Potential Effects Of Eliminating The Individual Mandate Penalty In California

Fung, Vicki; Liang, Catherine Y.; Shi, Julie; Seo, Veri; Overhage, Lindsay; Dow, William H.; Zaslavsky, Alan M.; Fireman, Bruce; Derose, Stephen F.; Chernew, Michael E.; Newhouse, Joseph P.; Hsu, John

doi:10.1377/hlthaff.2018.05161

Cited by 12 publications

(7 citation statements)

References 6 publications

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“…21,33 A direct beneficiary survey indicated that 19% of Californians with non-group coverage say the mandate influenced their decision to purchase insurance. 34 A recent working paper using tax data and discontinuities in the premium penalty find stronger evidence of an effect on coverage, though with modest population-level impacts. 35 In part based on this body of research, the CBO reduced its estimate of the mandate's effects on coverage after the ACA repeal debate in 2017.…”

Section: Part Ii: Effects Of the Aca On Insurance Coveragementioning

confidence: 99%

The Affordable Care Act’s Effects on Patients, Providers and the Economy: What We’ve Learned So Far

Gruber¹,

Sommers²

2019

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As we approach the tenth anniversary of the passage of the Affordable Care Act, it is important to reflect on what has been learned about the impacts of this major reform. In this paper we review the literature on the impacts of the ACA on patients, providers and the economy. We find strong evidence that the ACA's provisions have increased insurance coverage. There is also a clearly positive effect on access to and consumption of health care, with suggestive but more limited evidence on improved health outcomes. There is no evidence of significant reductions in provider access, changes in labor supply, or increased budgetary pressures on state governments, and the law's total federal cost through 2018 has been less than predicted. We conclude by describing key policy implications and future areas for research.

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Section: Part Ii: Effects Of the Aca On Insurance Coveragementioning

confidence: 99%

The Affordable Care Act’s Effects on Patients, Providers and the Economy: What We’ve Learned So Far

Gruber¹,

Sommers²

2019

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“…To address this concern, I present a specification check which restricts my analysis to states in the New England and mid-Atlantic Census divisions to provide a better geographical match between the treatment and control groups. I also estimate a regression that omits the year 2018 from analysis, as the repeal was announced in 2017 and some people may have falsely believed it would be implemented in 2018 (Fung et al, 2019 ).…”

Section: Methodsmentioning

confidence: 99%

The impact of the repeal of the federal individual insurance mandate on uninsurance

Soni

2022

Int J Health Econ Manag.

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The federal individual mandate of the Affordable Care Act, which required people to pay a tax penalty if they did not have health insurance, was repealed in 2019. However, some states implemented state-level insurance mandates which essentially replaced the federal mandate. I use nationally representative survey data from the 2015–19 Annual Social and Economic Supplement to the Current Population Survey to compare the probability of becoming newly uninsured among people living in states without state-level insurance mandates versus states with a mandate, before and after the 2019 repeal. In a sample of 214,821 lower-income, nonelderly adults, the repeal of the federal mandate was associated with a 0.5% point, or 24%, increase in the year-over-year probability of becoming newly uninsured. These results suggest that people respond to financial incentives when making insurance enrollment decisions. In the absence of a federal mandate, state-level mandates may reduce transitions to uninsurance.

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“…These are often hypothetical situations to analyze the decision-making process of individuals. For example, Fung and colleagues (2019), recently used a SP design to estimate that insurance premiums would increase by 4-7% if tax penalty for noncompliance with the Affordable Care Act's individual mandate were eliminated [11]. In this hypothetical context, RP data were not available; the study showed what would happen if such a policy were enacted.…”

Section: How Sp Data Could Be Usedmentioning

confidence: 99%

Using discrete choice experiments to measure preferences for hard to observe choice attributes to inform health policy decisions

Broek-Altenburg

Atherly

2020

Health Econ Rev

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Background: Models of preferences in health services research (HSR) and Health Economics are often defined by readily available information, such as that captured in claims data and electronic health records. Yet many important questions about patient choices cannot be easily studied because of a lack of critical data elements. The objective of this review is to outline the advantages of using stated preferences (SP) data in health services research, and to outline how these methods can be used to evaluate choices that have not yet been offered or studied. Main body: This article focuses on the application of DCE's to relevant policy and health system delivery questions currently relevant, particularly in the United States. DCE's may be helpful to collect data from patient or consumer data that we currently do not have. The article provides examples of research questions that have been answered using SP data collected with a DCE. It outlines how to construct a DCE and how to analyze the data. It also discusses the methodological challenges and emphasizes important considerations regarding the design and estimation methods. SP data can be adopted in situations where we would like to have consumer choice data, but we currently do not. These are often hypothetical situations to analyze the decision-making process of individuals. With SP data it is possible to analyze trade-offs patients make when choosing between treatment options where these hard to measure attributes are important. Conclusion: This paper emphasizes that a carefully designed DCE and appropriate estimation methods can open up a new world of data regarding trade-offs patients and providers in healthcare are willing to make. It updates previous "how to" guide for DCE's for health services researchers and health economists who are not familiar with these methods or have been unwilling to use them and updates previous description of these methods with timely examples.

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Potential Effects Of Eliminating The Individual Mandate Penalty In California

Cited by 12 publications

References 6 publications

The Affordable Care Act’s Effects on Patients, Providers and the Economy: What We’ve Learned So Far

The Affordable Care Act’s Effects on Patients, Providers and the Economy: What We’ve Learned So Far

The impact of the repeal of the federal individual insurance mandate on uninsurance

Using discrete choice experiments to measure preferences for hard to observe choice attributes to inform health policy decisions

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