From Medicaid to uninsured: drop-out among children in public insurance programs

Health Services Research, Feb, 2005 by Benjamin D. Sommers

This paper examines the enrollee retention of Medicaid and the Children's Health insurance Program (CHIP) in an attempt to determine the extent to which drop-out is a problem for the programs, and what demographic and policy factors make disenrollment more likely.

Children without health insurance are more likely to go without needed care in times of illness and are less likely to receive preventive treatment (Newacheck et al. 1998). Some parents may fail to maintain their children's coverage because they expect to re-enroll in case of an emergency, but children with discontinuous coverage are ,50 percent more likely to lack a regular source of care (Kogan et al. 1995), a factor associated with a tenfold increased risk of hospitalization for preventable health problems (Shi et al. 1999). Loss of insurance leads to lower rates of check-ups, vaccination, and follow-up care (Burstin et al. 1998), and total Medicaid costs per month go up as coverage becomes more sporadic (Ku and Ross 2002). Clearly, if many children are leaving Medicaid or CHIP and becoming uninsured, it would pose a significant public health and policy problem.

The current political climate adds to the significance of this issue. At both the state and federal level, expanded eligibility for Medicaid and CHIP has become a key tool in the incremental approach to covering the roughly 45 million Americans without health insurance. If Medicaid and CHIP struggle to keep current enrollees from dropping out despite continuing eligibility and lack of other insurance, then expansions without improved retention may not significantly decrease the ranks of the uninsured. Furthermore, since 2001, fiscal difficulties have forced states to look for ways to trim their Medicaid and CHIP budgets. While some states have simply cut beneficiaries off the rolls, many have used budget-saving changes that aim to maintain coverage for needy enrollees (KFF 2003a). In 2002-2003, 37 states froze or reduced reimbursement rates to providers (KFF 2003a). Other cost-saving measures include making the re-enrollment process more stringent (AHL 2002b), and switching to managed care, particularly for prescription drugs (AHL 2002a). Despite the appearance of trimming costs without increasing the number of uninsured, such changes may significantly exacerbate disenrollment.

Enrollee retention has typically been a secondary or even tertiary concern in research on public insurance, after crowd out and low take-up rates. However, several recent studies of CHIP have found a high turnover, ranging from 18 percent to 48 percent annually (Rosenbach et al. 2001; Shenkman et al. 2002). Medicaid studies provide estimates ranging from 20 percent to 33 percent, but these figures may no longer be applicable since they used data that preceded welfare reform (Ellwood and Lewis 1999; Ku and Ross 2002). One post reform analysis estimates that 18 percent of low-income uninsured children had been enrolled in Medicaid or CHIP during the previous year but were not enrolled by the time of the survey (Kenney and Haley 2001). But, critically, previous research has failed to distinguish between three different causes of disenrollment, each with unique policy and public health implications: (1) acquisition of new insurance; (2) loss of eligibility; and (3) drop-out from the program despite continuing eligibility and no other form of insurance. Each outcome must be considered separately in order to make appropriate policy in this realm.

What leads to disenrollment? An eight-state study of CHIP reveals that, in some states, up to 24 percent of applications for continuing enrollment were denied due to incorrect paperwork, and up to 40 percent of individuals never reapplied at all (Hill and Lutzky 2003). Surveys of the parents of CHIP disenrollees indicate that roughly 25 percent consciously decided to disenroll, while the remainder indicated that they had forgotten to reenroll or did not understand the process (Perry et al. 2001). In terms of predictors of disenrollment, the literature is sparse. Two studies found that older children disenroll at higher rates (Miller and Phillips 2002; Shenkman et al. 2002), while inconsistent results have been found on race and disenrollment (Miller and Phillips 2002; Shenkman et al. 2002; Shulman 2003). At a policy level, passive re-enrollment--which presumes that enrollees remain eligible, unless they report otherwise--and the countywide density of providers who accept CHIP patients were both strongly associated with lower disenrollment (Dick et al. 2002; Miller and Phillips 2002).

Overall, the existing literature offers several insights into the issue of public insurance disenrollment, but leaves much unanswered. Previous analyses have typically studied fewer than a dozen slates at a time--often only one state per study--and thus were unable to capitalize on the state-level variation in Medicaid and CHIP policies. Most of these studies have focused on CHIP, despite the fact that it is by far the smaller program. Most importantly, previous research did not distinguish between the three different types of disenrollment discussed earlier. Thus, in addition to offering a national post-welfare reform estimate of Medicaid/CHIP childhood disenrollment, this paper explores two key policy questions that remain unanswered: first, how many of the children who leave Medicaid or CHIP become uninsured despite remaining eligible for public coverage? Second, what policies and demographic indicators affect disenrollment and could shape future attempts to improve Medicaid and CHIP retention?