Inequality in mortality between Black and White Americans by age, place, and cause and in comparison to Europe, 1990 to 2018.

Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990 and 2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in high- and low-income US areas and with reference to six European countries. Inequalities in life expectancy are starker in the United States than in Europe. In 1990, White Americans and Europeans in high-income areas had similar overall life expectancy, while life expectancy for White Americans in low-income areas was lower. However, since then, even high-income White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%. Black American life expectancy increased more than White American life expectancy in all US areas, but improvements in lower-income areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black Americans' mortality reductions included cancer, homicide, HIV, and causes originating in the fetal or infant period. Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both high-income and low-income areas.

Knowledge as a Predictor of Insurance Coverage Under the Affordable Care Act.

BACKGROUND: The Affordable Care Act established policy mechanisms to increase health insurance coverage in the United States. While insurance coverage has increased, 10%-15% of the US population remains uninsured. OBJECTIVES: To assess whether health insurance literacy and financial literacy predict being uninsured, covered by Medicaid, or covered by Marketplace insurance, holding demographic characteristics, attitudes toward risk, and political affiliation constant. RESEARCH DESIGN: Analysis of longitudinal data from fall 2013 and spring 2015 including financial and health insurance literacy and key covariates collected in 2013. SUBJECTS: A total of 2742 US residents ages 18-64, 525 uninsured in fall 2013, participating in the RAND American Life Panel, a nationally representative internet panel. MEASURES: Self-reported health insurance status and type as of spring 2015. RESULTS: Among the uninsured in 2013, higher financial and health insurance literacy were associated with greater probability of being insured in 2015. For a typical uninsured individual in 2013, the probability of being insured in 2015 was 8.3 percentage points higher with high compared with low financial literacy, and 9.2 percentage points higher with high compared with low health insurance literacy. For the general population, those with high financial and health insurance literacy were more likely to obtain insurance through Medicaid or the Marketplaces compared with being uninsured. The magnitude of coefficients for these predictors was similar to that of commonly used demographic covariates. CONCLUSIONS: A lack of understanding about health insurance concepts and financial illiteracy predict who remains uninsured. Outreach and consumer-education programs should consider these characteristics.

Preparedness of Americans for the Affordable Care Act.

This paper investigates whether individuals are sufficiently informed to make reasonable choices in the health insurance exchanges established by the Affordable Care Act (ACA). We document knowledge of health reform, health insurance literacy, and expected changes in healthcare using a nationally representative survey of the US population in the 5 wk before the introduction of the exchanges, with special attention to subgroups most likely to be affected by the ACA. Results suggest that a substantial share of the population is unprepared to navigate the new exchanges. One-half of the respondents did not know about the exchanges, and 42% could not correctly describe a deductible. Those earning 100-250% of federal poverty level (FPL) correctly answered, on average, 4 out of 11 questions about health reform and 4.6 out of 7 questions about health insurance. This compares with 6.1 and 5.9 correct answers, respectively, for those in the top income category (400% of FPL or more). Even after controlling for potential confounders, a low-income person is 31% less likely to score above the median on ACA knowledge questions, and 54% less likely to score above the median on health insurance knowledge than a person in the top income category. Uninsured respondents scored lower on health insurance knowledge, but their knowledge of ACA is similar to the overall population. We propose that simplified options, decision aids, and health insurance product design to address the limited understanding of health insurance contracts will be crucial for ACA's success.

The Role of Outcome Forecasts in Patients' Treatment Decisions--Evidence from a Survey Experiment on Knee Replacement Surgery.

OBJECTIVE: To analyze the effect of personalized outcome probabilities on treatment decisions. DATA SOURCE: American Life Panel. STUDY DESIGN: We designed an experimental survey that respondents answered by recommending replacement surgery for hypothetical patients diagnosed with knee osteoarthritis. The primary manipulation was whether respondents were given personalized outcome probabilities for the patients. PRINCIPAL FINDINGS: Patient-specific outcome forecasts significantly influenced decisions, with effect sizes comparable to those of physicians' opinions and patient testimonials. The presentation format also affected the probabilities' influence on choices. We did not find evidence that the educational level of subjects affected the weight that they give to outcome probabilities in making recommendations. CONCLUSION: Our study points to a need for more research on the use of patient-specific outcome forecasts.

The Effects of World War II on Economic and Health Outcomes across Europe.

We investigate long-run effects of World War II on socio-economic status and health of older individuals in Europe. We analyze data from SHARELIFE, a retrospective survey conducted as part of SHARE in Europe in 2009. SHARELIFE provides detailed data on events in childhood during and after the war for over 20,000 individuals in 13 European countries. We construct several measures of war exposure-experience of dispossession, persecution, combat in local areas, and hunger periods. Exposure to war and more importantly to individual-level shocks caused by the war significantly predicts economic and health outcomes at older ages.

Contributions of Second Opinions, Outcome Forecasts, and Testimonials to Patient Decisions about Knee Replacement Surgery.

BACKGROUND: Decision aids are now a well-established means of supporting patients in their medical decision making. The widespread use of decision aids invites questions about how their components contribute to patient decisions. OBJECTIVE: The objective of this study was to measure the importance of second opinions, patient-specific outcome forecasts, and patient testimonials relative to patient clinical and socioeconomic factors and the primary physician recommendation on the decision to undergo full knee replacement surgery to treat knee osteoarthritis. METHODS: Middle-aged and older members of the RAND American Life Panel (N = 1616) chose whether to recommend surgery as a treatment for each of 3 hypothetical patients (vignettes) presented in a video-enhanced internet survey. Vignettes randomly sampled levels of scenario attributes. RESULTS: Second opinions, person-specific outcome forecasts, and 2 consistent patient testimonials strongly affected respondents' decision making; a single testimonial, however, did not significantly affect decisions. CONCLUSIONS: Information provided in a decision aid, including person-specific outcome forecasts and testimonials, can affect patient choices. The strong effect of testimonials and respondents' interest in reviewing them reinforces concerns about unwanted influence when testimonials are biased.