Research

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.

Importance  Work requirements are a controversial feature of US safety-net programs, with some policymakers seeking to expand their use. Little is known about the demographic, clinical, and socioeconomic characteristics of individuals most likely to be negatively impacted by work requirements.

Objective  To examine the association between work requirements and safety-net program enrollment.

Design, Setting, and Participants  This cohort study included Medicaid and Supplemental Nutrition Assistance Program (SNAP) enrollees in Connecticut. The impact of SNAP work requirements for able-bodied adults without dependents—the target population—was estimated using a triple-differences research design comparing outcomes before and after the policy (first difference) in affected and exempted towns (second difference) between the targeted population and untargeted parents and caregivers (third difference). SNAP and Medicaid enrollment trends were assessed for a 24-month period, and the characteristics of individuals most likely to lose coverage were examined. Data were collected from August 2015 to April 2018, and data were analyzed from August 2022 to September 2024.

Exposures  The reintroduction of SNAP work requirements in 2016.

Main Outcomes and Measures  Proportion of enrollees disenrolled from SNAP and Medicaid.

Results  Of 81 888 Medicaid enrollees in Connecticut, 46 872 (57.2%) were female, and the mean (SD) age was 36.6 (7.0) years. Of these, 38 344 were able-bodied adults without dependents, of which 19 172 were exposed to SNAP work requirements, and 43 544 were parents or caregivers exempted from SNAP work requirements. SNAP coverage declined 5.9 percentage points (95% CI, 5.1-6.7), or 25%, following work requirements. There were no statistically significant changes in Medicaid coverage (0.2 percentage points; 95% CI, −1.4 to 1.0). Work requirements disproportionately affected individuals with more chronic illnesses, targeted beneficiaries who were older, and beneficiaries with lower incomes. Individuals with diabetes were 5 percentage points (95% CI, 0.8-9.3), or 91%, likelier to lose SNAP coverage than those with no chronic conditions; older SNAP beneficiaries (aged 40 to 49 years) with multiple comorbidities were 7.3 percentage points (95% CI, 4.3-11.3), or 553%, likelier to disenroll than younger beneficiaries (aged 25 to 29 years) without chronic conditions; and households with the lowest incomes were 18.6 percentage points (95% CI, 11.8-25.4), or 204%, likelier to lose coverage than the highest income SNAP beneficiaries.

Conclusions and Relevance  In this cohort study, SNAP work requirements led to substantial reductions in SNAP coverage, especially for the most clinically and socioeconomically vulnerable. Work requirements had little effect on Medicaid coverage, suggesting they did not lead to sufficient increases in employment to transition beneficiaries off the broader safety net.

Importance  There is evidence that Republican-leaning counties have had higher COVID-19 death rates than Democratic-leaning counties and similar evidence of an association between political party affiliation and attitudes regarding COVID-19 vaccination; further data on these rates may be useful.

Objective  To assess political party affiliation and mortality rates for individuals during the initial 22 months of the COVID-19 pandemic.

Design, Setting, and Participants  A cross-sectional comparison of excess mortality between registered Republican and Democratic voters between March 2020 and December 2021 adjusted for age and state of voter registration was conducted. Voter and mortality data from Florida and Ohio in 2017 linked to mortality records for January 1, 2018, to December 31, 2021, were used in data analysis.

Exposures  Political party affiliation.

Main Outcomes and Measures  Excess weekly deaths during the COVID-19 pandemic adjusted for age, county, party affiliation, and seasonality.

Results  Between January 1, 2018, and December 31, 2021, there were 538 159 individuals in Ohio and Florida who died at age 25 years or older in the study sample. The median age at death was 78 years (IQR, 71-89 years). Overall, the excess death rate for Republican voters was 2.8 percentage points, or 15%, higher than the excess death rate for Democratic voters (95% prediction interval [PI], 1.6-3.7 percentage points). After May 1, 2021, when vaccines were available to all adults, the excess death rate gap between Republican and Democratic voters widened from −0.9 percentage point (95% PI, −2.5 to 0.3 percentage points) to 7.7 percentage points (95% PI, 6.0-9.3 percentage points) in the adjusted analysis; the excess death rate among Republican voters was 43% higher than the excess death rate among Democratic voters. The gap in excess death rates between Republican and Democratic voters was larger in counties with lower vaccination rates and was primarily noted in voters residing in Ohio.

Conclusions and Relevance  In this cross-sectional study, an association was observed between political party affiliation and excess deaths in Ohio and Florida after COVID-19 vaccines were available to all adults. These findings suggest that differences in vaccination attitudes and reported uptake between Republican and Democratic voters may have been factors in the severity and trajectory of the pandemic in the US.

Exploiting the random assignment of Medicaid beneficiaries to managed care plans, we find substantial plan-specific spending effects despite plans having identical cost sharing. Enrollment in the lowest-spending plan reduces spending by at least 25 percent—primarily through quantity reductions—relative to enrollment in the highest-spending plan. Rather than reducing "wasteful" spending, lower-spending plans broadly reduce medical service provision—including the provision of low-cost, high-value care—and worsen beneficiary satisfaction and health. Consumer demand follows spending: a 10 percent increase in plan-specific spending is associated with a 40 percent increase in market share. These facts have implications for the government's contracting problem and program cost growth.

Review of the Expert and Academic Literature Assessing Impact of Medicare Access and CHIP Reauthorization Act of 2015

There is no published national research reporting child care professionals’ physical health, depression, or stress during the COVID-19 pandemic. Given their central role in supporting children’s development, child care professionals’ overall physical and mental health is important. In this large-scale national survey, data were collected through an online survey from May 22, 2020 to June 8, 2020. We analyzed the association of sociodemographic characteristics with four physical health conditions (asthma, heart disease, diabetes, and obesity), depression, and stress weighted to national representativeness. Sociodemographic characteristics included race, ethnicity, age, gender, medical insurance status, and child care type. Our findings highlight that child care professionals’ depression rates during the pandemic were much higher than before the pandemic, and depression, stress and asthma rates were higher than U.S. adult depression rates during the pandemic. Given the essential work child care professionals provide during the pandemic, policy makers and public health officials should consider what can be done to support the physical and mental health of child care professionals.

We study the impact of changing choice set size on the quality of choices in health insurance markets. Using novel data on enrolment and medical claims for school district employees in the state of Oregon, we document that the average employee could save $600 by switching to a lower cost plan. Structural modelling reveals large “choice inconsistencies” such as non-equalization of the dollar spent on premiums and out of pocket, and a novel form of “approximate inertia” where enrolees are excessively likely to switch to other plans that are close to the current plan on the plan design spreadsheet. Variation in the number of plan choices across districts and over time shows that enrolees make lower-cost choices when the choice set is smaller. We show that a curated restriction of choice set size improves choices more than the best available information intervention, partly because approximate inertia lowers gains from new information. We explicitly test and reject the assumption that this is because individuals choose worse from larger choice sets, or “choice overload”. Rather, we show that this feature arises from the fact that larger choice sets feature worse choices on average that are not offset by individual re-optimization.