NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

HEALTH CARE


HEALTH CARE PROGRAM MEETING
April 21, 2009
Dana P. Goldman, Organizer


DARIUS LAKDAWALLA, RAND and NBER, and WESLEY YIN, University of Chicago and NBER
Insurer Bargaining and Negotiated Pharmacy Drug Prices in Medicare Part D

A controversial feature of the Medicare Part D drug benefit is its reliance on private insurers to negotiate drug prices and rebates with retail pharmacies and drug manufacturers. Central to this controversy is whether increases in market power—an undesirable feature in most settings—confers some benefits in health insurance markets. Improved insurer market power may manifest itself as a decrease in the negotiated prices charged to insurers; savings may then filter down to beneficiaries who face lower premiums. Lakdawalla and Yin investigate whether insurers who experience larger enrollment increases because of Part D negotiate lower pharmacy drug prices. Overall, they find that 100,000 additional insured individuals lead to 2.5 percent lower pharmacy prices negotiated by the insurer, and a 5 percent reduction in pharmacy profits earned on prescriptions filled by enrollees of that insurer. Estimated enrollment effects are much larger for drugs with therapeutic substitutes. In contrast, insurers have little ability to leverage enrollment when negotiating the cost of branded drugs without therapeutic substitutes—drugs that account for half of U.S. pharmaceutical expenditures for seniors. These researchers also present evidence that most of insurer savings are, on the margin, passed on to Medicare and to enrollees as lower premiums. Out-of-sample estimation suggests that modest insurer consolidation would generate significant savings to Medicare, premium reductions and enrollment increases. Consolidation, when accompanied by selective contracting of low-cost insurers, would generate even larger savings.


FRANK R. LICHTENBERG, Columbia University and NBER
The Quality of Medical Care, Behavioral Risk Factors, and Longevity Growth

The rate of increase of longevity has varied considerably across U.S. states since 1991. Lichtenberg examines the effect of the quality of medical care, behavioral risk factors (obesity, smoking, and AIDS incidence), and other variables (education, income, and health insurance coverage) on life expectancy and medical expenditure using longitudinal state-level data. He examines the effects of three different measures of the quality of medical care: 1) the average quality of diagnostic imaging procedures, defined as the fraction that are advanced procedures; 2) the average quality of practicing physicians, defined as the fraction of physicians trained at top-ranked medical schools; 3) the mean vintage (FDA approval year) of outpatient and inpatient prescription drugs. Life expectancy increased more rapidly in states where the fraction of Medicare diagnostic imaging procedures that were advanced procedures increased more rapidly; the vintage of self- and provider-administered drugs increased more rapidly; and the quality of medical schools previously attended by physicians increased more rapidly. Between 1991 and 2004, life expectancy at birth increased 2.37 years. The estimates imply that, during this period, the increased use of advanced imaging technology increased life expectancy by 0.62-0.71 years, use of newer outpatient prescription drugs increased life expectancy by 0.96-1.26 years, and use of newer provider-administered drugs increased life expectancy by 0.48-0.54 years. The decline in the average quality of medical schools previously attended by physicians reduced life expectancy by 0.28-0.47 years. The rise from 44 percent to 59 percent in the fraction of the population that was overweight or obese reduced the increase in life expectancy by .58-.68 years. The decline in the incidence of AIDS is estimated to have increased life expectancy by .18-.20 years. Growth in life expectancy is uncorrelated across states with health insurance coverage and education and inversely correlated with per capita income growth. The 19 percent increase in real per capita income is estimated to have reduced life expectancy by .34-.43 years. Although states with larger increases in the quality of diagnostic procedures, drugs, and physicians had larger increases in life expectancy, they did not have larger increases in per capita medical expenditure. Lichtenberg provides additional evidence about the impact of advanced imaging technology on mortality using data from Australia’s universal health care system. Demographic groups that had above-average increases in the number of advanced imaging procedures per capita had above-average declines in mortality rates, but changes in mortality rates were uncorrelated across demographic groups with changes in the number of standard imaging procedures per capita. Estimates of the effect of diagnostic imaging innovation on longevity based on Australian data are quite consistent with estimates based on U.S. data.


MARIANNE P. BITLER and CHRISTOPHER CARPENTER, UC, Irvine and NBER
Insurance Mandates and Mammography

The 1990s witnessed historic reductions in breast cancer mortality. Striking increases in screening mammography—rates more than doubled from 1987 to 2000 among prime age women—are widely seen as responsible for a substantial share of these improvements, though we know very little about what caused mammography rates to increase. Bitler and Carpenter show that state mandates requiring private insurers to cover mammography significantly contributed to the large increase in screening rates. They use data on over half a million 25–64 year old women from the CDC’s Behavioral Risk Factor Surveillance System. Their empirical strategy exploits variation in the timing of mandate adoption across states as well as in the ages of women targeted by each law, resulting in triple difference estimates of the effects of mammography mandates. They find robust evidence that state insurance mandates requiring coverage of an annual mammogram significantly increased past year mammography screenings by about 8 percent, and these effects are plausibly concentrated among insured women. Moreover, they find that the mammography mandates had no effects on the probability a woman obtains cervical cancer screenings or clinical breast exams (which were not explicitly targeted by mandates). Their results confirm that regulating private insurance markets to require coverage for relatively low-cost services such as mammograms can have meaningful effects on population preventive health behaviors.


ASHLESHA DATAR and NANCY NICOSIA, RAND Corporation
Junk Food in Schools and Childhood Obesity: Much Ado about Nothing?

There is a growing belief among policymakers and the general public that competitive foods in schools are a significant contributor to the childhood obesity epidemic. Numerous policy initiatives are underway at the local, state, and federal level to regulate the availability of competitive foods in schools. However, the existing empirical evidence motivating these efforts is limited and rarely addresses the potential endogeneity of the school food environment. Datar and Nicosia estimate the causal effect of competitive food availability on children’s body mass index (BMI) and other food- and school-related outcomes using an instrumental variables approach on a national sample of children. They find that competitive food availability generates in-school purchases of junk foods, but contrary to common concerns, there is no significant effect on children’s BMI. Nor do they observe significant changes in overall consumption of healthy and unhealthy foods, and in physical activity. Finally, their results find no support for broader effects of junk foods in school on social/behavioral and academic outcomes.


ANDREEA BALAN-COHEN, Tufts University
Sobering up: The Impact of the 1985-1988 Russian Anti-Alcohol Campaign on Child Health

Balan-Cohen estimates the impact of parental alcohol consumption on child health by taking advantage of a unique shock to alcohol supply: the 1985 to 1988 alcohol prohibition campaign in Russia. This campaign was short lived and resulted in large amounts of exogenous geographic variation in its intensity and effectiveness. Balan-Cohen constructs a new dataset that combines the Russian Longitudinal Monitoring Survey with regional alcohol data. Using both a differences-in-differences approach and instrumental variables methods, she finds significant improvements in child height, immunization rates, and chronic conditions among boys born during prohibition who also lived in regions with effective anti-alcohol campaigns. This confirms the effect of investments during a child’s fetal period and first two years of life on long-term health measures and demonstrates a potential positive effect of suppressing parental access to alcohol. Furthermore, evidence from vaccination rates suggests that the positive effect of prohibition on child health occurred through improvements in parental time, rather than income resources.


AMITABH CHANDRA, Harvard University and NBER, and JONATHAN S. SKINNER, Dartmouth College and NBER
Technology Growth and Expenditure Growth In Health Care

Chandra and Skinner examine the parallel trends in technology growth and cost growth in health care. A simple model of provider behavior shows that the productivity of treatments depends critically on the heterogeneity of these effects across patients, the precise shape of the health production function, and the cost structure of procedures such as MRIs with high fixed costs and low marginal costs. Using these insights, it is informative to think about a (crude) typology of the productivity of medical technologies: highly cost-effective “home run” innovations (aspirin and beta blockers for cardiac care, and anti-retro viral therapy for HIV), treatments that are effective for appropriate patients (surgical interventions for heart attack patients) but offer scope for overuse in less appropriate patients, and “gray area” treatments with uncertain clinical value (ICU days among chronically ill patients). Future productivity growth of the current system will be limited by constraints on health care financing because of high tax burdens and the collapse of private health insurance markets. Nonetheless, there are tremendous potential productivity gains from better coordination of care and information technology.



 
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