Principal investigator: Bruno Benevit
Original title: Health Insurance and Mortality: Experimental Evidence from Taxpayer Outreach
Authors: Jacob Goldin, Ithai Zvi Lurie and Janet McCubbin
Location of the Intervention: United States
Sample Size: 8,9 million taxpayers
Sector: Health Insurance
Primary Variable of Interest: Health insurance coverage, Mortality
Type of Intervention: Experiment, Dissemination
Methodology: OLS, IV, Logit
Summary
Despite numerous studies on the subject, the relationship between health insurance and mortality remains a widely debated topic in the field of health economics. Assessing the impact of health insurance coverage is crucial for improving the effectiveness of health policies. This study aimed to evaluate the impact of randomly sending informational letters from the U.S. Internal Revenue Service to 3,9 million households that paid a tax penalty for not having health insurance coverage. Affordable care in health insurance coverage and mortality. The results indicate that the intervention increased coverage during the following two years and reduced mortality among middle-aged adults during the same period.
- Policy Problem
The relationship between health insurance and mortality is a constantly debated topic in the health economics literature. According to data from Lurie and Pearce (2019), approximately 9% to 13% of Americans under 65 years of age do not have health insurance coverage for the entire year. The proportion of Americans who are uninsured for at least one month during the year ranges from 21% to 26%. With the aim of expanding health insurance coverage, federal law... Affordable care The American Convention on Health (ACA) was enacted in 2010, making health insurance coverage mandatory for most contributors. In this sense, measuring how health insurance coverage impacts mortality is essential for policymakers.
- Implementation and Evaluation Context
In the United States, health insurance coverage is primarily provided by employers. Government programs such as Medicaid, Medicare or the Veterans Administration represent the second largest source of coverage. American citizens without these types of coverage have the option of enrolling in a plan from Exchange, acquired through your state's health insurance market, or in a plan outside of it. Exchange.
Unlike programs like the MedicaidIndividuals can only enroll in health insurance coverage via Exchange during the open enrollment period for the corresponding year. For example, the enrollment period for the year 2017 ran from November 1, 2016 to January 31, 2017. Additionally, individuals are required to apply for Exchange coverage by the 15th day of the month preceding the month in which coverage is to begin. Most private plans offered by employers also have a similar enrollment period, commonly ending near the end of the calendar year.
In early 2017, the U.S. Internal Revenue Service (IRS) sent informational letters to taxpayers who had previously paid an income tax rate for lack of health insurance coverage, in accordance with the so-called individual mandate provision of the ACA. This intervention allows for the assessment of the causal relationship between coverage and taxpayer mortality.
- Policy/Program Details
Between 2014 and 2018, the federal ACA law made health insurance coverage mandatory for most Americans, resulting in a penalty for non-compliance. Individuals who did not have qualifying health insurance coverage for themselves or a dependent for one or more months during the year were required to report and pay the penalty on their annual income tax return, unless an exemption applied.
The intervention of sending letters to taxpayers was funded by the Department of Health and Human Services (HHS) and executed by the IRS. The letter informed recipients that they had paid a fee in 2015, provided information about the penalty and plan costs for 2017, and offered instructions regarding the possibility of obtaining coverage through the [unclear - possibly a specific program or system]. Exchange and Medicaid.
Recipients who met the criteria for receiving the letter were randomly selected, corresponding to a group that underwent the intervention (86%) and a control group that did not receive the letter (14%). Randomization was stratified by age and sex of the main taxpayer, marital status, number of dependents, income, presence of self-employment income, 2014 penalty/tax status, and whether the taxpayer's state expanded the program. Medicaid and/or participated in the federal market Exchange during 2017.
- Method
The sample used was constructed from IRS income tax returns filed for the year 2015 showing positive penalties related to the ACA. The authors adopted several exclusion criteria for the sample, disregarding recipients with addresses outside the United States and/or enrolled in the coverage of the Exchange in 2015 or 2016. Data on health insurance coverage were extracted from forms submitted annually to the IRS by private and public insurers, employers with their own insurance, and health insurance marketplaces (Form 1095 A/B/C), providing monthly coverage information at the individual level. The forms provide information on monthly coverage and the type of coverage the individual was enrolled in (e.g., whether the coverage was MedicaidMortality data are obtained from Social Security Death Filewhich records the date of all deaths in the United States. The final sample consists of 4,5 million tax returns, corresponding to 8,9 million individuals (primary taxpayer, spouse, and up to 4 dependents).
The analyses in the study considered characteristics of the individuals, the household, the region/state, the IRS penalty status, and coverage from 2014 and 2015. The period covers the years 2015 to 2018, considering the period from 2017 to 2018 as the treatment period. No significant differences were identified in the means of the variables used between the treated and control groups.
The first analysis examines how the intervention affected contributors' coverage, the number of months covered by health insurance, and the probability of being covered for at least one month during the period from 2017 to 2018. Regressions were estimated by splitting the analysis considering the complete sample, only for those insured in all of the first 11 months of 2016, and only for those who were not insured during all of the first 11 months of 2016. Additionally, regressions were conducted under the same splitting criteria, considering only adults aged 45 to 64 at the end of 2017.
The second analysis seeks to identify the effects of the intervention over the months in terms of coverage between the treated and control groups and the difference between the groups. The third analysis presents the effect of the intervention for each type of health insurance coverage, dividing the regressions between the complete sample and adults aged 45 to 64 years.
The following analyses seek to identify how the exogenous variation in health insurance coverage caused by the intervention explains the relationship between coverage and mortality. To this end, using OLS and IV methods, the effects of the intervention on mortality were estimated, verifying whether possible effects occurred as a function of increases in health insurance coverage and the effects of each month of induced coverage. Additionally, several robustness tests were conducted with different sample specifications regarding age, placebo tests, and analyses regarding the heterogeneity of the effect of coverage caused by the intervention over the months. These analyses considered the sample of adults between 45 and 64 years old, the age group with the highest mortality rate.
- Main results
The results of the initial analyses demonstrated that uninsured individuals in any month during 2016 who underwent the intervention were 1,1 percentage points more likely to obtain health insurance coverage in the two years following the intervention compared to the control group, representing a relative increase of 1,9%. On average, the intervention resulted in an average of 0,23 additional months of coverage during this period, or one additional year of coverage for every 52 individuals treated.
Regarding the effects by type of coverage contracted, the effect was mainly due to the subscription to coverages by Exchange and, to a lesser extent, through the program MedicaidThe coverage rate was higher among the treatment group, showing a reduction in the difference between the treated and control groups over the two years following the intervention.
The results of the intervention-induced additional coverage effect showed a reduction in the mortality rate for the group that requested some coverage after the intervention. The mortality rate among previously uninsured individuals aged 45 to 64 was approximately 0,06 percentage points lower in the treatment group than in the control group. This result corresponded to one less death for every 1.587 individuals treated in the two years following the intervention. No effects were identified for groups beyond the 45-64 age range.
Instrumental analysis indicates that the average monthly effect of induced coverage on mortality was approximately -0,18 percentage points over the two years following the intervention. However, the authors caution that the magnitude of the effect on mortality is likely more reliably approximately -0,04 percentage points. The results also show that the annual effect on mortality is less than 12 times the estimated monthly effect due to the concavity in the relationship between coverage and mortality. In other words, the monthly effects decrease over the two-year intervention period.
- Lessons in Public Policy
This article provided important evidence related to the use of disclosure policy strategies to increase health insurance coverage. The results demonstrated that the groups that showed the greatest reductions in mortality were those for whom the benefits of health coverage tend to be small, especially when the disclosure refers to financial penalties for remaining uninsured. According to the authors, these results suggest that inattention, shaping how tax incentives interact with adverse selection in health insurance markets, and causing behavioral frictions that reduce adherence to coverage may be especially concentrated among those who would benefit from enrolling. Given this scenario, disclosure policies of this type are effective in inducing health insurance coverage.
References
LURIE, I.Z.; PEARCE, J. Health Insurance Coverage from Administrative Tax Data. Office of Tax Analysis Working Paper 117, 2019.
