Medicaid expansion and the Medicaid undercount in the American Community Survey.

OBJECTIVE: To measure discordance between aggregate estimates of means-tested coverage from the American Community Survey (ACS) and administrative counts and examine the association of discordance with ACA Medicaid expansion. DATA SOURCES: 2010-2016 ACS and counts of Medicaid and Children's Health Insurance Program enrollment from the Centers for Medicare & Medicaid Services. STUDY DESIGN: State-by-year counts of means-tested coverage from the ACS were compared to administrative counts using percentage differences. Discordance was compared for states that did and did not adopt expansion using difference-in-differences. We then contrasted the effect of expansion on means-tested coverage estimated from the ACS with results from administrative data. DATA COLLECTION/EXTRACTION: Survey and administrative data. PRINCIPAL FINDINGS: One year before expansion there was a 0.8 and 4 percent overcount in expansion and nonexpansion states, respectively. By 2016, there was a 10.64 percent undercount in expansion states vs a 0.02 percent undercount in nonexpansion states. The ACS suggests that expansion increased means-tested coverage in the full population by three percentage points, relative to five percentage points suggested by administrative records. CONCLUSIONS: Discordance between the ACS and administrative records has increased over time. The ACS underestimates the impact of Medicaid expansion, relative to administrative counts.

Estimated Costs of a Reinsurance Program to Stabilize the Individual Health Insurance Market: National- and State-Level Estimates.

Reinsurance, an insurance product designed to protect health insurers against the financial risk of covering high-cost enrollees, has attracted bipartisan policy interest as a mechanism to stabilize individual health insurance markets. Three states-Alaska, Minnesota, and Oregon-have implemented state-based reinsurance programs under the Affordable Care Act's 1332 State Innovation Waivers, and reinsurance waivers have been approved though not yet enacted in Maine, Maryland, New Jersey, and Wisconsin. In this article, we estimate the costs of implementing national and state-based reinsurance programs using health spending data from the 2007-2016 Medical Expenditure Panel Survey and state demographic and health insurance coverage data from the 2015-2017 Current Population Survey Annual Social and Economic Supplement. We project that a reinsurance program with an 80% payment rate for expenditures between $40,000 and $250,000 would cost $30.1 billion from 2020-2022. We observed considerable variation in reinsurance programs and estimated costs between the 4 states we examined: California, Florida, Illinois, and Texas. Our projections provide updated estimates of the costs of implementing federal reinsurance programs for the individual health insurance market.

Community Characteristics and Qualified Health Plan Selection during the First Open Enrollment Period.

OBJECTIVE: To examine state and community factors that contributed to geographic variation in qualified health plan selection during the first open enrollment period. DATA SOURCES/STUDY SETTING: Administrative data on qualified health plan selections at the ZIP code area merged with survey estimates from the American Community Survey. STUDY DESIGN: Descriptive and regression analyses. DATA COLLECTION/EXTRACTION METHODS: Data were generated by healthcare.gov and from a household survey. PRINCIPAL FINDINGS: Thirty-one percent of the variation in qualified health plan selection ratios resulted from between-state differences, and the rest was driven by local area differences. Education, language, age, gender, and the ethnic composition of communities contributed to disparate levels of plan selection. Medicaid expansion states had a qualified health plan selection ratio that was 4.4 points lower than non-Medicaid expansion states, controlling for covariates. CONCLUSIONS: Our results suggest community-level differences in the intensity or receptiveness to outreach and enrollment activities during the first open enrollment period.

Residential High-Speed Internet Among Those Likely to Benefit From an Online Health Insurance Marketplace.

Using data from the 2013 American Community Survey, we found that 24.3 million people (about 1 in 4) who were either eligible for Medicaid/Children's Health Insurance Program (CHIP) or appeared likely to shop for Qualified Health Plan (QHP) lacked residential high-speed Internet. Specifically, 28.6% or 18.9 million people eligible for Medicaid/CHIP and 17.1% or 5.5 million people who appeared likely to shop for a QHP did not have high-speed Internet in the home. For both the Medicaid/CHIP eligible and those likely to shop for a QHP, the proportion of people living in households without Internet varied substantially by race, geography, and other socio-demographic characteristics.

Millions of Americans may be eligible for Marketplace coverage outside open enrollment as a result of qualifying life events.

Federal regulations establish special enrollment periods--times outside of open enrollment periods--during which people may enroll in or change their health insurance plans offered through the federal and state-based exchanges, or Marketplaces. To be eligible, a person must experience a shift in income or another "qualifying life event," such as a change in marital status or the number of dependents, or the loss of minimum essential health coverage. We produced an upper-bound estimate that 3.7 million nonelderly adults with coverage through a federal or state Marketplace could have experienced a qualifying life event and become eligible for a special enrollment period because of income shifts. In addition, more than 8.4 million nonelderly adults who did not have Marketplace coverage--three-quarters of whom had no insurance--became eligible for a special enrollment period as a result of other qualifying life events. Many if not most of these people may be unaware of their eligibility. In states that did not expand Medicaid eligibility, we estimated that 1.9 million people experienced income shifts outside of the open enrollment period that would make them eligible for Marketplace subsidies. However, because they were uninsured or had nongroup coverage (instead of Medicaid) during the most recent open enrollment period, they had to wait until the next period to enroll in a Marketplace plan.

Measurement Error in Public Health Insurance Reporting in the American Community Survey: Evidence from Record Linkage.

OBJECTIVE: Examine measurement error to public health insurance in the American Community Survey (ACS). DATA SOURCES/STUDY SETTING: The ACS and the Medicaid Statistical Information System (MSIS). STUDY DESIGN: We tabulated the two data sources separately and then merged the data and examined health insurance reports among ACS cases known to be enrolled in Medicaid or expansion Children's Health Insurance Program (CHIP) benefits. DATA COLLECTION/EXTRACTION METHODS: The two data sources were merged using protected identification keys. ACS respondents were considered enrolled if they had full benefit Medicaid or expansion CHIP coverage on the date of interview. PRINCIPAL FINDINGS: On an aggregated basis, the ACS overcounts the MSIS. After merging the data, we estimate a false-negative rate in the 2009 ACS of 21.6 percent. The false-negative rate varies across states, demographic groups, and year. Of known Medicaid and expansion CHIP enrollees, 12.5 percent were coded to some other coverage and 9.1 percent were coded as uninsured. CONCLUSIONS: The false-negative rate in the ACS is on par with other federal surveys. However, unlike other surveys, the ACS overcounts the MSIS on an aggregated basis. Future work is needed to disentangle the causes of the ACS overcount.

Implementing federal health reform in the States: who is included and excluded and what are their characteristics?

OBJECTIVE: To estimate the characteristics and number of nonelderly adults eligible and ineligible for Affordable Care Act (ACA) expansions. DATA SOURCES AND SETTINGS: Two secondary data sources are used in this analysis: the 2008 Panel of the Survey of Income and Program Participation (SIPP) and the 2009 American Community Survey (ACS). STUDY DESIGN: We use multiple imputation to incorporate model-based uncertainty into the prediction of immigration status into the ACS from the SIPP. Key variables include place of birth, year of entry to the U.S., and health insurance coverage. DATA COLLECTION/EXTRACTING METHODS: No primary data are used in this study. PRINCIPLE FINDINGS: We estimate that potentially 3.5 million nonelderly adults will be excluded from the ACA Medicaid Expansion and 2 million from the health insurance exchanges because of their immigration status. We also find significant differences in estimates of excluded nonelderly adults across states. CONCLUSIONS: Over 15 percent of income-eligible uninsured nonelderly adults will be potentially excluded from the ACA coverage expansions due to their immigration status. Policy makers must be careful to exclude ineligible nonelderly adults before estimating the impact of the ACA on coverage rates.