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Abstract
In the United States, most people get health insurance through an employer or through a public program like Medicare or Medicaid. But some people – around 11% of the non-elderly population in 2019 according to estimates in this document – do not have access to public or employer coverage. Rather, these individuals should seek out-of-group coverage, either through the markets established by the Affordable Care Act (ACA) or outside the markets. For many purposes, including evaluating proposals to increase out-of-group enrollment such as the recently adopted increases in ACA grants for Marketplace plans, it is useful to know how many people have out-of-group coverage, what forms of out-of-group coverage they have, how many potential enrollees remain out of school, and how enrollment rates vary by income.
To that end, this paper estimates how many non-elderly people in different income groups had market coverage, non-market coverage that qualifies as minimum essential coverage (MEC) under the ACA, or non-market coverage. non-MEC group (for example, short-term limited-term plans), as well as the number of people without coverage, in 2019. I am focusing on enrolling people who: (1) are not eligible for public or employer coverage; (2) are legally present in the United States; and (3) do not fall within the Medicaid “coverage gap”. This group, which I refer to as the “potential grant recipient” population, is the group most likely to be targeted by efforts to increase out-of-group enrollment such as the recently passed grant expansions. Thus, the estimates for this population are particularly relevant for policy.
It is difficult to estimate non-group enrollment models. Household surveys poorly measure out-of-group coverage since respondents often report other forms of coverage as out-of-group coverage and vice versa, while administrative data lacks the necessary detail. Thus, this article produces estimates by mixing administrative and survey data. Briefly, I start with tabulations of insurance coverage by income in 2016 produced using tax data by Lurie and Pearce, which probably provide the best available snapshot of out-of-group enrollments by income. I then use a combination of survey, administrative and other data to construct raw estimates of enrollment in non-group non-CEM policies (which are not captured in tax data), track the various estimates through 2019. and make other necessary adjustments. In doing so, I pay close attention to the limitations of the survey data sources and mitigate those limitations where possible.
Findings concerning non-group registration models in 2019
Figure ES.1 summarizes this paper’s estimates of out-of-group enrollments and uninsurance among potential non-elderly grant recipients in 2019. The paper highlights four main findings, each of which has important implications for policymakers. politicians, researchers, or both.
Finding # 1: Only half of potential grant recipients were enrolled in a non-group CEM, and participation rates varied only modestly with income. Just over half (52%) of people with incomes below 400% of the Federal Poverty Line (FPL), the income limit for ACA Marketplace grants in 2019, were enrolled in non-group policies. which constitute the MEC. This fraction was slightly lower (49%) among those with incomes above 400% of the FPL. These estimates indicate that there was considerable scope for increasing enrollment in non-group CEMs at all income levels, including income levels where market subsidies were already available from 2019. This involves the recently enacted US bailout law, which both made the grants more generous. for those already eligible and extended them above 400% FPL, has the potential to increase MEC enrollment through income distribution.
Finding # 2: The vast majority of potential grant recipients who did not have a CEM had incomes below 400% of the FPL. Among the potential grant recipients who did not have a non-group CEM, 70% had incomes below 400% of the FPL. Thus, not only is it possible to increase enrollment in out-of-group CMEs among those who were already eligible for grants, but most of the opportunities to increase overall participation lie within this group.
Finding # 3: At lower income levels, potential grant recipients who did not have CEMs were generally uninsured, while at higher income many had non-insured policies. collective without MEC. Among the potential beneficiaries of non-group non-MEC grants who had incomes below 400% of the FPL, 91% were not fully insured, while the remaining 9% held non-group non-MEC policies. In contrast, at higher income levels, 61% held non-group non-MEC policies and only 39% were not fully insured. This suggests that efforts to increase MEC enrollment may do less to improve financial protection at higher income levels, although these improvements may still be substantial as non-MEC policies often provide much less robust coverage. It also suggests that efforts to restrict the availability of policies other than CEMs would have their greatest effects at higher income levels.
Finding # 4: Potential low-income grant recipients with CEMs overwhelmingly had market coverage, while higher income people generally had non-market CEMs. Among potential grant recipients with a non-group CEM, 91% of those with incomes below 400% of FPL were covered by the market, while only 35% had it above 400% of FPL. One implication is that research that focuses only on Marketplace registrants can paint a very misleading picture of out-of-group registration as a whole.
Given that grants were available below 400% of FPL, it is remarkable that anyone at these income levels opted for non-market plans. This could indicate that knowledge of subsidized coverage is incomplete, as some surveys suggest. In addition, out-of-market policies (grandfathered and transitional MEC policies and non-MEC policies) can sometimes be less expensive than subsidized market coverage for healthier, moderate-income registrants.
Findings concerning the trends in non-group registrations from 2016 to 2019
The method used by this article to estimate registrations in 2019 also generates estimates of the evolution of the different categories of registrations between 2016 and 2019. The article highlights two main results.
Finding # 5: Non-market listings fell sharply over this period, especially at lower income levels, while market listings were stable. Figure ES.2 graphically illustrates these trends. The decline in off-market listings is not surprising as premiums for ACA-compliant policies have risen sharply over this period and some healthier people with “grandfather” or “transitional” policies have exited. over time and have probably not been replaced. However, to the extent that this decline was caused by the increase in premiums, it is somewhat surprising that there has not been an offsetting increase in market listings at revenues below 400% of FPL. , when grants were available. This could indicate that people exiting off-market plans were unaware that there was subsidized Marketplace coverage. Alternatively, this could indicate that Marketplace registration was stable overall, as an influx of former non-Marketplace registrants was offset by other factors that reduced Marketplace registration, such as the elimination of the Marketplace listing. individual mandate penalty.
Finding # 6: Subscriptions to non-group, non-MEC policies may have been stable from 2016 to 2019. Existing data sources do not directly measure trends in non-group registrations outside the MEC. To fill this gap, this article constructs an indirect measure of these trends by combining data from insurers’ medical claims reports (MLRs) with data from the American Community Survey (ACS). Since MLR data only captures enrollments in out-of-group CEMs, while ACS plausibly captures all out-of-group enrollments, any difference in enrollment trends shown in MLR and ACS data may reflect changes in non-MEC registrations.
Figure ES.3 shows that the estimates of the change in out-of-group enrollment from 2016 to 2019 derived from MLR and ACS data are very strongly correlated at the state level. Additionally, after using the Pascale, Fertig, and Call results to adjust for known patterns of misrepresentation of coverage in the ACS, the ACS and MLR data show very similar enrollment trends, on average across all states. This finding suggests that enrollment in non-group, non-MEC policies may have changed little over this period.
Stable enrollment in policies other than MEC may be the net effect of offsetting factors. On the one hand, premium increases for ACA-compliant plans, the elimination of the individual tenure policy, and federal regulatory changes favoring short-term plans with limited duration may have increased non-MEC enrollments. However, many states put new restrictions on short-term plans during this time, which may have worked in the opposite direction.
Opportunities to improve registration data outside the group
The paper ends by making two recommendations on how the data on enrollment in out-of-group coverage could be improved in the future. First, the Treasury Department should regularly publish insurance coverage tables by income group based on tax data such as those produced by Lurie and Pearce and consider releasing estimates that are further disaggregated by state of residence.
Second, policymakers should collect better data on enrollment in non-group non-MEC policies. The best approach would be to extend the tax reporting regime that applies to MEC policies to non-MEC policies. Covering all types of non-MEC non-group policies would likely require legislation, but it might be possible to do so for short-term, limited-term policies through administrative action. If it is not possible to extend the tax declaration system, it would be useful to collect at least aggregate information on non-group registrations outside the MEC. The National Association of Insurance Commissioners has collected data on enrollment in short-term, limited-term policies and may collect more, but these efforts should be extended to other types of non-group, non-MEC policies. In addition, this data should be made widely available to researchers and decision-makers, which is currently not planned.
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