The impact of health insurance on health
ABSTRACT How does health insurance affect health? After reviewing the evidence on this question, we reach three conclusions. First, many of the studies claiming to show a causal effect of health insurance on health do not do so convincingly because the observed correlation between insurance and good health may be driven by other, unobservable factors. Second, convincing evidence demonstrates that health insurance can improve health measures of some population subgroups, some of which, although not all, are the same subgroups that would be the likely targets of coverage expansion policies. Third, for policy purposes we need to know whether the results of these studies generalize. Solid answers to the multitude of important questions about how specific health insurance policy options may affect health seem likely to be forthcoming only with investment of substantial resources in social experiments.
- SourceAvailable from: Charles J Courtemanche
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- "An important part of the argument for universal coverage is the idea that health insurance improves health. As quoted by Yelowitz and Cannon (2010), Levy and Meltzer (2008) write, The central question of how health insurance affects health, for whom it matters, and how much, remains largely unanswered at the level of detail needed to inform policy decisions. . . . Understanding the magnitude of health benefits associated with insurance is not just an academic exercise[,] . . . it is crucial to ensuring that the benefits of a given amount of public spending on health are maximized (p. "
ABSTRACT: In 2006, Massachusetts passed health care reform legislation designed to achieve nearly universal coverage through a combination of insurance market reforms, mandates, and subsidies that later served as the model for national reform. Using data from the Behavioral Risk Factor Surveillance System, we provide evidence that health care reform in Massachusetts led to better overall self-assessed health. Various robustness checks and placebo tests support a causal interpretation of the results. We also document improvements in several determinants of overall health: physical health, mental health, functional limitations, joint disorders, and body mass index. Next, we show that the effects on overall health were strongest among those with low incomes, nonwhites, near-elderly adults, and women. Finally, we use the reform to instrument for health insurance and estimate a sizeable impact of coverage on health.Journal of Policy Analysis and Management 12/2014; 33(1):36-69. DOI:10.1002/pam.21737 · 0.93 Impact Factor
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- "Regression models may also be subject to omitted variable bias; both the labor market and health insurance expenditures' models may be correlated with other time varying confounders that influence the mortality rate, health status, healthcare spending, and healthcare professionals' employment. Nevertheless, causality among these relationships is ambiguous (Levy and Meltzer 2008). Instrumental variables approach is used to deal with endogeneity so that consistent estimates for the labor market effect are obtained. "
ABSTRACT: The healthcare sector was one of the few sectors of the US economy that created new positions in spite of the recent economic downturn. Economic contractions are associated with worsening morbidity and mortality, declining private health insurance coverage, and budgetary pressure on public health programs. This study examines the causes of healthcare employment growth and workforce composition in the US and evaluates the labor market's impact on healthcare spending and health outcomes. Data are collected for 50 states and the District of Columbia from 1999-2009. Labor market and healthcare workforce data are obtained from the Bureau of Labor Statistics. Mortality and health status data are collected from the Centers for Disease Control and Prevention's Vital Statistics program and Behavioral Risk Factor Surveillance System. Healthcare spending data are derived from the Centers for Medicare and Medicaid Services. Dynamic panel data regression models, with instrumental variables, are used to examine the effect of the labor market on healthcare spending, morbidity, and mortality. Regression analysis is also performed to model the effects of healthcare spending on the healthcare workforce composition. All statistical tests are based on a two-sided alpha significance of p<.05. Analyses are performed with STATA and SAS. The labor force participation rate shows a more robust effect on healthcare spending, morbidity, and mortality than the unemployment rate. Study results also show that declining labor force participation negatively impacts overall health status (p<.01), and mortality for males (p<.05) and females (p<.001), aged 16-64. Further, the Medicaid and Medicare spending share increases as labor force participation declines (p<.001); whereas, the private healthcare spending share decreases (p<.001). Public and private healthcare spending also has a differing effect on healthcare occupational employment per 100,000 people. Private healthcare spending positively impacts primary care physician employment (p<.001); whereas, Medicare spending drives up employment of physician assistants, registered nurses, and personal care attendants (p<.001). Medicaid and Medicare spending has a negative effect on surgeon employment (p<.05); the effect of private healthcare spending is positive but not statistically significant. Labor force participation, as opposed to unemployment, is a better proxy for measuring the effect of the economic environment on healthcare spending and health outcomes. Further, during economic contractions, Medicaid and Medicare's share of overall healthcare spending increases with meaningful effects on the configuration of state healthcare workforces and subsequently, provision of care for populations at-risk for worsening morbidity and mortality.International Journal of Health Care Finance and Economics 03/2014; DOI:10.1007/s10754-014-9142-0 · 0.49 Impact Factor
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- "Compared to those with coverage, uninsured adults experience significantly worse health outcomes and die at younger ages (Institute of Medicine 2002). Recent quasi-experimental and randomassignment studies consistently find positive and often significant effects of health insurance on health outcomes, especially for low-income adults, those with chronic health conditions, and other vulnerable populations (Levy and Meltzer 2008; McWilliams 2009; Finkelstein et al. 2011). Health insurance loss is also associated with subsequent declines in health (Baker et al. 2002). "
ABSTRACT: This article bridges the literatures on the economic consequences of divorce for women with that on marital transitions and health by focusing on women’s health insurance. Using a monthly calendar of marital status and health insurance coverage from 1,442 women in the Survey of Income and Program Participation, we examine how women’s health insurance changes after divorce. Our estimates suggest that roughly 115,000 American women lose private health insurance annually in the months following divorce and that roughly 65,000 of these women become uninsured. The loss of insurance coverage we observe is not just a short-term disruption. Women’s rates of insurance coverage remain depressed for more than two years after divorce. Insurance loss may compound the economic losses women experience after divorce and contribute to as well as compound previously documented health declines following divorce.Journal of Health and Social Behavior 12/2012; 53(4):413-431. DOI:10.1177/0022146512465758 · 2.72 Impact Factor