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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary 2 The Changing Policy Context The need for an accurate accounting of the coverage of children in public and private health insurance programs has been an integral part of the Children’s Health Insurance Program (CHIP) since its inception. Since its passage in 1997 as part of the Balanced Budget Act, the goal of the program has been to close coverage gaps facing low-income families who do not have access to affordable private coverage for their children but do have incomes too high to qualify for Medicaid. These legislative and programmatic goals have created a need for good measures of insurance coverage for children. LEGISLATIVE REQUIREMENTS FOR ESTIMATES OF INSURANCE COVERAGE CHIP began as a block grant to states (see Kenney and Lynch, Chapter 8 in this volume). With higher federal matching rates than states typically receive under Medicaid, the program gained wide acceptance. Importantly, from the beginning, states have had considerable flexibility to design their CHIP, and as a result eligibility thresholds, outreach efforts, retention, enrollment policies, benefits, and cost-sharing have varied. This flexibility has affected the relative coverage from state to state. After 1997, CHIP and coverage grew rapidly. However, as Kenney and Lynch point out, despite this progress, at the time when the Children’s Health Insurance Program Reauthorization Act (CHIPRA) was passed in 2009, millions of children were still uninsured despite being
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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary eligible for Medicaid or CHIP. In an effort to address these gaps, CHIPRA provided states with new tools to address shortfalls in enrollment as well as access and quality. CHIPRA included new outreach and enrollment grants and bonus payments to states that adopted five of eight enrollment/retention strategies and that experienced Medicaid enrollment that exceeded targeted growth rates.1 States were also given greater options to use “express lane” eligibility strategies to facilitate eligibility determination and enrollment and were given new options for meeting documentation requirements. CHIPRA allowed states to use federal dollars to cover legal immigrant children who had been in the United States less than 5 years (previously coverage for such children had to be funded exclusively with state funds). In her presentation at the workshop, Genevieve Kenney pointed out that, just a year later, data from the Georgetown Center for Children and Families indicate that as many as 15 states actually have expanded eligibility to higher income levels since CHIPRA was passed. Another 19 are now using federal dollars to cover legal immigrant children, and almost 20 have adopted some type of major change in their enrollment and retention processes aimed at increasing participation. CHIPRA also provided states with additional federal allotments for their CHIP to cover the costs of enrolling more eligible children and of expanding eligibility (e.g., to higher income groups). In addition, CHIPRA included a number of provisions designed to improve access to care and the quality of care for the children served by Medicaid and CHIP. CHIPRA had two expected outcomes that help define the context for measurement, according to Kenney and Lynch (see Chapter 8). The first is the expected decrease in the number of uninsured. There was indeed an enrollment increase, about a year later, of 2.6 million children (over the period October 1, 2008, to September 30, 2009) (U.S. Department of Health and Human Services, 2010a, p. 1). The second was an expected decline in private coverage, which would partially offset the positive impact on coverage to the extent that CHIP gains were accompanied by cuts in private insurance coverage. In their paper, Kenney and Lynch suggest that an independent source 1 The strategies are (1) adopting 12-month continuous eligibility for all children, (2) eliminating the asset test for children, (3) eliminating in-person interview requirements at application and renewal, (4) using joint applications and supplemental forms and the same application and renewal verification process for the two programs, (5) allowing for administrative or paperless verification at renewal through the use of prepopulated forms or ex parte determinations, (6) exercising the option to use presumptive eligibility when evaluating children’s eligibility for coverage, (7) exercising the new option in the law to use the Express Lane Eligibility option, and (8) exercising the new options in the law in regard to premium assistance (Georgetown Center for Children and Families, 2009).
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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary of data on coverage is needed to answer the following evaluative questions, important for gaining an understanding of the impact of CHIPRA: Did uninsured rates fall among children following enactment of CHIPRA? If so, by how much? How much do Medicaid/CHIP participation rates vary across states? Do differences across states narrow over time? How did rates of public and private coverage change for different groups of children (defined by race/ethnicity, income, age, health status, etc.)? To what extent are the observed changes in uninsurance, public coverage, and private coverage among children attributable to CHIPRA? With much the same emphasis, Chris Peterson pointed out that Congress is broadly interested in good data because of an interest in measuring both need and success. Although need is expressed in terms of funding, it also drives decisions about other resources, for example, whether or not to build hospitals, clinics, or other infrastructure. The questions of need add a geographic dimension to the data because many of the resource decisions are made at the local level. The use of data in the measurement of success is also straightforward. Congress wants to know if the programs that have been implemented have been successful. For CHIPRA, has it resulted in a reduction in uninsurance among children? The ink was barely dry on the CHIPRA legislation when it was modified by two other important pieces of legislation. The American Recovery and Reinvestment Act (ARRA) includes enhanced matching rates to states that maintain their Medicaid eligibility thresholds for children and adults, in an effort to induce them to continue supporting Medicaid coverage during the current recession. The enhanced matching rates, which are at least 6.2 percentage points higher than regular matching rates, were implemented on October 1, 2008; they are slated to continue through June 2011, with a phased-down increase in the matching support. The Patient Protection and Affordable Care Act of 2010 (PPACA, P.L. 111-148) contains a number of important policy changes that could affect both Medicaid and CHIP coverage for children. It legislates comprehensive health reform, including an expansion of Medicaid to adults and children up to 133 percent of the federal poverty level (FPL) by January 2014, a maintenance of effort requirement through 2019 on state Medicaid and CHIP coverage for children, the provision of new subsidies for the coverage of families with incomes up to 400 percent of the FPL, the creation of health insurance exchanges, and coverage mandates for both individuals and employers. (See Box 2-1 for a summary of coverage provisions of
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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary BOX 2-1 Coverage for Children Under CHIPRA and PPACA Infants under age 1 and children aged 1-5* Medicaid < 133% of the federal poverty level CHIP 133-200% of the federal poverty level Children aged 6-18* Medicaid < 100% of the federal poverty level, going to 133% in 2014 CHIP 100-200% of the federal poverty level Disabled children: Medicaid medically needy option Other children: Foster care, children aged 18-20 *States can disregard income and extend coverage to higher percentages of the federal poverty level (e.g., 300% of the federal poverty level) SOURCE: Baugh (2010). CHIPRA and PPACA.) PPACA also provided 2 additional years of federal funding for CHIP, beyond what was in CHIPRA, through 2015. As noted earlier, PPACA includes a technical correction that also refers to definition of a “high-performing state”—one that “on the basis of the most timely and accurate published estimates of the Bureau of the Census, ranks in the lowest 1⁄3 of States in terms of the State’s percentage of low-income children without health insurance.” The federal matching payment is determined in part on whether a state meets this benchmark. EVOLVING CRITERIA FOR STATE FUNDING ALLOCATIONS Throughout its history, CHIP has relied in some way on estimates of children’s insurance coverage, mainly in regard to establishing the amounts allotted to the states for program operations and evaluation. The criteria for allocating funds to the states have changed over the course of the program, and so has the need for coverage estimates. In his presentation to the workshop, Richard Strauss outlined the past and current practices used by the Centers for Medicare & Medicaid Services (CMS) for allocating funds to states for CHIP. Prior to 2008, the fiscal year allotment (A) for the states (including the District of Columbia) was based on the number of children (Ci) under age 19 with a family income
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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary equal to or less than 200 percent of the FPL and the number of such children with no health insurance. A state cost factor (SCFi) for each state was annual wages in the health industry for the state (Wi) and annual wages in the health industry for all states (WN). The allotment formula for fiscal years 1998 through 2008 was given as: Strauss pointed out that the statute was very specific as to the source of the data that determined the number of children in the state. The number was determined on the basis of data as reported and defined in the three most recent March supplements to the Current Population Survey (CPS) before the beginning of the calendar year in which the fiscal year begins. The formula allocation procedures that governed the allocation of funds for the first decade of the program were changed with CHIPRA in 2009. CHIPRA based the amount each state would receive for 2009 and subsequent fiscal years on the 2008 allocation as adjusted by an allotment increase factor. This factor is based on a per capita health care growth factor (based on the percentage increase in the population of children in the state from July 1 of previous fiscal year to July 1 of the fiscal year involved, as provided by CMS), and a child population growth factor (based on the percentage increase in the per capita amount of national health expenditures from the calendar year in which the previous fiscal year ends to the calendar year in which the current fiscal year ends, as provided by the Census Bureau). Beginning in 2011, the amount will be adjusted by “rebasing.” Under rebasing, the allotment for a fiscal year is determined by applying the allotment increase factor to the previous fiscal year’s expenditures, which were applied against the allotments that were available in the previous fiscal year. Under CHIP, this alternates with each fiscal year; that is, the allotment increase factor is applied against the previous fiscal year’s allotment or the previous fiscal year’s expenditures. COVERAGE ESTIMATES FOR PROGRAM PURPOSES Concerned over the estimate by the Urban Institute that some 5 million eligible children remained unenrolled a year after enactment of the CHIPRA legislation (based on data from CPS and the CHIP State Enrollment Data System), Secretary of Health and Human Services Kathleen Sebelius issued a challenge to the states called Connecting Kids to Coverage. Her challenge to states, local governments, community-based organizations, health centers, and faith-based organizations was to enroll the
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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary estimated 5 million children who are eligible for CHIP or Medicaid but do not have coverage over the next 5 years (Sebelius, 2010). As part of this initiative, the U.S. Department of Health and Human Services has a plan to engage a contractor to assist with measuring progress in meeting the secretary’s challenge. A request for proposals was issued shortly after the completion of the workshop. The department is asking a contractor to analyze survey and administrative data to develop quarterly national estimates of the number of uninsured but eligible children (aged 0-18) and comparable estimates for all states and the District of Columbia. The contractor’s report is expected to outline the methodology for the estimates, ensure that the projections will be replicable, and explain the methods clearly in a separate report on methodology (U.S. Department of Health and Human Services, 2010b). In her workshop presentation, Cindy Mann, director of the Center for Medicaid and State Operations, stated that the secretary’s challenge is a high priority for the agency and the states. In order to determine the progress toward the coverage goal for the challenge, the department needs good estimates of insurance coverage by state. Progress will be measured by calling for semiannual reports by state that include current estimates of the number of uncovered children. The measurement of progress toward accomplishing the challenge goal requires current and timely data on the uncovered population by state. Another issue for which good data is needed is the targeting of outreach grant funds. Mann stated that CHIPRA authorized $100 million in outreach grants, of which $40 million has been granted to community-based organizations, $10 million to states and counties, and $10 million to Indian health organizations. The remaining $40 million and an additional $40 million under PPACA will be targeted by group and geographic area based on evidence. Similarly, CHIPRA provides matching funds for translation and interpreter services, another focus of data to help target intervention strategies. Mann also identified a wish list for data to assist in managing and evaluating CHIP. The list includes Data on the longitudinal experience of low-income children by urban and rural location, composition of their households, immigration status, and language issues. For various reasons, children can enter and leave coverage over the course of a year, and it is important to identify the causes and effects of this kind of transition. More timely data, both from the administrative databases and from surveys. The eventual goal would be real-time data on enrollment and uninsurance at the state level.
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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary Data to better understand gaps in insurance coverage. Mann gave the example of a drop in enrollment in Arizona due to a program freeze in that state. It is important to know how many children are losing coverage because they are unable to renew it, or because they are moving into Medicaid. (Medicaid enrollment is increasing in Arizona.) Better data on the status of children beyond enrollment in CHIP. This includes the kind of care they are receiving by income and the impact of that care as measured by diagnosis. These detailed data would answer questions about different patterns of care around the country and different levels of access to certain providers and to certain protocols. More standardization of state administrative data and better integration of federal and state data collection systems. In many cases, states are already collecting data useful for program administration, such as on determinations of applications, denials, and determination of renewals, but the data are not required at the federal level, so they are not available to the federal government for program management purposes.