Significance
Policymakers and academics alike tend to focus on the share of Americans who do not have health insurance. Yet, many insured Americans are at risk of losing their coverage. We estimate that although only 12.5% of under-65 Americans were uninsured at any given point in time, twice as many—one in four—were uninsured at some point over a 2-y period. Moreover, the risk of an insured individual losing coverage barely declined after the passage of the landmark 2010 Affordable Care Act. These observations point to the much broader impact of the lack of universal health insurance coverage and indicate that coverage uncertainty—in addition to lack of insurance—should be an important object of attention.
Abstract
Health insurance coverage in the United States is highly uncertain. In the post-Affordable Care Act (ACA), pre-COVID United States, we estimate that while 12.5% of individuals under 65 are uninsured at a point in time, twice as many—one in four—are uninsured at some point over a 2-y period. Moreover, the risk of losing insurance remained virtually unchanged with the introduction of the landmark ACA. Risk of insurance loss is particularly high for those with health insurance through Medicaid or private exchanges; they have a 20% chance of losing coverage at some point over a 2-y period, compared to 8.5% for those with employer-provided coverage. Those who lose insurance can experience prolonged periods without coverage; about half are still uninsured 6 mo later, and almost one-quarter are uninsured for the subsequent 2 y. These facts suggest that research and policy attention should focus not only on the “headline number” of the share of the population uninsured at a point in time, but also on the stability and certainty (or lack thereof) of being insured.
Sign up for PNAS alerts.
Get alerts for new articles, or get an alert when an article is cited.
The United States is the only high-income country without universal coverage. This has prompted considerable policy and academic attention on the share of people in the United States who are uninsured, the costs and benefits of providing them with insurance, and the relative merits of various potential policies that might cover the uninsured.
In this paper, we focus on another, inevitable consequence of the lack of universal coverage, which has received considerably less attention: the risk that the currently insured may become uninsured. We use data from the Medical Expenditure Panel Survey that covers the time period after the landmark Affordable Care Act (ACA) and before the COVID-19 pandemic—from 2014 to 2019—as well as the period 2007 to 2013 prior to the ACA. We focus on individuals under 65. We estimate that although only 12.5% were uninsured in any given month in the post-ACA period, twice as many—one in four—were uninsured at some point over a 2-y period. Moreover, although the risk of being uninsured in any given month fell substantially after the ACA—from 20 to 12.5%—the risk of an insured individual losing coverage barely declined. These results underscore how policies that increase the share of people with insurance at a point in time do not necessarily increase the stability and certainty associated with having insurance.
In the post-ACA period, we also document that the risk of insurance loss is particularly pronounced among those with health insurance through Medicaid or the health insurance exchanges, two forms of coverage that were greatly increased by the ACA. Those with Medicaid or insurance through the exchanges have about a 20% chance of losing coverage at some point over a 2-y period, compared to 8.5% for those with employer-provided coverage. Moreover, for those who lose insurance coverage, the subsequent period without insurance can be prolonged. About half of those who lose coverage remain uninsured for at least 6 mo, and almost one-quarter remain uninsured for at least 2 y.
Perversely, we find that US health insurance coverage—whose very purpose is to provide a measure of certainty in an uncertain world—is itself highly uncertain. The risk of losing insurance reduces its value for risk-averse individuals. It also creates the potential for suboptimal medical choices as individuals may suboptimally shift the timing of their medical treatments to align with when they have insurance coverage. They may also seek treatment under the mistaken impression that they have coverage, or forego treatment under the mistaken impression that they do not. Our findings suggest that these issues should receive more attention both from academic research and public policy.
The rest of the paper proceeds as follows. Section 1 describes the data, Section 2 presents the results, and Section 3 concludes with a discussion of some implications and directions for further work.
1. Data
We focus on the under-65 population, as everyone aged 65 and older is covered by Medicare. This makes the elderly the only group (in the United States) who does not face the risk of losing their insurance coverage. Supplementary Information provides more detail on our analysis samples and variable construction.
Our primary analysis uses the Medical Expenditure Panel Survey (MEPS), a nationally representative annual survey conducted by the Agency for Healthcare Research and Quality at the Department of Health and Human Services. The survey is structured around overlapping cohorts. Each year, a new cohort is surveyed over five rounds of interviews, which are roughly equally spaced over a period of two calendar years, thus creating a 1-y overlap with the next cohort. With these two cohorts, the MEPS interviews approximately 15,000 households annually. The data are drawn primarily from interviews with household respondents who provide information on behalf of all household members.
Our analysis draws on twelve consecutive MEPS cohorts, from the 2007 to 2008 cohort through the 2018 to 2019 cohort. We focus primarily on what we refer to as the “post-ACA” sample, which includes five MEPS cohorts, starting with the 2014 to 2015 cohort and extending through the 2018 to 2019 cohort; we deliberately stop the analysis in 2019 to avoid any potential impacts of COVID-19. We also compare results with a “pre-ACA” sample, which includes six cohorts (the 2007 to 2008 cohort through the 2012 to 2013 cohort).*
For each cohort, we restrict the sample to individuals who respond to all the five survey waves, who are at least 2 y old and less than 65 y old by the end of the second survey year, and who have nonmissing information on insurance in every survey wave. The resultant post-ACA sample consists of 59,784 unique individuals.
Our key variable of interest is an individual’s insurance coverage. This is reported on a monthly basis, based on interview answers which ask the respondents about health insurance coverage each month over the reference period, which is typically the previous 4 to 5 mo. The data also contain information on the source of insurance coverage—such as Medicaid, employer provided, or private exchange—as well as additional demographics including race, ethnicity, education, and medical history.†
Our post-ACA analysis sample is roughly evenly split between individuals under 18, 18 to 30, 31 to 50, and 50 to 64. Fifty-eight percent of the individuals in the sample are White, 20% are Hispanic, 13% are Black, and 6% are Asian or Pacific Islanders.‡ For the sample that is 18 and over, about 35% have a college degree or higher, and about 53% have a high school degree or GED as their highest degree completed. About one-quarter of the sample reports a prior diagnosis of high blood pressure, diabetes, coronary heart disease, stroke, or heart attack (with high blood pressure being, by far, the most common condition).§
Of those who report being insured in the first survey month, about two-thirds have private health insurance provided by an employer or union, about one-fifth have Medicaid, and about 3% have insurance through the ACA private exchanges. The remaining few had insurance through other forms of public coverage, such as Medicare coverage for the disabled.¶ All of these individuals face the risk of insurance loss.
0 Comments