Each year the federal government distributes more than $12 billion under the Children’s Health Insurance Program (CHIP). The program was established by the Balanced Budget Act of 1997 to expand health insurance coverage to uninsured children in families with incomes that are modest but too high to qualify for Medicaid. The program is financed jointly by the federal government and the states, and it is administered by the states within broad federal guidelines. States offer this expanded coverage through Medicaid program coverage expansions or stand-alone programs aimed specifically at providing health coverage to children.
The federal CHIP monies are distributed to the states on the basis of a formula that, until recently, included the number of uninsured low-income children in each state. Through 2008, federal CHIP allocations were calculated using a formula with two key components: the child component factor and the health cost factor. The child component factor was a combination of the number of low-income children (defined as under 200 percent of the federal poverty level, FPL) and the number of low-income uninsured children based on 3 years of pooled state estimates from the Annual Social and Economic Supplement to the Current Population Survey (CPS). The health cost factor, which was used as a proxy for estimated program expenses, was based on estimates by the Bureau of Labor Statistics of the ratio of the average state wage in the health services industry relative to the national wage for the 3 most recent years of available data. States must contribute to the CHIP cost, and the federal
government provides matching payments to the states up to their available annual capped federal allotments. The matching rates are based on the Medicaid Federal Medical Assistance Percentages but are “enhanced,” reflecting greater federal financial participation.
In early 2009 the Children’s Health Insurance Program Reauthorization Act (CHIPRA) changed that allocation practice. For 2009 through 2013, CHIPRA mandates new allotment formulas for each of the 50 states and the District of Columbia as a function of their past allotments, their past or projected federal CHIP spending, or both.
CHIPRA also mandates in Section 602 that the secretary of commerce, in consultation with the secretary of health and human services, develop more accurate state-specific estimates of the number of children enrolled under Medicaid or CHIP, improve the estimates of the child population growth factor, and assess whether the American Community Survey (ACS) produces more reliable estimates for the purposes of the act.
The 2010 health care legislation included a technical correction to Section 2109(b)(2)(B) of the Social Security Act (42 U.S.C. 1397ii(b)(2)(B)), as added by Section 602 of CHIPRA, which strikes “the child population growth factor under section 2104(m)(5)(B)” and inserts “high-performing State under section 2111(b)(3)(B),” which also set a definition of a “high-performing state.” A high-performing state is 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” (Section 2102 (a)(6)). The federal matching payment will be determined in part on whether a state meets this benchmark.
Thus, although CHIP funds are no longer allocated on the basis of coverage estimates, it is presumed that the results of that mandated assessment could be used in assessing the appropriateness of a future CHIP funding formula—one that includes estimates of the low-income uninsured population of children—as well as to meet other specific provisions of CHIPRA and the new health reform legislation that require estimates of health insurance coverage for children primarily to assess state performance and assist in program evaluation.
To address the provisions of CHIPRA that call for an assessment of the accuracy and adequacy of databases on which estimates of children’s health insurance coverage are based, the Office of the Assistant Secretary for Planning and Evaluation of the U.S. Department of Health and Human Services requested that the Committee on National Statistics of the National Research Council convene a steering committee of experts
to organize, commission papers for, and conduct a public workshop to critically examine the various databases that could provide national and state-level estimates of low-income uninsured children and could be effectively used as criteria for monitoring children’s health insurance coverage. In designing the workshop, the steering committee determined that the data sets for consideration at the workshop would include ACS, CPS, the Small Area Health Insurance Estimates, the National Health Interview Survey (NHIS), and administrative databases.
The workshop was held in Washington, DC, on June 17-18, 2010. The agenda and a list of participants appear in Appendix A. Among the participants were representatives of public policy research organizations and federal agencies with responsibility for CHIP and the databases under consideration.
The exchange of information and the publication of this report with the background papers were the sole goals of the workshop. This report is intended as a record of the discussion of key issues identified by the steering committee and discussed by the subject-matter experts who participated in the workshop. It draws no conclusions, nor does it make any recommendations.
It is important to be specific about the nature of this report, which documents the information presented in the workshop presentations and discussions. It lays out the key ideas that emerged from the workshop and should be viewed as an initial step in examining the research and applying it in specific policy circumstances. The report is confined to the material presented by the workshop speakers and participants. Neither the workshop nor this summary is intended as a comprehensive review of what is known, although it is a general reflection of the field. The presentations and discussions were limited by the time available for the workshop.
This report was prepared by a rapporteur and does not represent findings or recommendations that can be attributed to the steering committee. Indeed, the report summarizes views expressed by workshop participants, and was not designed to generate consensus conclusions or recommendations but focused instead on the identification of ideas, themes, and considerations that contribute to understanding.
The report is organized into two parts. Part I is a summary of the workshop. Following this introductory chapter, Chapter 2 continues with a discussion of the context of the changing environment for the children’s health insurance program. Both the 2009 reauthorization of CHIP and the new health reform legislation are bringing significant changes to the
program, generating new requirements for good data on coverage. In addition, several initiatives, such as the secretary of health and human services’ challenge and program management goals, are also creating demand for good coverage estimates.
Chapter 3 discusses the main federal surveys for measuring health insurance coverage for children: CPS, ACS, and NHIS. Two additional surveys are also discussed: the Survey of Income and Program Participation and the Medical Expenditure Panel Survey, Household Component. Administrative databases are also important elements in the measurement of health insurance coverage for children in that they define the population and its characteristics and reflect enrollments. These state-gathered, federally maintained data collections are discussed in Chapter 4.
With primary responsibility for managing the programs, many states have mounted their own data collections for measuring the health insurance coverage of children in their states. These survey-based collections, some of which are quite extensive, are described in Chapter 5.
Chapter 6 introduces a somewhat different approach to estimating coverage, summarizing three presentations on the main modeling strategies for improving estimates using multiple data inputs. Two Census Bureau models are designed to provide reliable data for poverty and health care coverage: the Small Area Income and Poverty Estimation and the Small Area Health Insurance Estimation projects. The chapter also describes another approach, which involves the combination of data from multiple surveys to develop data that are lacking or of insufficient reliability from any single survey.
Chapter 7 summarizes the rich and stimulating discussion by the participants in response to the question: What do we need to know? In this time of change in health care policy, the way ahead is indeed challenging. The participants’ contributions are organized around the broad topics of matching data, gathering data from both public and private sources, rationalizing the ACS and the CPS, and being prepared to assess the impact of the new health care legislation.
Part II consists of six papers that were prepared as background for the workshop. Two appendixes complete the report: Appendix A presents the workshop agenda and list of participants; Appendix B presents biographical sketches of steering committee members.