Reasons For The Wide Variation In Medicaid Participation Rates Among States Hold Lessons For Coverage Expansion In 2014

Sommers, Benjamin D.; Tomasi, Meredith Roberts; Swartz, Katherine; Epstein, Arnold M.

doi:10.1377/hlthaff.2011.0977

Cited by 91 publications

(78 citation statements)

References 20 publications

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“…One reason is that many of those made eligible for public insurance already had private insurance coverage. Complex application processes and informational barriers also contribute to low participation (Sommers, Tomasi, Swartz, & Epstein, 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

Premium subsidies, the mandate, and Medicaid expansion: Coverage effects of the Affordable Care Act

Frean

Gruber

Sommers

2017

Journal of Health Economics

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339

144

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Using premium subsidies for private coverage, an individual mandate, and Medicaid expansion, the Affordable Care Act (ACA) has increased insurance coverage. We provide the first comprehensive assessment of these provisions' effects, using the 2012-2015 American Community Survey and a triple-difference estimation strategy that exploits variation by income, geography, and time. Overall, our model explains 60% of the coverage gains in 2014-2015. We find that coverage was moderately responsive to price subsidies, with larger gains in state-based insurance exchanges than the federal exchange. The individual mandate's exemptions and penalties had little impact on coverage rates. The law increased Medicaid among individuals gaining eligibility under the ACA and among previously-eligible populations ("woodwork effect") even in non-expansion states, with no resulting reductions in private insurance. Overall, exchange premium subsidies produced 40% of the coverage gains explained by our ACA policy measures, and Medicaid the other 60%, of which 1/2 occurred among previously-eligible individuals. Americans to obtain insurance (with several exemptions, most notably related to affordability). KeywordsThese principal pieces of the ACA took effect in January 2014. 1 National data from multiple sources strongly support the notion that the ACA has reduced the uninsurance rate substantially beginning in 2014, reaching an historic low by 2015 (Cohen & Martinez, 2014;Smith & Medalia, 2015;Sommers, Gunja, Finegold, & Musco, 2015). This drop has generally been attributed to the ACA, but most analyses of the ACA to date have 1 The earliest coverage expansion enacted under the ACA was the dependent coverage provision, which mandated that private insurers allow parents to cover their children on their insurance until age 26. This provision took effect September 2010. We do not examine this policy here, since it had essentially reached steady-state by 2012 and has already been examined thoroughly elsewhere (Antwi, Moriya, & Simon, 2013). 4 been largely descriptive (Cohen & Martinez, 2014;Long et al., 2014) or limited to a particular aspect of the ACA such as the Medicaid expansion (Black & Cohen, 2015;Kaestner, Garrett, Gangopadhyaya, & Fleming, 2015;Wherry & Miller, 2016). No studies have disentangled the different coverage effects of the ACA's various provisions. Even as the 2016 election results cast uncertainty over the ACA's future, these issues remain critically important to understanding the potential impact of a partial or complete rollback of the law, as well as the potential consequences of future state or federal efforts to expand coverage.In this paper, we provide the first comprehensive model that identifies the causal impact of the ACA's numerous provisions on insurance coverage. In doing so, we also offer an empirical template for future research on this wide-ranging law. We use data from the American Community Survey (ACS) for the two years before and two years after full ACA implementation. We estimate rich mod...

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Section: Literature Reviewmentioning

confidence: 99%

Premium subsidies, the mandate, and Medicaid expansion: Coverage effects of the Affordable Care Act

Frean

Gruber

Sommers

2017

Journal of Health Economics

Self Cite

339

144

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“…X i is a vector of individual-level variables that related to the probability of being eligible for Medicaid and/or the probability of enrollment conditional on eligibility. Previous research demonstrates that Medicaid take-up is highly variable by eligibility group, with high participation rates among eligible disabled adults (76%) and children (85%), with much lower rates among parents (57%) and childless adults (38%) (Kenney, Lynch et al 2011;Sommers, Tomasi et al 2012). Variation across states is equally pronounced, with state-specific take-up rates among adults ranging from 44% to 88% (Sommers, Tomasi et al 2012).…”

Section: Iiib3 Stochastic Model: Propensity Score Matching With Ranmentioning

confidence: 99%

“…Previous research demonstrates that Medicaid take-up is highly variable by eligibility group, with high participation rates among eligible disabled adults (76%) and children (85%), with much lower rates among parents (57%) and childless adults (38%) (Kenney, Lynch et al 2011;Sommers, Tomasi et al 2012). Variation across states is equally pronounced, with state-specific take-up rates among adults ranging from 44% to 88% (Sommers, Tomasi et al 2012). To model these issues, our propensity scores are stratified by eligibility pathway, and then include the following covariates: age, self-reported health (on a five point scale), educational attainment, citizenship, employment status, student status, race, ethnicity, gender, marital status, imputed pregnancy status, 7 and the additional income and eligibility measures listed below.…”

Section: Iiib3 Stochastic Model: Propensity Score Matching With Ranmentioning

confidence: 99%

“…Second, prior research demonstrates that among eligible individuals take-up of Medicaid varies widely based on demographic factors and state of residence (Sommers, Tomasi et al 2012), which is best modeled using the flexibility of interaction terms between state of residence and imputed eligibility.…”

Section: Iiib3 Stochastic Model: Propensity Score Matching With Ranmentioning

confidence: 99%

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The poverty-reducing effect of Medicaid

Sommers

Oellerich

2013

Journal of Health Economics

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Abstract:Medicaid provides health insurance for 54 million Americans. Using the Census Bureau's supplemental poverty measure (which subtracts out-of-pocket medical expenses from family resources), we estimated the impact of eliminating Medicaid. In our counterfactual, Medicaid beneficiaries would become uninsured or gain other insurance. Counterfactual medical expenditures were drawn stochastically from propensity-score-matched individuals without Medicaid. While this method captures the importance of risk protection, it likely underestimates Medicaid's impact due to unobserved differences between Medicaid and non-Medicaid individuals. Nonetheless, we find that Medicaid reduces out-of-pocket medical spending from $871 to $376 per beneficiary, and decreases poverty rates by 1.0% among children, 2.2% among disabled adults, and 0.7% among elderly individuals. When factoring in institutionalized populations, an additional 500,000 people were kept out of poverty. Overall, Medicaid kept at least 2.6 million -and as many as 3.4 million -out of poverty in 2010, making it the U.S.'s third largest anti-poverty program.

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“…As the U.S. Accountable Care Act (ACA) rolls out, policy experts have described the wide variation in Medicaid programs from state to state. [38][39][40] These variations translate into differences in benefit packages for the poor. 41 Greater than 3 out of 4 respondents that did not receive a necessary medication reported that they could not afford it in this study.…”

Section: Discussionmentioning

confidence: 99%

Association of increased emergency rooms costs for patients without access to necessary medications

Watanabe

Ney

2015

Research in Social and Administrative Pharmacy

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Background: Prescription medications are an important component of chronic disease management. They are vital in preventing unnecessary ER visits. However, few studies have examined the association between patients' self-reported inability to receive necessary medications and emergency room costs. Objectives: The study objectives were to: 1) determine differences in ER costs based on self-reported ability to obtain necessary medications. 2) identify differences in ER costs based on self-reported ability to obtain necessary medications among medication users. The association was also examined by insurance category. Methods: Respondent data from 10 years (2002-2011) of the U.S. Medical Expenditure Panel Survey was analyzed. The models employed estimated the association of respondents reporting being 'unable to receive necessary medications' on ER expenditures. Secondarily, the relationship was assessed by insurance category: private, public, and uninsured. Two-part cost regression models with bootstrapped estimates to produce 95% confidence intervals of cost differences were applied for these analyses. Significance was set at a ¼ 0.05. Analyses were completed using SAS 9.4 (Cary, NC) and Stata 13 (College Station, TX). Estimates were in 2011 US dollars. Results: People unable to receive necessary medications experienced increased average annual ER costs of $46.62 with 95% a confidence interval [CI] of 34.76-58.49) compared to patients able to receive necessary medications. By insurance category, respondents unable to receive necessary medications experienced increased ER costs ), for Publically Insured, Privately Insured, and Uninsured, respectively. Findings were similar for those already using medications. Conclusions: Inability to obtain necessary medications is associated with increased emergency room costs. Those with public insurance have a larger increase in ER costs if they are without necessary medications compared to those insured privately or without insurance.

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Reasons For The Wide Variation In Medicaid Participation Rates Among States Hold Lessons For Coverage Expansion In 2014

Cited by 91 publications

References 20 publications

Premium subsidies, the mandate, and Medicaid expansion: Coverage effects of the Affordable Care Act

Premium subsidies, the mandate, and Medicaid expansion: Coverage effects of the Affordable Care Act

The poverty-reducing effect of Medicaid

Association of increased emergency rooms costs for patients without access to necessary medications

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