This study has confirmed findings from previous research showing that children in foster care utilize behavioral healthcare services more frequently than other Medicaid children. This study shows clearly that not only were foster care children more likely to be diagnosed with mental health or substance abuse conditions, but they also were more likely to use such services compared to other groups of Medicaid children (including children who were eligible for Medicaid through SSI due to disability).
Children in foster care also were more likely than the Medicaid population as a whole to have physical health conditions documented in Medicaid claims data, but not surprisingly, they had fewer such conditions than children who were eligible for Medicaid coverage through SSI. Levels of utilization in the foster care population generally followed this pattern as well, that is, higher than the Medicaid population overall, but lower than the SSI population. This is consistent with previous research by Rymer and Adler (1987), based on Medicaid data for four states from 1985.
Children in foster care typically were more likely to receive preventive and dental care through Medicaid than other groups of Medicaid children (including those receiving SSI benefits). Nevertheless, the rate of health assessments was still well below the level recommended by the CWLA guidelines, especially during the period immediately following placement (CWLA 1988; AAP 1994). Simms and Halfon (1994) speculate that the reasons for poor compliance with recommendations include limitations in staffing and funding, which impede implementation of the standards; lack of research justifying the recommendations; and a general lack of understanding concerning their rationale.
This chapter discusses the results of this study in terms of the implications for policymakers, areas for further research, and limitations of the research due to data constraints.
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These findings have important implications for policy and practice aimed at improving the delivery of health care services to children in foster care, especially in the changing health care environment. The first implication of this study is the importance of continuity of health insurance coverage within the foster care population.(1) Children in foster care were less likely to be continuously enrolled in Medicaid for a full year than adoption assistance or SSI children. This may not be surprising given that placement in foster care is often a pathway to Medicaid eligibility for children in crisis. Nevertheless, this result held when we examined the extent of continuous 12-month coverage over a 24-month period and still, foster care children were less likely than other vulnerable populations to be continuously enrolled in Medicaid. (We cannot tell from Medicaid eligibility data whether some children had other forms of public or private coverage during periods in which they were not enrolled in Medicaid.)
There is growing literature documenting the adverse effects of discontinuities of health insurance coverage (see, for example, Weissman et al. 1999; Berman et al. 1999; Burstin et al. 1998/99). Consequently, states are implementing strategies to increase retention rates, including less frequent redeterminations (such as every six months or annually instead of monthly) and less onerous reapplication requirements (such as mail-in or telephone rather than face-to-face procedures). Eleven states are offering 12-month continuous coverage (Ross and Jacobson 1998). It remains to be seen how foster care children will be affected by these policies in terms of their continuity of health insurance coverage and access to health care (both while they are in foster care and during other periods of Medicaid eligibility). In the meantime, policymakers should focus explicitly on ways to improve continuity of health insurance coverage among foster care children. This would include more timely determination of eligibility when children are removed from the home as well as continuation of eligibility when they return home (Rawlings-Sekunda 1999).
A second implication of this study is that states have considerable flexibility in how they use Medicaid to pay for services for children in foster care. Florida, for example, funded case management services through Medicaid. Children in Pennsylvania — especially those in foster care — had greater access to services through the EPSDT program. Medicaid can fund a comprehensive continuum of care — ranging from screening and assessment to follow-up treatment and ongoing therapies — to meet the wide-ranging needs of children in foster care. Evidence of state-level variation in Medicaid expenditures suggests that states differ in the use of Medicaid to serve children in foster care.
A third implication of this study is the importance of developing mechanisms to better coordinate services for children in foster care, whether they are receiving care in a managed care or fee-for-service environment. The analysis of utilization before and after foster care placement revealed that the majority of foster care children are not receiving CWLA-recommended services during the initial placement period (or at least these services are not being billed to Medicaid). Care coordination strategies are designed to minimize discontinuities of care during transitions (for example, from one foster care placement to another or from one provider to another). In some states, care coordination may be designed to provide access to both covered and noncovered services (that is, services that are not included in the Medicaid benefit package) (Rosenbach and Young 2000). A broad-based concept of care coordination is especially relevant for foster care families, whose needs may involve multiple systems of care, such as public health, child welfare, mental health, schools, and juvenile justice, to name a few. What often differentiates the care coordination process from traditional case management is the advocacy orientation and creative problem-solving approaches used by care coordinators to ensure that individuals get the care they need, regardless of who pays. In other words, care coordinators can help families navigate the boundaries of Medicaid and obtain services provided through other systems of care. The use of proactive care coordination, however, requires a shift away from controlling access and utilization and toward advocating for the needs of children and their families. Whether such services are provided in a managed care environment or on a fee-for-service basis, care coordination may help foster care families get the care they need for their children. More research is needed, however, about the costs and benefits of care coordination (Rosenbach and Young 2000).
A fourth implication of this study is the critical importance of tailoring managed care programs to meet the special needs of the foster care population. Although they represent only 1 to 3 percent of the child Medicaid population, foster care children clearly have higher needs. Policymakers may lose sight of these needs when they consider the larger and more visible Medicaid populations. Payment mechanisms — such as risk adjustment approaches — need to take into account the differential utilization and expenditure profile among children in foster care, especially their higher use of mental health services.
The higher level of mental health conditions (as reflected in Medicaid claims data) and more intensive utilization of mental health/substance abuse treatment also have important implications for the design of programs to adequately serve the foster care population, both in terms of the benefit structure and the composition of provider networks. Covered benefits should reflect the full continuum of care, while networks may need to include both public and private providers to ensure continuity of care. Managed care organizations may not be aware of the special needs of this population when developing provider networks or applying their standard medical necessity criteria. Education of managed care providers is essential to ensure that this small, but vulnerable, population does not fall through the cracks.
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This study raised a number of questions that remain unanswered. First, what accounts for the significant variation in diagnoses, utilization, and expenditure patterns across states? Utilization and expenditures, for example, were consistently lower in California than in the other two states. (The level of chronic illness and disability was also lower, but this may be endogenous due to our reliance on claims data for this measure.) This study should motivate policymakers to consider factors that account for such variations within the foster care population. One factor may be the role of child welfare and health agencies in coordinating and advocating for health care services for children in foster care. California, for example, implemented health passports for children in foster care in 1995, well after the other two states (Lutz and Horvath 1997). Another factor may be differential involvement of the courts in mandating evaluation and treatment of physical or mental health conditions (Halfon et al. 1992(b); English and Freundlich 1997). State variation may also be a function of the propensity of states to cover certain services through Medicaid (such as case management in Florida or EPSDT services in Pennsylvania). Other factors that may be associated with state-level variation include the availability of providers to serve this population, their knowledge of services needed by the population, the generosity of reimbursement rates, differences in case mix, or level of stigma about accessing services. This study has taken a first step to document differences across states. Further research is required to explain them.
In addition to observing state-level variation, we observed variation within subgroups of the foster care population (for example, variations by age, length of Medicaid eligibility, health condition, SSI status, and Title IV-E status). More consideration needs to be given to why certain groups of foster care children experience lower levels of utilization and expenditures than others whether they are driven by different levels of need or whether factors other than clinical need account for the variation. One foster care subgroup that appears to be particularly vulnerable and at-risk is adolescents; they have particularly high mental health needs and utilization and lower levels of routine preventive care. Given that, policymakers, providers, and advocates should focus attention on assuring that adolescents in foster care have adequate access to the health care system, particularly to help them prepare for their independence.
Another question raised by this study concerns the extent of unmet need in the foster care population. It is possible that lower rates of utilization among certain groups of foster care children reflect an underutilization of health care services, or conversely, that higher rates in certain groups may reflect inappropriate, or overutilization. Without external benchmarks against which to evaluate patterns of care, together with more detailed clinical assessments, we cannot tell definitively whether lower rates of utilization are indicative of access barriers or simply of lower health care needs. This is of particular concern for those children who ostensibly have "no chronic conditions" according to the approach we used to classify health conditions. Because the classification of chronic health conditions is conditional upon having a claim with a particular set of diagnoses, those who do not use any services de facto cannot be classified as having a chronic condition. Therefore, the lower level of use in the "no condition" group reflects an averaging of utilization patterns among those who truly have none of the specified CDPS conditions, and those who — due to access barriers — have unmet needs. While it is reassuring to observe substantially higher levels of utilization among those with one or more chronic health conditions, it is unclear whether those with no chronic conditions are receiving an adequate level of care that meets their needs. This is certainly true for preventive and dental care, where we would not expect to observe such disparities between children who have chronic health conditions and those who do not.
Policymakers and researchers might consider various approaches to further explore the extent of unmet need in the foster care population. One approach is to conduct a prospective or retrospective medical record review to ascertain compliance with external standards (CWLA 1988; AAP 1994). Another approach is to survey foster care families and case managers to assess their perceptions of the adequacy of health care received by the children in their custody. Such assessments could be gathered for those receiving services through the fee-for-service sector as well as those enrolled in managed care. This way the two systems of care could be compared.
Another issue raised by this study is how children receiving adoption assistance fare relative to other children, especially those in foster care. Children receiving adoption assistance clearly were different from foster care children, in terms of their demographic characteristics, eligibility dynamics, diagnoses, utilization, and expenditures. In general, adopted children had more continuous Medicaid coverage than those in foster care, fewer diagnosed conditions, and lower expenditures and utilization. More continuous Medicaid coverage would be expected for children receiving adoption assistance since adoption is a lifetime legal relationship and foster care is a temporary service for the protection of a child. To the extent that Medicaid claims accurately represent patterns of diagnoses, utilization, and expenditures among adopted children, it would appear that adopted children are healthier than those in foster care, possibly explaining the lower levels of utilization and expenditures. One caveat, however, is that we cannot tell whether adopted children had other third-party coverage through their adoptive families so that Medicaid served as the payer of last resort, providing coverage when benefits were exhausted or for services not covered by commercial plans. In such cases, diagnoses, utilization, and expenditures would be understated in Medicaid claims. Further investigation is required to better understand the differences. The lower level of preventive care and dental care in the adoption assistance group deserves further exploration as well.
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Like all studies, this one has a number of limitations related to generalizability and reliability of results. First, we relied on data from three states. Although this is an improvement over previous studies that used data from only a single state, it still nevertheless cannot be generalized to all states or to the nation as a whole. The value of multiple states, however, is that it demonstrates the extent of variation across the country, and hopefully, can provide useful comparisons to other states. Second, the data are from the early-to mid-1990s (1994-95 for California and Florida and 1993-94 for Pennsylvania). These were the most recent data available through SMRF. Clearly, more recent data would be desirable to ascertain whether patterns of enrollment, diagnosed conditions, utilization, and expenditures have changed.
Third, the analyses of diagnosed conditions, expenditures, and utilization exclude children enrolled in managed care, since SMRF did not gather encounter data for capitated services (the one exception was for dental services provided through prepaid dental plans in California). Therefore, to the extent that there are systematic differences in the utilization patterns among children in foster care who are enrolled in managed care, these will not be captured in the analysis. Ideally, future studies would include encounter data from managed care organizations to allow a comparison of utilization patterns in managed care versus fee-for-service.
Fourth, the analyses rely on Medicaid claims data submitted by providers. The reliability of the CDPS classification hinges on the reliability of diagnostic coding by providers. Likewise, the analysis of Medicaid expenditures and utilization patterns relies on the accuracy of procedure codes. To the extent that there are errors in coding, our results will be less than precise.
We also encountered a number of limitations in using the SMRF data, which other researchers should be aware of. First, there is no indicator of provider specialty on the SMRF files, which precluded us from looking at continuity of care or specialty referral patterns. Second, not all states report basic data such as diagnoses, which precluded us from conducting analyses of diagnosed conditions in Florida.(2) To our knowledge, however, there is no central database that indicates which SMRF files contain which data elements and to what degree of completeness. Third, states often use state-specific procedure codes for such specialized services as case management, EPSDT, and mental health. We were fortunate to have access to state-specific procedure codes, but these are not uniformly available to researchers. Fourth, we found significant inconsistencies in the way states classified services by type of service. This was especially problematic for mental health services, where the three states each used different type-of-service categories. Again, we were fortunate to have access to state-specific procedure codes that enabled us to sort out these inconsistencies. Fifth, the SMRF file contains a single eligibility code for each month, which means that children with dual SSI and foster care eligibility during a given month would only be classified in a single category. This hampered our ability to identify foster care children with SSI coverage, and conversely, to identify SSI children in an out-of-home placement. Our solution was to identify children with any foster care eligibility during the year (our analytic group), and then screen for SSI eligibility during the full 24-month study period. This yielded relatively few children, but was the best we could do under the circumstances. A more desirable solution would be to obtain eligibility information from both child welfare offices and the Social Security Administration and match these records to Medicaid data to more reliably identify the populations of analytic interest. Sixth, it is unclear whether the date of initial foster care placement is reliably identified in Medicaid eligibility files. Anecdotal evidence suggests there are significant lags in obtaining Medicaid coverage for those who are not covered or in switching the reason for eligibility among those with prior Medicaid coverage (Rawlings-Sekunda 1999; Schneider and Fennel 1999). That might explain why we see such low levels of utilization immediately following foster care placement, but we cannot be sure.
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Increasing attention currently is being focused on the health care needs of children in foster care. There is considerable interest in developing performance measures to track the effectiveness of child welfare services, including outcomes of child well-being. This study has provided examples of how health care measures can be operationalized using Medicaid enrollment and claims data.
More recent data are required, however, to determine how children in foster care are faring in the "new millennium." States are developing initiatives to improve the continuity and comprehensiveness of care received by children in foster care. A recent survey of 35 states revealed (Rawlings-Sekunda 1999):
The effectiveness of these initiatives is unknown. Additional analysis — based on more recent data — would be useful to determine whether children in foster care are now receiving more continuous coverage and more comprehensive care as a result of recent efforts.
1. A related issue, but one that was not addressed by this study, is the lack of health insurance coverage for the parents of foster care children. Anecdotal evidence suggests that barriers to mental health and substance abuse treatment because parents are uninsured (and not eligible for Medicaid) often serves as an obstacle to preserving or reuniting families.
2. Beginning in 1999, states are submitting claims data through the Medicaid Statistical Information System (MSIS) that conform with UB-92 and HCFA-1500 billing standards. The expanded data reporting will capture more procedures and diagnoses and will be an important data source for future research.
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Last updated: 12/8/00