The Affordable Care Act's Coverage Impacts in the Trump Era.

The 2016 US presidential election created uncertainty about the future of the Affordable Care Act (ACA) and led to postponed implementation of certain provisions, reduced funding for outreach, and the removal of the individual mandate tax penalty. In this article, we estimate how the causal impact of the ACA on insurance coverage changed during 2017 through 2019, the first 3 years of the Trump administration, compared to 2016. Data come from the 2011-2019 waves of the American Community Survey (ACS), with the sample restricted to non-elderly adults. Our model leverages variation in treatment intensity from state Medicaid expansion decisions and pre-ACA uninsured rates. We find that the coverage gains from the components of the law that took effect nationally-such as the individual mandate and regulations and subsidies in the private non-group market-fell from 5 percentage points in 2016 to 3.6 percentage points in 2019. In contrast, the coverage gains from the Medicaid expansion increased in 2017 (7.0 percentage points) before returning to the 2016 level of coverage gains in 2019 (5.9 percentage points). The net effect of the ACA in expansion states is a combination of these trends, with coverage gains falling from 10.8 percentage points in 2016 to 9.6 percentage points in 2019.

Chance elections, social distancing restrictions, and KENTUCKY's early COVID-19 experience.

Early in the pandemic, slowing the spread of novel coronavirus disease 2019 (COVID-19) relied on non-pharmaceutical interventions. All U.S. states adopted social-distancing restrictions in March and April of 2020, though policies varied both in timing and scope. Compared to states with Democratic governors, those with Republican governors often adopted measures for shorter durations and with greater resistance from their residents. In Kentucky, an extremely close gubernatorial election immediately prior to the discovery of SARS-CoV-2 replaced a Republican incumbent with a Democrat, despite Republicans easily winning all other statewide races. This chance election result offers a unique opportunity to examine the impact of early social distancing policies in a relatively conservative, rural, white-working-class state. Our study begins by estimating an event-study model to link adoption of several common social distancing measures-public school closures, bans on large gatherings, closures of entertainment-related businesses such as restaurants, and shelter-in-place orders (SIPOs)-to the growth rate of cases across counties in the Midwest and South in the early stages of the pandemic. These policies combined to slow the daily growth rate of COVID-19 cases by 9 percentage points after 16 days, with SIPOs and entertainment establishment closures accounting for the entire effect. In order to obtain results with more direct applicability to Kentucky, we then estimate a model that interacts the policy variables with a "white working class" index characterized by political conservatism, rurality, and high percentages of white, evangelical Christian residents without college degrees. We find that the effectiveness of early social distancing measures decreased with higher values of this index. The results imply that the restrictions combined to slow the spread of COVID-19 by 12 percentage points per day in Kentucky's two largest urban counties but had no statistically detectable effect across the rest of the state.

Did COVID-19 change life insurance offerings?

The profitability of life insurance offerings is contingent on accurate projections and pricing of mortality risk. The COVID-19 pandemic created significant uncertainty, with dire mortality predictions from early forecasts resulting in widespread government intervention and greater individual precaution that reduced the projected death toll. We analyze how life insurance companies changed pricing and offerings in response to COVID-19 using monthly data on term life insurance policies from Compulife. We estimate event-study models that exploit well-established variation in the COVID-19 mortality rate based on age and underlying health status. Despite the increase in mortality risk and significant uncertainty, the results generally indicate that life insurance companies did not increase premiums or decrease policy offerings due to COVID-19. Nonetheless, we find some evidence that premiums differentially increased for individuals with very high risk and that some policies were removed for the oldest of the old.

The impact of the Affordable Care Act on health care access and self-assessed health in the Trump Era (2017-2018).

OBJECTIVE: To estimate the impact of the major components of the ACA (Medicaid expansion, subsidized Marketplace plans, and insurance market reforms) on health care access and self-assessed health during the first 2 years of the Trump administration (2017 and 2018). DATA SOURCE: The 2011-2018 waves of the Behavioral Risk Factor Surveillance System (BRFSS), with the sample restricted to nonelderly adults. The BRFSS is a commonly used data source in the ACA literature due to its large number of questions related to access and self-assessed health. In addition, it is large enough to precisely estimate the effects of state policy interventions, with over 300 000 observations per year. DESIGN: We estimate difference-in-difference-in-differences (DDD) models to separately identify the effects of the private and Medicaid expansion portions of the ACA using an identification strategy initially developed in Courtemanche et al (2017). The differences come from: (a) time, (b) state Medicaid expansion status, and (c) local area pre-2014 uninsured rates. We examine ten outcome variables, including four measures of access and six measures of self-assessed health. We also examine differences by income and race/ethnicity. PRINCIPAL FINDINGS: Despite changes in ACA administration and the political debate surrounding the ACA during 2017 and 2018, including these fourth and fifth years of postreform data suggests continued gains in coverage. In addition, the improvements in reported excellent health that emerged with a lag after ACA implementation continued during 2017 and 2018. CONCLUSIONS: While gains in access and self-assessed health continued in the first 2 years of the Trump administration, the ongoing debate at both the federal and state level surrounding the future of the ACA suggests the need to continue monitoring how the law impacts these and many other important outcomes over time.

Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate.

State and local governments imposed social distancing measures in March and April 2020 to contain the spread of the novel coronavirus disease (COVID-19). These measures included bans on large social gatherings; school closures; closures of entertainment venues, gyms, bars, and restaurant dining areas; and shelter-in-place orders. We evaluated the impact of these measures on the growth rate of confirmed COVID-19 cases across US counties between March 1, 2020, and April 27, 2020. An event study design allowed each policy's impact on COVID-19 case growth to evolve over time. Adoption of government-imposed social distancing measures reduced the daily growth rate of confirmed COVID-19 cases by 5.4 percentage points after one to five days, 6.8 percentage points after six to ten days, 8.2 percentage points after eleven to fifteen days, and 9.1 percentage points after sixteen to twenty days. Holding the amount of voluntary social distancing constant, these results imply that there would have been ten times greater spread of COVID-19 by April 27 without shelter-in-place orders (ten million cases) and more than thirty-five times greater spread without any of the four measures (thirty-five million cases). Our article illustrates the potential danger of exponential spread in the absence of interventions, providing information relevant to strategies for restarting economic activity.

Racial and Ethnic Disparities in COVID-19: Evidence from Six Large Cities.

As of June 2020, the coronavirus pandemic has led to more than 2.3 million confirmed infections and 121 thousand fatalities in the USA, with starkly different incidence by race and ethnicity. Our study examines racial and ethnic disparities in confirmed COVID-19 cases across six diverse cities-Atlanta, Baltimore, Chicago, New York City, San Diego, and St. Louis-at the ZIP code level (covering 436 "neighborhoods" with a population of 17.7 million). Our analysis links these outcomes to six separate data sources to control for demographics; housing; socioeconomic status; occupation; transportation modes; health care access; long-run opportunity, as measured by income mobility and incarceration rates; human mobility; and underlying population health. We find that the proportions of Black and Hispanic residents in a ZIP code are both positively and statistically significantly associated with COVID-19 cases per capita. The magnitudes are sizeable for both Black and Hispanic, but even larger for Hispanic. Although some of these disparities can be explained by differences in long-run opportunity, human mobility, and demographics, most of the disparities remain unexplained even after including an extensive list of covariates related to possible mechanisms. For two cities-Chicago and New York-we also examine COVID-19 fatalities, finding that differences in confirmed COVID-19 cases explain the majority of the observed disparities in fatalities. In other words, the higher death toll of COVID-19 in predominantly Black and Hispanic communities mostly reflects higher case rates, rather than higher fatality rates for confirmed cases.

The three-year impact of the Affordable Care Act on disparities in insurance coverage.

OBJECTIVE: To estimate the impact of the major components of the ACA (Medicaid expansion, subsidized Marketplace plans, and insurance market reforms) on disparities in insurance coverage after three years. DATA SOURCE: The 2011-2016 waves of the American Community Survey (ACS), with the sample restricted to nonelderly adults. DESIGN: We estimate a difference-in-difference-in-differences model to separately identify the effects of the nationwide and Medicaid expansion portions of the ACA using the methodology developed in the recent ACA literature. The differences come from time, state Medicaid expansion status, and local area pre-ACA uninsured rates. In order to focus on access disparities, we stratify our sample separately by income, race/ethnicity, marital status, age, gender, and geography. PRINCIPAL FINDINGS: After three years, the fully implemented ACA eliminated 43% of the coverage gap across income groups, with the Medicaid expansion accounting for this entire reduction. The ACA also reduced coverage disparities across racial groups by 23%, across marital status by 46%, and across age-groups by 36%, with these changes being partly attributable to both the Medicaid expansion and nationwide components of the law. CONCLUSIONS: The fully implemented ACA has been successful in reducing coverage disparities across multiple groups.

Effects of the Affordable Care Act on Health Care Access and Self-Assessed Health After 3 Years.

Using data from the Behavioral Risk Factor Surveillance System, we examine the causal impact of the Affordable Care Act on health-related outcomes after 3 years. We estimate difference-in-difference-in-differences models that exploit variation in treatment intensity from 2 sources: (1) local area prereform uninsured rates from 2013 and (2) state participation in the Medicaid expansion. Including the third postreform year leads to 2 important insights. First, gains in health insurance coverage and access to care from the policy continued to increase in the third year. Second, an improvement in the probability of reporting excellent health emerged in the third year, with the effect being largely driven by the non-Medicaid expansions components of the policy.

Medicaid program choice, inertia and adverse selection.

In 2012, Kentucky implemented Medicaid managed care statewide, auto-assigned enrollees to three plans, and allowed switching. Using administrative data, we find that the state's auto-assignment algorithm most heavily weighted cost-minimization and plan balancing, and placed little weight on the quality of the enrollee-plan match. Immobility - apparently driven by health plan inertia - contributed to the success of the cost-minimization strategy, as more than half of enrollees auto-assigned to even the lowest quality plans did not opt-out. High-cost enrollees were more likely to opt-out of their auto-assigned plan, creating adverse selection. The plan with arguably the highest quality incurred the largest initial profit margin reduction due to adverse selection prior to risk adjustment, as it attracted a disproportionate share of high-cost enrollees. The presence of such selection, caused by differential degrees of mobility, raises concerns about the long run viability of the Medicaid managed care market without such risk adjustment.

Medicaid Managed Care and the Health Care Utilization of Foster Children.

A recent trend in state Medicaid programs is the transition of vulnerable populations into Medicaid managed care (MMC) who were initially carved out of such coverage, such as foster children or those with disabilities. The purpose of this article is to evaluate the impact of the transition of foster children from fee-for-service Medicaid coverage to MMC coverage on outpatient health care utilization. There is very little empirical evidence on the impact of managed care on the health care utilization of foster children because of the recent timing of these transitions as well as challenges associated with finding data sets large enough to contain a sufficient number of foster children for such analysis. Using administrative Medicaid data from Kentucky, we use retrospective difference-in-differences analysis to compare the outpatient utilization of foster children transitioned to MMC in one region of the state with foster children in the rest of the state who remained in fee-for-service coverage. We find that the transition to MMC led to a 4 percentage point reduction in the probability of having any monthly outpatient utilization. We also estimate that MMC leads to a reduction in outpatient spending.

Early Impacts of the Affordable Care Act on Health Insurance Coverage in Medicaid Expansion and Non-Expansion States.

The Affordable Care Act (ACA) aimed to achieve nearly universal health insurance coverage in the United States through a combination of insurance market reforms, mandates, subsidies, health insurance exchanges, and Medicaid expansions, most of which took effect in 2014. This paper estimates the causal effects of the ACA on health insurance coverage in 2014 using data from the American Community Survey. We utilize difference-in-difference-in-differences models that exploit cross-sectional variation in the intensity of treatment arising from state participation in the Medicaid expansion and local area pre-ACA uninsured rates. This strategy allows us to identify the effects of the ACA in both Medicaid expansion and non-expansion states. Our preferred specification suggests that, at the average pre-treatment uninsured rate, the full ACA increased the proportion of residents with insurance by 5.9 percentage points compared to 2.8 percentage points in states that did not expand Medicaid. Private insurance expansions from the ACA were due to increases in both employer-provided and non-group coverage. The coverage gains from the full ACA were largest for those without a college degree, non-whites, young adults, unmarried individuals, and those without children in the home. We find no evidence that the Medicaid expansion crowded out private coverage.

Who Gained Insurance Coverage in 2014, the First Year of Full ACA Implementation?

The most significant pieces of the Affordable Care Act (exchanges, subsidies, Medicaid expansion, and individual mandate), implemented in 2014, were associated with sizable gains in coverage nationally that were divided equally between gains in Medicaid and private coverage. These national trends mask heterogeneity in gains by state Medicaid expansion status, age, income level, and source of coverage. Copyright © 2016 John Wiley & Sons, Ltd.

Does Medicaid Managed Care Help Equalize Racial and Ethnic Disparities in Utilization?

OBJECTIVE: To estimate the impact of different forms of Medicaid managed care (MMC) delivery on racial and ethnic disparities in utilization. DATA SOURCE: Longitudinal, administrative data on 101,649 children in Kentucky continuously enrolled in Medicaid between January 1997 and June 1999. Outcomes considered are monthly professional, outpatient, and inpatient utilization. STUDY DESIGN: We apply an intent-to-treat, instrumental variables analysis using the staggered geographic implementation of MMC to create treatment and control groups of children. PRINCIPAL FINDINGS: The implementation of MMC reduced monthly professional visits by a smaller degree for non-whites than whites (3.8 percentage points vs. 6.2 percentage points), thereby helping to equalize the initial racial/ethnic disparity in utilization. The Passport MMC program in the Louisville-centered region statistically significantly reduced disparities for professional visits (closing the gap by 8.0 percentage points), while the Kentucky Health Select MMC program in the Lexington-centered region did not. No substantive impact on disparities was found for either outpatient or inpatient utilization in either program. CONCLUSIONS: We find evidence that MMC has the possibility to reduce racial/ethnic disparities in professional utilization. More work is needed to determine which managed care program characteristics drive this result.

A tale of two cities? The heterogeneous impact of Medicaid managed care.

Evaluating Accountable Care Organizations is difficult because there is a great deal of heterogeneity in terms of their reimbursement incentives and other programmatic features. We examine how variation in reimbursement incentives and administration among two Medicaid managed care plans impacts utilization and spending. We use a quasi-experimental approach exploiting the timing and county-specific implementation of Medicaid managed care mandates in two contiguous regions of Kentucky. We find large differences in the relative success of each plan in reducing utilization and spending that are likely driven by important differences in plan design. The plan that capitated primary care physicians and contracted out many administrative responsibilities to an experienced managed care organization achieved significant reductions in outpatient and professional utilization. The plan that opted for a fee-for-service reimbursement scheme with a group withhold and handled administration internally saw a much more modest reduction in outpatient utilization and an increase in professional utilization.

Physician preference for antiepileptic drug concentration testing.

A four-item questionnaire asked active U.S. members of the Child Neurology Society to value painless antiepileptic drug concentration monitoring, whether members had ordered a saliva level (the best established painless method) in the last year, and whether such levels were available. Value was quantified by time per patient that the physician would willingly expend to arrange for the test. Of 945 questionnaires sent, 544 (58%) were returned. When asked the value of a painless method for children, 286/522 (55%) reported willingness to expend 10 to 30 minutes to arrange the test; 498/522 (95%) would use a painless method if available. When asked the value of an immediate sample at home during a seizure or adverse event, a substantial majority, 370/526 (70%), would make an important donation of their own time to arrange for the sample. Only 5% would not use it. Just 2/544 respondents had obtained a painless (saliva) concentration, and merely 33/544 (6%) perceived such tests as being available. We conclude that child neurologists put a high value on painless antiepileptic monitoring. These data suggest that a painless method of measuring antiepileptic drug concentrations--especially if it could be performed at home--would fulfill an unmet need in the care of children with epilepsy.