-style program in the 1960s; and 3) the sharpest mortality reductions in acute causes of death (heart disease), with no change in cancer deaths. They estimate that Medicare's introduction had a cost-per-life year ratio below $200 (in 1982-4 dollars), with an even lower cost ratio for quality-adjusted life years. In an analysis of changes over time in the characteristics of the "marginal" person who benefited from Medicare coverage, they find that the 65-and-over discontinuity in insurance coverage fell over time, and that the rate of decline was highest among blacks, the less educated, and the poor. They also find a sharp increase during the 1980s in the use of coronary artery bypass graft (CABG) surgery on the Medicare eligible, which coincided with an increase in the relative Medicare reimbursement rate for this procedure.


Mark Trusheim, MIT; Murray L. Aitken, IMS Health; and Ernst R. Berndt, MIT and NBER
Characterizing Markets for Biopharmaceutical Innovations: Do Biologics Differ from Small Molecules?

While much has been written about the distinctions between biologics and small molecules in terms of their scientific, manufacturing, and regulatory experiences, relatively little has been published comparing their clinical and commercial experiences. Using a database encompassing all 96 biologics and 212 small molecules newly launched in the United States between 1998Q1 and 2008Q4, Trusheim, Aitken, and Berndt compare their downstream clinical and commercial characteristics. Substantial heterogeneity occurs across therapeutic classes. Biologics are more concentrated than small molecules in their therapeutic class composition, but have obtained FDA indication approvals in 13 of 15 classes. While average delays between FDA approval and first observed sales revenues are similar, biologics are twice as likely as small molecules to be Orphan Drugs, are slightly more likely to be designated FDA priority rather than standard review status, and gain slightly more supplemental indication approvals. Although 9.4 percent of new small molecules permanently exited the market for a variety of reasons, 7.3 percent of new biologics exited, but 26 percent of biologics had black box warnings compared to 20 percent of small molecules. Both biologics and small molecules take 21-22 quarters from launch to reach $100 million in real revenues. Small molecules have an initially more rapid uptake, but thereafter biologics' mean revenues tend to be slightly greater than for small molecules. While launch prices for biologics are commonly perceived as being greater than for small molecules, price growth per standard unit is generally greater for small molecules than biologics, with rates of price growth increasing for small molecules in the first five years since launch, and decreasing thereafter. The authors conclude that the market dynamics of biologics differ substantially from those of small molecules, although therapeutic class composition plays a major role.

Gary Burtless, Brookings Institution
Health Care, Health Insurance, and the Distribution of American Incomes

More than one seventh of total personal consumption now consists of health care purchased with government insurance and employer contributions to employee health plans. Burtless and Svaton combine health care spending and insurance reimbursement data in the Medical Expenditure Panel Study, and money income and health coverage data in the Current Population Survey, to assess the impact of health insurance on the distribution of income. Their estimates imply that gross money income significantly understates the resources available to finance household purchases. A more complete measure of resources would show less inequality than the income measures that are currently used. The addition of estimates of the value of health insurance to countable incomes reduces measured inequality in the population and the income gap between young and old. If the analysis were extended over a longer period, it would show a sizeable impact of insurance on inequality trends in the United States.


Lindsey Leininger, University of Wisconsin; Helen G. Levy, University of Michigan and NBER; and Diane Whitmore Schanzenbach, University of Chicago and NBER
Consequences of Public Health Insurance Expansions for Household Well-Being

About 7.4 million children were covered by the State Children's Health Insurance Program (SCHIP) at some point during fiscal year 2008. Many of these children would probably have had private coverage in the absence of SCHIP; recent estimates of the extent of "crowd-out" associated with SCHIP are about 60 percent (Gruber and Simon, 2008). The high rate of crowdout means that the program is not as effective is it might be at reducing the number of uninsured children, which has been a political liability for the program. Both political concerns and policy research focusing on crowd-out in SCHIP build on more than a decade of similar attention to the crowd-out associated with the Medicaid expansions of the late 1980s and early 1990s. This focus on crowd-out has overshadowed a related question about the impact of SCHIP, namely: how has the program affected the overall well-being of targeted households? Well-being depends not only on health insurance coverage but on the full set of economic resources available to a household. While there is little doubt that expanding eligibility for public insurance to children who are not poor will lead some to substitute public for private coverage, this substitution should increase total resources available to these households in two ways. First, those who drop private coverage in order to enroll their children in SCHIP can take whatever they had been spending on health insurance and spend it on something else. Second, public insurance requires less cost-sharing than a typical private insurance policy, providing first-dollar coverage with minimal co-payments. This means that switching from private to public coverage reduces a family's out-of-pocket medical spending, freeing up even more of the family's resources for other uses. From the perspective of a low-income family, then, crowd-out is a windfall. Leininger, Levy, and Whitmore ask how big this windfall is, and what these families do with it? They analyze consumption data from the Consumer Expenditure Survey and find that eligibility for SCHIP is associated with an increase in overall spending; most of this increase appears to come in spending on housing, food, and transportation. These results suggest that the SCHIP expansions substantially improved the material well-being of the low-income families it is intended to assist - including those who had previously been paying for their own coverage. This evidence should allow a better accounting of the benefits and not just the costs of recent expansions in public health insurance programs.

 
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