October 2003/Issue 7 Translating Research to Policy Yet Another Wild Card in State Budget Deliberations: Federal SCHIP Allocations to States In light of the tight fiscal environments in program, or a Medicaid expansion, participating which most states now find themselves, it is states obtain federal matching funds to finance not difficult to imagine why health care policy health care expansions at higher federal makers and program administrators at the state financial participation rates than under existing level find unstable federal funding problematic. Medicaid programs. To be sure, forecasting state health care obligations—given fluctuating unemployment SCHIP is not a federal entitlement. Available rates, rising costs of health care, and legislative federal matching funds for SCHIP—$3.15 reductions to program eligibility and benefits— billion to $4.2 billion for fiscal years 1998- is not a precise science. Added uncertainty over 2004—are distributed to states via an allocation the extent to which federal matching dollars can formula. This formula is specified in law, and be used to offset state health care expenditures was designed to address states’ differing often leads to less-informed decision-making as demographics with respect to the levels of state budgets are deliberated amongst competing uninsurance among poor children and need for interests and community needs. added resources. Notwithstanding certain exceptions, a state’s “SCHIP allocation” can be In the last five years, projecting federal thought of as a limit on the amount of federal participation in the State Children’s Health program participation the state can attain in Insurance Program (SCHIP) has been a any given year. challenge for most states. Analysis by the State Health Access Data Assistance Center To target funds to states with the greatest need, (SHADAC) indicates that state SCHIP Congress initially specified that funds be allocations have varied significantly—on average, allocated to states based on the number of 22 percent per state—between 1999 and 2002. uninsured children age 18 and younger living in families with incomes below 200 percent of the For an average state participating in the federal poverty level (FPL). Later, so as not to program, this fluctuation equates to funding penalize states making progress toward greater changes during the time period, either upwards coverage of uninsured children, Congress or downwards, of $18.5 million. In other words, specified that future allocations be made based the average state participating in SCHIP could on a “blended allocation formula”, one have only reasonably counted on a federal incorporating the number of uninsured children allocation within a range of $37 million between in low-income households and the overall 1999 and 2002. This SHADAC issue brief number of children in low-income households, seeks to provide an understanding of the sources weighted equally. The blended formula was of this variability and to recommend methods phased in beginning in fiscal year 2000, and that could be employed to reduce the uncertainty fully implemented by fiscal year 2001. for states in future years. SOURCES OF VARIATION IN SCHIP SCHIP ALLOCATION FORMULA ALLOCATIONS Established in 1997, SCHIP provides states Generally speaking, variation in a state’s SCHIP with federal funding for the expansion of health allocations across years could be the result of care eligibility for uninsured, low-income one of the following factors: (1) changes in the children. Through either a separate SCHIP allocation formula (e.g., initial versus blended way, would other data sources be expected to formula), (2) movement in the actual number of change more exclusively with movements in uninsured and poor children, or (3) random error actual state uninsurance and poverty rates? in the state estimates of uninsured and poor children. Two alternate data sources for reducing estimate error include: (1) the newly By simulating what “would have happened” expanded CPS-ADS sample, and (2) a fully under various formulas and scenarios, our implemented American Community Survey analysis suggests that over half of the variation in (ACS). The CPS-ADS was expanded from state SCHIP allocations between 1999 and 2002 a survey of roughly 50,000 to 78,000 is due to changes in the allocation formula; the interviewed households beginning in 2001. rest of the variation can be attributed to random The ACS will be an annual survey of three error in the estimates used to approximate million addresses similar to the decennial uninsurance rates for children and the number census long form. Utilizing these alternate of families living under 200 percent of FPL. data sources by themselves in the SCHIP allocation formula reduced the variability in In contrast to the policy rationale behind state allocations by 23 and 67 percent, the allocation formula, we found no evidence that respectively. We suggest that the most fluctuations in allocations had anything to do desirable path would be to create estimates with actual changes in state rates of uninsurance via statistical modeling that combine the or poverty among children. In practice, then, it strengths of the CPS-ADS and the fully appears that with current data sources, the implemented ACS. This method would methodology for allocating federal SCHIP be similar to the one used by the Census funding is not functioning as designed. Bureau to allocate Title I education funds. RECOMMENDATIONS FOR STABILIZING Our analysis illustrates how seemingly technical data issues can have very real SCHIP ALLOCATIONS policy implications for states. Working The main state-level inputs to the SCHIP with improved data estimates would have allocation formula described above—namely, the effect of greatly reducing the amount of estimates of the number of uninsured children random fluctuation in funding built into the and the number of children in families below 200 current SCHIP formula. Resolving this percent of poverty—come from the Annual problem will only become more critical as Demographic Supplement to the Current more and more states exhaust their federal Population Survey (CPS-ADS). One important SCHIP allotments in the context of growing question to ask is whether other data sources numbers of uninsured, increasing health exist that would be less “noisy.” Said another care inflation, and severe budget deficits. The State Health Access Data Assistance Center at the University of Minnesota promotes the effective use of available data to inform the debate on health coverage and access. For a copy of SHADAC’s study, please see: Davern, Michael, Lynn A. Blewett, Boris Bershadsky, Kathleen Thiede Call, Todd Rockwood. “State Variation in SCHIP Allocations: How Much Is There, What Are Its Sources, and Can It Be Reduced?” Inquiry 40: 184-197 (Summer 2003) State Health Access Data Assistance Center (SHADAC) | University of Minnesota School of Public Health 612-624-4802 | fax: 612-624-1493 | www.shadac.org IB-07-1003