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Association: Name: Economics of Population Health: Inaugural Conference of the American Society of Health Economists URL: http://healtheconomics.us
Citation: URL: http://www.allacademic.com/meta/p91662_index.html Direct Link: HTML Code:

Rice, Jennifer. and Thornton, James. "Does Extending Health Insurance Coverage to the Uninsured Improve Population Health Outcomes?" Paper presented at the annual meeting of the Economics of Population Health: Inaugural Conference of the American Society of Health Economists, TBA, Madison, WI, USA, Jun 04, 2006 <Not Available>. 2009-05-25 <http://www.allacademic.com/meta/p91662_index.html>

Rice, J. L. and Thornton, J. A. , 2006-06-04 "Does Extending Health Insurance Coverage to the Uninsured Improve Population Health Outcomes?" Paper presented at the annual meeting of the Economics of Population Health: Inaugural Conference of the American Society of Health Economists, TBA, Madison, WI, USA <Not Available>. 2009-05-25 from http://www.allacademic.com/meta/p91662_index.html

Publication Type: Abstract Abstract: The large number of Americans without health insurance has produced a vigorous debate about whether the U.S. should adopt universal health insurance coverage. To assess whether extending health insurance coverage to a larger segment of the population is socially beneficial, it is necessary to measure the associated benefits and costs. Measuring the benefits requires a good estimate of the contribution of health insurance to measures of population health. Prior research suggests that uninsured individuals tend to have worse health outcomes than the insured; however, establishing a causal relationship and obtaining a reliable estimate of the causal effect has been difficult. In general, previous research has not adequately controlled for confounding factors associated with both health insurance coverage and health outcomes resulting in potential omitted variable bias. Many studies have also failed to account for possible reverse causation from health status to insurance coverage leading to simultaneity bias. Moreover, past research provides no information on the dynamics of the process by which changes in health insurance coverage affect mortality over time. The objective of this paper is to investigate the aggregate relationship between health insurance and health outcomes for the general U.S. population, and extend previous work in this area in an attempt to obtain a more reliable estimate of the effect of insurance coverage on mortality that is largely purged of the influence of non-insurance determinants of health, and reverse causation. Our study addresses the following questions. Does increased insurance coverage lead to improved mortality outcomes in aggregate populations, and if so what is the size of the effect? Do different types of health insurance, such as employment, non-employment, and government financed insurance have different effects on mortality outcomes? What is the time path of the effect of insurance coverage on health outcomes? Specifically, does extending health insurance coverage to the uninsured affect aggregate health outcomes both contemporaneously and with a lag, and if so what is the size of the short-term and longer term effects? The approach adopted in this investigation uses a panel of aggregate data on all 50 states for the period 1987-2003 to estimate a health insurance augmented, aggregate health production function for the U.S. Instrumental variable, fixed-effects, static and dynamic models are estimated that control for unobserved state heterogeneity and reverse causation. State-specific time trends are also included to allow unobservable determinants of health to vary within states over time. The effect of health insurance on mortality is therefore identified by relative within-state variation in insurance coverage. In addition, a number of observed covariates, such as income, education, unemployment, cigarette and alcohol consumption, and population demographic characteristics are also included in the aggregate health production function to control for potential determinants of mortality that may be correlated with insurance coverage. The data on health insurance coverage by state come from the U.S. Census Bureau. We also collected data on a large number of additional variables from a variety of sources to construct a unique and rich dataset for use in this study.

The Micropolitics of University-School District Partnerships: Case Study of an Onsite Graduate Program in a Rural Community of Color

“Regional Institutions and the Distribution of Federal Economic Development Grant Funds”

Distributive Justice & Corrective Justice: The Effect of County-Level Racial and Income Inequality on Tort Trial Outcomes