IMPACT ON MEMBERS AND PREMIUMS OF COVERING THE COST OF THE UNFUNDED COST SHARING REDUCTION PROGRAM

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IMPACT ON MEMBERS AND PREMIUMS OF COVERING THE COST OF THE UNFUNDED COST SHARING REDUCTION PROGRAM FEBRUARY 14, 2019 Kurt Giesa, FSA, MAAA Peter Kaczmarek, FSA, MAAA

Contents Contents 1. Executive Summary... 1 2. Background... 2 3. Data, Methodology, and Results... 5 4. Results... 6 5. Considerations, Limitations, and Acknowledgement of Qualifications... 9 Oliver Wyman

Executive Summary 1. Executive Summary At the request of the BlueCross and BlueShield Association, we have made estimates of the impact on premium and enrollment of requiring issuers to spread the cost of unfunded Cost Sharing Reduction payments (CSR payments) across all ACA policies, both on- and off- Exchange. We will refer to this approach to covering the cost of unfunded CSRs as broad loading. Broad loading contrasts with what occurred in most states in 2018 (and will continue in 2019), where the cost of the unfunded CSR program was recovered by increasing premiums only for on-exchange, silver plans. We refer to this approach as silver loading. Our primary findings are the following: We expect that under broad loading, premiums for those who are not eligible for tax credits will increase by 10% nationwide compared to premiums under silver loading. Presubsidy premiums for those who are eligible for tax credits will decline by roughly 1% under broad loading. As a result of the increase in premiums for those individuals who are not eligible for tax credits, we expect roughly 0.9 million fewer people to have coverage in the non-group market, and we expect that this enrollment loss will occur mostly among individuals who are not eligible for premium tax credits. We expect the premium rate changes for the population not eligible for tax credits to vary at the state level. For example, because Minnesota and New York operate a Basic Health Program, few members in the ACA, non-group market are eligible for CSR benefits in those states and the impact of broad loading would be small. This contrasts with those states that have chosen not to expand their Medicaid programs. In states like Texas, Oklahoma, Alabama, and Georgia, premium increases for non-subsidized enrollees are expected to be higher than the nationwide average, as a high proportion of individuals in the non-group, ACA market are eligible for CSR benefits. Oliver Wyman 1

Background 2. Background In October 2017, the administration announced that it would stop reimbursing issuers for CSR payments that, under the ACA, issuers are required to make to reduce cost-sharing, such as copayments, coinsurance and deductibles, for covered members with incomes below 250% of the federal poverty level (FPL) who purchase silver coverage on the Exchanges. These reductions in cost-sharing are built into the products that health plans must offer to eligible members, providing a direct benefit to these members when they access health care services. While state regulators and issuers approaches to dealing with the loss of federal funding for the CSR program varied, many states directed or allowed issuers to adjust their 2018 premiums by building the cost of the CSR program into their on-exchange, silver premiums, which again we refer to as sliver loading. In Figure 1, we show the impact of this silver loading strategy on average premiums in the 39 states using the federal Exchange platform, healthcare.gov. Figure 1 Average monthly premiums for enrollees prior to tax credits Source: https://www.gao.gov/assets/700/693362.pdf. Figure 1 shows that premiums for bronze and gold plans increased by an average of roughly 23% in 2018. This increase includes the actuaries expectations for medical claims cost trends and changes in the morbidity of the single risk pool. The increase likely also reflects actuaries expectations for the effects of the regulatory uncertainty and operational changes that issuers were facing in the first half of 2017 as they were developing their 2018 premiums, such as the significant reduction in federal spending for marketing and outreach, and efforts to alter the ACA Oliver Wyman 2

Background in the U.S. Congress. 1,2 Compared to the increase for bronze and gold plans, premiums for silver plans increased by 45%, or an additional 18%, over bronze and gold plans. The average cost of silver coverage in 2018 was almost equal to the cost of gold coverage. Issuers used this additional 18% premium increase on silver plans to cover the cost of providing CSR benefits which are only available to individuals with incomes less than 250% FPL purchasing silver coverage on the Exchanges. Silver loading allows individuals who are not eligible for CSR benefits to purchase off-exchange silver coverage or gold or bronze coverage and thereby avoid having to pay for CSR benefits they do not receive. Because tax credits available under the ACA are based on the difference between the cost of the second-lowest-cost silver plan and a fixed percentage of an individual s income, silver loading has the effect of increasing the value of tax credits for those eligible for them. For those eligible for them, these larger tax credits generally resulted in lower net premiums in 2018 than in 2017. We show this in Figure 2 for on-exchange enrollees in the 39 states using the healthcare.gov platform. Figure 2 Average monthly post-subsidy premiums for enrollees with tax credits Source: https://www.gao.gov/assets/700/693362.pdf. Because individuals eligible for tax credits contribute a fixed percentage of their incomes toward the cost of coverage, the net premiums after tax credits in 2018 would have increased because of the increase in individuals incomes and the increase in the federal poverty level. As Figure 2 shows, however, due to silver loading, net premiums after tax credits for silver coverage actually 1 https://www.cms.gov/newsroom/press-releases/cms-final-report-shows-118-million-consumers-enroll-2018- exchange-coverage-nationwide 2 https://www.congress.gov/bill/115th-congress/house-bill/1628 Oliver Wyman 3

Background decreased by 13% in 2018. Under silver loading, the spread between the lowest-cost and second-lowest cost silver plan expanded, and this led to a reduction in net premiums for the lowest-cost silver plan in most markets. The net premiums for bronze and gold coverage declined by substantially more than the net premiums for silver coverage on both a percentage and an absolute basis. This resulted in a shift in members away from silver and into bronze and gold coverage, as we show in Figure 3. Figure 3 Plan selection by metal (1,000,000s and percentage of members) 3 Source: https://www.gao.gov/assets/700/693362.pdf. While the initial total on-exchange plan selection during open enrollment in the healthcare.gov states decreased by 0.5 million in 2018, the relatively large reductions in net premiums after tax credits for bronze and gold coverage we illustrated in Figure 2 resulted in roughly 0.7 million more selecting those coverages in 2018 than in 2017. Of particular note shown in Figure 2 is the 0.5 million increase in the number of individuals choosing bronze coverage. In prior work, we described how silver loading could result in free bronze coverage, particularly for older individuals in rating areas where premiums are high. 4 This increase in the number of individuals purchasing on-exchange bronze coverage may result, at least partially, from the availability of free bronze coverage. It may also represent individuals reacting to double-digit premium increases on the ACA Exchanges by purchasing policies with less rich benefits and lower premiums, particularly those who are not eligible for tax credits. 3 Please note that the plan selection during open enrollment might differ from effectuated or actual enrollment during the entire calendar year. We assume in this paper that the metal distribution shown in Figure 3 is representative of the actual distribution in 2018. 4 https://health.oliverwyman.com/2017/05/impact_defunding_csr_payments.html Oliver Wyman 4

Data, Methodology, and Results 3. Data, Methodology, and Results Data and Methodology We used the Oliver Wyman Microsimulation Model to develop the results we present here. 5 We have used this model to study the impact on health insurance markets, and the non-group, ACA market in particular, of a wide variety of policies, from 1332 waivers to alternative tax credit structures. For this work, we first modeled the 2019 ACA market as we expect it will operate in 2019 under current law and regulation, including the elimination of the mandate penalty, the availability of short-term limited duration plans offering coverage up to 364 days, and silver loading in every state. In our modeling, we assumed individuals purchase the lowest cost silver plan available in their market. We then developed model estimates assuming the cost of unfunded CSR payments must be spread across all ACA policies, both off- and on-exchange. We point out here that it may be difficult for regulators to implement broad loading. Because CSR benefits are only available to individuals buying coverage on-exchange, those issuers selling off-exchange policies or selling only off-exchange will have no CSR liability. We assume that regulators will have some mechanism, such as revising risk adjustment, to collect funds from off-exchange policies and to redirect those funds to on-exchange issuers to help the on-exchange issuers cover the cost of unfunded CSR payments. Without such collections, on-exchange issuers would need to raise the silver premiums more than we show here because they would not be receiving funds from off-exchange coverage. In addition, they would have an incentive to avoid being the secondlowest-cost or lowest-cost silver plan to avoid CSR enrollees whose premiums do not cover costs, by either charging a very high silver premium or by not offering on-exchange coverage at all. 5 For a description of the Oliver Wyman Microsimulation Model, and the data used in producing these results, see https://www.oliverwyman.com/content/dam/oliverwyman/v2/publications/2017/aug/market%20stabilization_final%20version.pdf Oliver Wyman 5

Results 4. Results In Figure 4, we show the enrollment in the non-group market in 2019 under two alternative scenarios; first, the current law baseline, which includes silver loading, and second, assuming broad loading. Figure 4 Non-group enrollment by subsidy eligibility under silver and broad loading in 2019 (1,000,000s) Our model produces a decline in total, nationwide enrollment of 0.9 million individuals in the non-group market including both the healthcare.gov states and the states operating their own Exchanges. We estimate that the number of individuals with transitional and grandfathered policies would be higher by about 0.1 million under broad loading because the broad loading increases all ACA premiums, and not just on-exchange silver premiums, so that retaining a grandfathered or transitional policy would be more attractive. We show no change in enrollment among those eligible for tax credits. These individuals are responsible for paying a fixed percentage of their incomes towards the cost of coverage and so do not react strongly to the modeled changes in premiums. The primary effect of broad loading is to increase the cost of coverage for those not eligible for tax credits. We show a reduction of roughly 1.0 million in the number of individuals who are not eligible for tax credits due to having incomes greater than 400% FPL. This loss of enrollment is the result of higher premiums under the broad loading approach to covering the cost of unfunded CSR payments. Oliver Wyman 6

Results In Figure 5, we show the change in premiums going from silver loading to broad loading in 2019. Figure 5 Monthly silver premiums per member in 2019 by eligibility for tax credits under silver and broad loading in 2019 all states We show that premiums increase by 10% for individuals without access to tax credits, and premiums before tax credits decrease by roughly 1% for individuals who are eligible for those credits. There are three primary forces leading to the relatively large increase in premiums for nonsubsidized individuals and the relatively small premium decrease for those who are eligible for tax credits. Two of these factors relate to the relative share of premium coming from subsidized and non-subsidized individuals, and the other relates to a change in the morbidity of the single risk pool. The premium revenue the non-subsidized individuals contribute to the market accounts for just 15% of total market premium under broad loading. Our model projects that under broad loading, less than one in five enrollees in the non-group, ACA market will not receive tax credits (see Figure 4). Further, non-subsidized individuals tend to have lower premiums than subsidized individuals (Figure 5) due to demographic and other differences. These two market forces combine so that premiums for individuals not eligible for tax credits must increase by roughly $7 for every $1 reduction in the premiums for those eligible for tax credits. Oliver Wyman 7

Results The remaining factor driving the premium changes we show in Figure 5 is that the 1.0 million individuals not eligible for tax credits lost from the ACA market have lower morbidity than the market as a whole, so their loss leads to an increase in premiums for all insureds who remain in the single risk pool, both those who are receiving tax credits and those who are not. These three forces, taken together, produce the 10% increase in premiums for non-subsidized individuals and the 1% premium decrease for those receiving tax credits. In our modeling, reducing premiums for those eligible for premium subsidies does reduce federal spending for tax credits, but the reduction is small, on the order of 1% of federal spending for tax credits under silver loading. Oliver Wyman 8

Considerations, Limitations, and Acknowledgement of Qualifications 5. Considerations, Limitations, and Acknowledgement of Qualifications We prepared this report for the BlueCross and BlueShield Association for the purposes of illustrating the impact of broad loading on the non-group, ACA market. This report is not to be used for any other purpose. In this work, we have relied on publicly available data and information without independent audit. Though we have reviewed the data for reasonableness and consistency, we have not audited or otherwise verified this data. It should also be noted that our review of data may not always reveal imperfections. We have assumed that the data and information we relied upon are both accurate and complete. The results of our analysis are dependent on this assumption. If this data or information is inaccurate or incomplete, our findings and conclusions may need to be revised. Our conclusions are based on data and information that we believe are appropriate for these purposes, and on the estimation of the outcome of many contingent events. Our estimates make no provision for extraordinary future events not sufficiently represented in historical data on which we have relied or which are not yet quantifiable. The sources of uncertainty affecting our estimates are numerous and include items such as changes in policies beyond those modeled here such as changes in outreach and advertising, changes in taxes, and changes in federal and state funding. While this analysis complies with applicable Actuarial Standards of Practice, users of this analysis should recognize that our projections involve estimates of future events, and are subject to economic and statistical variations from expected values. We have not anticipated any extraordinary changes to the legal, social, or economic environment that might affect the results of our modeling. For these reasons, no assurance can be given that the emergence of actual results will correspond to the projections in this analysis. The authors of this report are members of the American Academy of Actuaries and meet that body s Qualifications Standards to perform this work and render the opinions expressed in this report. Oliver Wyman 9

Oliver Wyman 411 East Wisconsin Avenue, Suite 1300 Milwaukee, WI 53202-4419 414 223 2280 414 688 0686 kurt.giesa@oliverwyman.com Oliver Wyman Actuarial Consulting, Inc. (DE)