CHIPRA Mandated Evaluation of Express Lane Eligibility: First Year Findings. D. Implications of First-Year Findings for State and Federal Policy

12/01/2012

Although first-year findings are tentative, they have helped identify several important policy issues that future evaluation activities can address. For example, we need to better understand ELE’s effects on retention outcomes and whether state policy or process modifications could affect retention through ELE versus standard routes. First-year descriptive findings about retention are mixed: in Iowa Medicaid, retention rates were higher for those entering through ELE, but in Louisiana and in Iowa’s separate CHIP program, retention rates were lower. In Alabama, there was no discernible difference in retention between ELE and those who entered through the standard route. It is likely that, in Iowa’s separate CHIP program, the cost-sharing policy in CHIP is affecting retention rates. Because Louisiana changed its policy regarding ELE renewal, moving from affirmative consent to an opt-in policy for data matching, we are eager to study the effect of this state policy change on retention rates there, and will be able to do so in the second year.

Another policy of interest at the Federal level is assessing the effects, if any, of linking the CHIPRA performance bonuses to ELE. As noted earlier, Congress specified that states that implemented at least five out of eight simplifications (one of which was ELE) and that increased Medicaid enrollment by a specified threshold could qualify for bonus funds. These funds represent a significant Federal investment: more than $500 million has been awarded in the first three years to 23 states. All 9 ELE states are among these 23 states; 3 of them (Georgia, Maryland, and South Carolina) needed ELE to meet the 5 of 8 threshold (the other states would have met the 5 of 8 policy criteria without having ELE in place). The case studies will help us better understand whether the availability of funds acted as an incentive to implement ELE, and further assess whether this new investment in states that implemented ELE is warranted or needs adjustment, given enrollment outcomes using ELE methods.

A further important question for future evaluation work regards ELE’s potential value following implementation of the Affordable Care Act in 2014. States have a compressed timeline with which to prepare to enroll, by Congressional Budget Office estimates, approximately 9 million subsidized individuals through the exchanges and 7 million individuals into Medicaid or CHIP as of 2014, rising to 23 and 10 million, respectively, by 2016 (Congressional Budget Office 2012). Asked about the potential for ELE to benefit states in meeting these targets, administrators who had implemented ELE felt it was too soon to answer this question, but that ELE programs and experiences likely would be useful in the context of Affordable Care Act implementation.

Finally, as the research on this project unfolds, we expect to learn more about whether ELE supports or compromises program integrity. Program integrity involves the incorrect application of a program’s eligibility rules to a particular household. As this is an important policy concern, states will be reporting their error rates to CMS, and if these are available when the final Report to Congress on ELE is submitted in September 2013, we will report them.

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