For Kids’ Sake: State-Level Trends in Children’s Health Insurance A State-by-State Analysis. SHADAC, April 2014.
County Health Rankings Show People Living in Least Healthy Counties Twice as Likely to Have Shorter Lives than People Living in Healthiest Counties – Robert Wood Johnson FoundationMarch 28, 2014
The fifth edition of the County Health Rankings released today continues to show us that where we live matters to our health. Large gaps remain between the least healthy counties and healthiest counties. For instance, the least healthy counties have twice the death rates and twice as many children living in poverty and teen births as the nation’s healthiest counties.
A collaboration between the Robert Wood Johnson Foundation (RWJF) and the University of Wisconsin Population Health Institute (UWPHI), the County Health Rankings allow each state to see how its counties compare on 29 factors that impact health, including smoking, high school graduation rates, unemployment, physical inactivity, and access to healthy foods. The Rankings are available at http://www.countyhealthrankings.org.
This undersupply of physicians has long caused medical experts to fret that rural patients receive too little medical care. As a team of researchers pointed out in a recent article in Health Affairs, Medicare has responded by providing a financial incentive to rural healthcare providers, boosting their payment to encourage physicians to locate in such areas: “In the aggregate, Medicare pays rural providers $3 billion more each year in special payments than those providers would receive under traditional payment rates.”
These researchers are skeptical that such payments are working as intended. They analyzed healthcare use across the U.S. to see whether, all else equal, rural patients receive fewer Medicare services than their urban peers. Their results raise serious questions about the idea that such patients are underserved
America’s Underinsured: A State-by-State Look at Health Insurance Affordability Prior to the New Coverage Expansions – The Commonwealth FundMarch 25, 2014
The Affordable Care Act insurance reforms seek to expand coverage and to improve the affordability of care and premiums. Before the implementation of the major reforms, data from U.S. census surveys indicated nearly 32 million insured people under age 65 were in households spending a high share of their income on medical care. Adding these “underinsured” people to the estimated 47.3 million uninsured, the state share of the population at risk for not being able to afford care ranged from 14 percent in Massachusetts to 36 percent to 38 percent in Idaho, Florida, Nevada, New Mexico, and Texas. Nationally, more than half of people with low incomes and 20 percent of those with middle incomes were either underinsured or uninsured in 2012. The report provides state baselines to assess changes in coverage and affordability and compare states as insurance expansions and market reforms are implemented.
Last week, the Census Bureau released some nice charts about the young and uninsured — that is, the folks that insurance companies are now falling over themselves to sign up because young people are cheap (and can be charged premiums higher than are actuarially fair in order to subsidize older people).
Thus, while the US spends more than twice as much on health care than the mean of other OECD countries, its greater GDP and higher prices explain most of it, and income inequality offers an explanation for the rest.
Jeff Young tweeted these Census Bureau maps showing where Americas low-income uninsured live, using the cutoffs for Medicaid expansion eligibility and for Obamacare exchange subsidy eligibility.
it’s clear that people with cancer diagnoses continued to have a higher rate of bankruptcy than people without such diagnoses.
How much higher? About 2 ½ times, on average, across all cancers.
Life Expectancy, Schooling, and Lifetime Labor Supply: Theory and Evidence Revisited by Matteo Cervellati, Uwe Sunde :: SSRNApril 1, 2013
This paper presents a theoretical and empirical analysis of the role of life expectancy for optimal schooling and lifetime labor supply. The results of a simple prototype Ben-Porath model with age-specific survival rates show that an increase in lifetime labor supply is not a necessary, nor a sufficient, condition for greater life expectancy to increase optimal schooling. The observed increase in survival rates during working ages that follows from the “rectangularization” of the survival function is crucial for schooling and labor supply. The empirical results suggest that the relative benefits of schooling have been increasing across cohorts of US men born 1840-1930. A simple quantitative analysis shows that a realistic shift in the survival function can lead to an increase in schooling and a reduction in lifetime labor hours.
Education and Health: The Role of Cognitive Ability by Govert Bijwaard, Hans Van Kippersluis, Justus Veenman :: SSRNApril 1, 2013
We aim to disentangle the relative contributions of (i) cognitive ability, and (ii) education on health and mortality using a structural equation model suggested by Conti et al. (2010). We extend their model by allowing for a duration dependent variable, and an ordinal educational variable. Data come from a Dutch cohort born around 1940, including detailed measures of cognitive ability and family background at age 12. The data are subsequently linked to the mortality register 1995-2011, such that we observe mortality between ages 55 and 75. The results suggest that the treatment effect of education (i.e. the effect of entering secondary school as opposed to leaving school after primary education) is positive and amounts to a 4 years gain in life expectancy, on average. Decomposition results suggest that the raw survival differences between educational groups are about equally split between a ‘treatment effect’ of education, and a ‘selection effect’ on basis of cognitive ability and family background.