Research

This case-control study evaluates the impact of a hospitalization on credit scores for Medicaid beneficiaries in Louisiana stratified by sex, race, and ethnicity.

Hospitalizations can impose financial hardships on families,1,2 contributing to lower credit scores3 and reducing access to credit.1 Non-Hispanic Black and Hispanic patients may struggle more with hospitalization costs due to lower wealth compared with non-Hispanic White patients.

We evaluated the impact of a hospitalization on credit scores for Medicaid beneficiaries in Louisiana, examining effects by sex, race, and ethnicity. Louisiana is a setting well-suited for this research given that it is a Medicaid expansion state, has relatively high levels of personal debt (which inform credit scores), and has a relatively diverse population.

Could policy changes boost economic growth enough and at a low enough cost to meaningfully reduce federal budget deficits? We assess seven areas of economic policy: immigration of high-skilled workers, housing regulation, safety net programs, regulation of electricity transmission, government support for research and development, tax policy related to business investment, and permitting of infrastructure construction. We find that growth-enhancing policies almost certainly cannot stabilize federal debt on their own, but that such policies can reduce the explicit tax hikes, spending cuts, or both that are needed to stabilize debt. We also find a dearth of research on the likely impacts of potential growth-enhancing policies and on ways to design such policies to restrain federal debt, and we offer suggestions for ways to build a larger base of evidence.

The child mental health crisis has been described as the "defining public health crisis of our time." This article addresses three myths about the crisis: (i) the idea that the crisis is new; (ii) the belief that increases in youth suicide mainly reflect deterioration in children's underlying mental health; and (iii) the myth that investments in children have little impact on children's mental health. In fact, the crisis has existed for decades, youth suicides vary asynchronously with other mental health measures and are impacted by external factors such as firearms legislation, and investments can improve child mental health and prevent suicide.

This cohort study assesses the association of implementation and reversal of Supplemental Nutritional Assistance Program (SNAP) work requirements with SNAP enrollment.

Increasing use of biofuels increases the demand for agricultural land. Credible empirical evidence supports the common-sense judgment that this will lead to the conversion of forests and other habitats to generate more cropland, particularly in the tropics, where land conversion is cheapest. However, when analyzing the effects of biofuels on land use, governments frequently use a particular class of economic models, including the popular “GTAP” model, to justify a finding that biofuels will cause little additional land conversion. We argue that the GTAP model does not provide a credible scientific basis for this conclusion because it lacks an econometric basis for its economic parameters, generates physically impossible results by a wide margin, and incorporates several unsupported assumptions that guarantee little land use change, such as constraints on international trade and a failure to account for unmanaged forests.

From 2002 to 2020, there were over 1,000 mergers of US hospitals. During this period, the FTC took enforcement actions against 13 transactions. However, using the FTC’s standard screening tools, we find that 20  percent of these mergers could have been predicted to meaningfully lessen competition. We show that, from 2010 to 2015, predictably anticompetitive mergers resulted in price increases over 5 percent. We estimate that approximately half of predictably anticompetitive mergers had to be reported to the FTC per the Hart–Scott– Rodino Act. We conclude that there appears to be underenforcement of antitrust laws in the hospital sector.

Copyright American Economic Association; reproduced with permission

We analyze the economic consequences of rising US health care prices. By increasing the cost of employer-sponsored health insurance, rising prices serve as a de facto payroll tax on labor. Using exposure to hospital mergers as an instrument, we estimate that a 1% increase in health care prices lowers payroll and employment at non-health-care employers by 0.4%. At the county level, a 1% increase in health care prices reduces labor income by 0.27%, increases flows into unemployment by 1%, and lowers federal income tax receipts by 0.4%. The disemployment effects of rising prices are concentrated among lower- and middle-income workers.

Importance  There is increased interest in public reporting of, and linking financial incentives to, the performance of organizations on health equity metrics, but variation across organizations could reflect differences in performance or selection bias.

Objective  To assess whether differences across health plans in sex- and age-adjusted racial disparities are associated with performance or selection bias.

Design, Setting, and Participants  This cross-sectional study leveraged a natural experiment, wherein a southern US state randomly assigned much of its Medicaid population to 1 of 5 plans after shifting to managed care in 2012. Enrollee-level administrative claims and enrollment data from 2011 to 2015 were obtained for self-identified Black and White enrollees. The analyses were limited to Black and White Medicaid enrollees because they accounted for the largest percentages of the population and could be compared with greater statistical power than other groups. Data were analyzed from June 2021 to September 2024.

Exposures  Plan enrollment via self-selection (observational population) vs random assignment (randomized population).

Main Outcomes and Measures  Annual counts of primary care visits, low-acuity emergency department visits, prescription drug fills, and total spending. For observational and randomized populations, models of each outcome were fit as a function of plan indicators, indicators for race, interactions between plan indicators and race, and age and sex. Models estimated the magnitude of racial differences within each plan and tested whether this magnitude varied across plans.

Results  Of 118 101 enrollees (mean [SD] age, 9.3 [7.5] years; 53.0% female; 61.4% non-Hispanic Black; and 38.6% non-Hispanic White), 70.2% were included in the randomized population, and 29.8% were included in the observational population. Within-plan differences in primary care visits, low-acuity emergency department visits, prescription drug use, and total spending between Black and White enrollees were large but did not vary substantially and were not statistically significantly different across plans in the randomized population, suggesting minimal effects of plans on racial differences in these measures. In contrast, in the observational population, racial differences varied substantially across plans (standard deviations 2-3 times greater than in the randomized population); this variation was statistically significant after adjustment for multiple testing, except for emergency department visits. Greater between-plan variation in racial differences in the observational population was only partially explained by sampling error. Stratifying by race did not bring observational estimates of plan effects meaningfully closer to randomized estimates.

Conclusions and Relevance  This cross-sectional study showed that selection bias may mischaracterize plans’ relative performance on measures of health care disparities. It is critical to address disparities in Medicaid, but adjusting plan payments based on disparity measures may have unintended consequences.