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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary 7 Looking Ahead Along with the rest of the nation’s health care system, the Children’s Health Insurance Program (CHIP) finds itself in a time of massive change. In the 18-month period prior to the workshop, CHIP was reengineered with passage of the Children’s Health Insurance Program Reauthorization Act in early 2009; it was then further clarified with passage of the American Recovery and Reinvestment Act (ARRA) in 2009 and the Patient Protection and Affordable Care Act (PPACA) in 2010. During the workshop, participants emphasized that the program can be expected to be in a state of change for some time to come, as changes wrought by the new health care reform legislation are implemented at the national and state levels. At the same time, on the data front, two major trends are expected to yield a change in the kind of information that will be available to understand the impact of the new health reform legislation on children’s health insurance coverage, among other issues. These are the increased attention to the quality of administrative data on the CHIP and Medicaid programs at the federal and state levels and the growing maturity and acceptance of the American Community Survey (ACS). The coming decade is a time in which, with proper planning, there will be new opportunities for developing and implementing improvements to survey and administrative databases in ways that will enhance understanding of children’s health insurance coverage issues.
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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary MATCHING DATA Although this is a time of constrained resources, there are exponentially expanding needs for data that will assist policy makers and program administrators at the federal, state, and local levels ensure coverage of eligible populations, manage programs efficiently, and evaluate the effectiveness of program options and approaches. One consistent theme of the workshop was the emerging power to link survey to survey, survey to administrative record data, and administrative to administrative record data systems. In addition to hearing about pioneering record matching projects, such as those involving State Health Access Data Assistance Center (SHADAC), the National Center for Health Statistics (NCHS), the Agency for Healthcare Research and Quality (AHRQ), the U.S. Department of Health and Human Services Assistant Secretary for Planning and Evaluation (ASPE), the Centers for Medicare & Medicaid Services (CMS), and the U.S. Census Bureau, the workshop was informed that the CMS has released a task order to produce person-level data files on Medicaid eligibility, service utilization, and payment information to support comparative effectiveness research funded by the ARRA. As was pointed out in the workshop, as a component of ARRA, CMS has been approved by the U.S. Department of Health and Human Services to produce and enhance the Medicaid Analytic eXtract file (MAX). The agency has released a task order relating to the production of MAX, along with the development of an accelerated version of MAX to produce more timely data for research use. The range of activities that are optional under this task order include verification of Social Security numbers, production of a master file of Medicaid/CHIP enrollment, and linkage of MAX to federal surveys, identified in the solicitation as the National Health Information Survey, the National Health and Nutrition Examination Survey, the Longitudinal Study on Aging, the National Nursing Home Survey, the Medicare Current Beneficiary Survey, and a prototype for the Census Bureau’s ACS. Many of the opportunities for matching exist at the state level. It was suggested that state-level matching could involve using other data to get a better match of the potentially eligible population with enrollment files. These links between administrative data systems would permit improvements in the modeling of state impacts and in the development of measurement error models. Because insurance coverage is dynamic, useful links would be not only cross-sectional but also longitudinal—creating records on individuals over time. One benefit of this matching activity, it was suggested at the workshop, would be to improve understanding of the existing data, their limitations, and how they could be better used for policy analysis.
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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary IMPROVING UNDERSTANDING OF NONFEDERAL AND STATE COVERAGE SOURCES Improvements to federal and state survey and administrative record systems will go only part of the way toward gaining a better understanding of children’s health insurance coverage. To get a complete picture, the coverage represented by private insurers needs to be better understood. It was suggested that there are few links to private insurance enrollment records as well as little knowledge of the effects of private insurance. Some past efforts to develop such links, such as the SNACC project, were unsuccessful in obtaining private insurers’ data. States are also looking into using data from all-payer databases in order to have information on both public and private plans, and it was suggested that understanding of the total coverage picture may change when the Internal Revenue Service (IRS) implements its responsibility for ascertaining the health insurance coverage of the population. The requirement for coverage and the penalty imposed on those who fail to maintain minimum essential health benefits coverage were established by the PPACA, as amended by the Health Care and Education Reconciliation Act of 2010, in new section 5000A of the Internal Revenue Code, and are scheduled to begin in tax year 2014. In general, the legislation requires individuals, beginning in 2014, to maintain health insurance, with some exceptions. Individuals will be required to maintain minimum essential coverage, which includes eligible employer coverage, individual coverage, grandfathered plans, and federal programs, such as Medicare and Medicaid, among others. In order to assess a penalty, IRS may be obtaining information from insurers about an individual’s health insurance coverage with an indication of coverage on a monthly basis (the penalties would be applied monthly). This requirement sets up an opportunity for obtaining extensive new information on insurance coverage. RATIONALIZING THE AMERICAN COMMUNITY SURVEY AND THE CURRENT POPULATION SURVEY Several factors identified during the workshop appear to drive increased reliance on the ACS as the major survey source of estimates of children’s health insurance coverage, although there will continue to be reliance on the Current Population Survey (CPS) or some purposes. This trend will be based, in part, on the fact that the ACS and the CPS results are close for many characteristics and statuses, particularly in terms of family income and uninsurance. The CPS is generally acknowledged to provide better estimates of poverty due to the income questions. That said, the facts that the ACS has better geographic coverage, a larger sample size (and lower standard errors), and the new coverage question mean
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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary that it should increasingly become the primary source of the estimates. This has practical consequences, as the workshop was reminded by David Johnson. The Census Bureau now receives about $20 million annually to pay for the additional work associated with collecting the children’s health insurance data on the CPS and to fund a program of research and modeling for these data. These funds would be put in jeopardy if the user community shifted to sole use of the ACS as the source of these data. The discussion at the workshop focused on the meaning of this trend for these major household surveys. A few participants speculated that there would be increasing pressure to improve measurement of other factors other than coverage that affect the uninsured, such as health status and access. Moreover, it was noted, these additional data items would be most useful if they were ready in time to measure the coverage and effectiveness of the post-2014 program changes, although it was recognized that the next window of opportunity for adding or adjusting questions in the ACS will not occur until 2018. In the near term, the upcoming, near-simultaneous release in September 2010 of the ACS and CPS estimates of children’s coverage in 2009 will draw attention to reconciliation and preference issues. Organizations such as the State Health Access Data Assistance Center are focusing on improving understanding of the ACS this year and are engaged in finding out from states what numbers they use so they will be ready for this event. IMPACT OF THE NEW HEALTH CARE REFORM LEGISLATION The workshop discussion focused on the critical factor of time in considering necessary changes to data systems. Officials of the U.S. Department of Health and Human Services reminded everyone that many things will change after 2014, including coverage under Medicaid. The representatives of the Office of the Assistant Secretary for Policy and Evaluation stressed that the federal government must be flexible during this implementation period and that projects should be put in place to perform some timely infrastructure studies as the implementation activities unfold. Such studies might well learn from the infrastructure studies in Massachusetts that were reported at the workshop, which have helped to assess the effects of the health care changes there.