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Databases for Estimating Health Insurance Coverage for Children: A Workshop Summary
nificant is that differences in the estimates of health insurance coverage among the three major current sources are not analytically significant. The CPS, the ACS, and the NHIS all produced coverage estimates that rounded to 85 percent in 2008.
The choice of which data source to use largely depends on the question that is asked, since they have different features related to sample size, level of detail used in questions collecting information about coverage, other subjects asked about, characteristics of the interview, and postcollection processing that affect their estimates of health insurance coverage. For example, if the need is for a point-in-time estimate, the user would turn to the ACS, whereas the CPS yields an all-year view of coverage. Each of the surveys has limitations when it comes to monitoring coverage, so Kenney and Lynch suggest that it is important to benchmark key estimates to other surveys.
Some sophisticated analysis by the State Health Access Data Assistance Center, using an “enhanced” CPS series, gives an approximation of what future estimates might look like. Turner reported that the 2008 estimates showed an ACS estimate of 14.6 percent uncovered, which was nearly identical to the NHIS 14.8 percent and actually identical to the CPS rate. On the basis of this work, she observed that the ACS estimates of health insurance coverage looked reasonable, and, when the logical edits are implemented for 2009, it is possible that the ACS estimate of uninsured may be nearly identical to the “best” NHIS estimate for overall coverage.
Much work needs to be done to improve the precision of the survey-based estimates of uninsured children, including modifying questionnaires, enhancing content, and expanding what is available in public-use files, improving clarity of published estimates, improving documentation, giving data users more information about reasons for differences in survey estimates, expanding state-level data on access and service use, and editing cases with misreported coverage. Many of the presenters emphasized conducting targeted methodological research, building bridges between the surveys so they could benefit from the strengths of one another, and providing data users more information for analyzing and possibly further adjusting data.