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Validating Health Insurance Coverage Survey Estimates: A Comparison of Self-Reported Coverage and Administrative Data Records

08/2009;

ABSTRACT We administered a health insurance coverage survey module to a sample of 4,575 adult Blue Cross and Blue Shield of Minnesota (BCBS) members to examine if people who have health insurance coverage self-report that they are uninsured. We were also interested in whether respondents correctly classify themselves as having commercial, Medicare, MinnesotaCare, and/or Medicaid coverage (the four sample strata). The BCBS of Minnesota sample is drawn from both public and commercial health insurance coverage strata that are important to policy research involving survey data. Our findings support the validity of our health insurance module for determining whether someone who has health insurance is correctly coded as having health insurance coverage, as only 0.4 percent of the BCBS members answered the survey as though they were uninsured. However, we find problems for researchers interested in using survey responses to specific types of public coverage. For example, 21 percent of the Medicaid self-reported coverage came from known enrollees and only 67 percent of the MinnesotaCare self-reported count came from known enrollees. We conclude with a discussion of the study's implications for understanding the Medicaid “undercount” and the validity of self-reported health insurance coverage.

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    ABSTRACT: To assess reasons why survey estimates of Medicaid enrollment are 43 percent lower than raw Medicaid program enrollment counts (i.e., "Medicaid undercount"). Linked 2000-2002 Medicaid Statistical Information System (MSIS) and the 2001-2002 Current Population Survey (CPS). Centers for Medicare and Medicaid Services provided the Census Bureau with its MSIS file. The Census Bureau linked the MSIS to the CPS data within its secure data analysis facilities. We analyzed how often Medicaid enrollees incorrectly answer the CPS health insurance item and imperfect concept alignment (e.g., inclusion in the MSIS of people who are not included in the CPS sample frame and people who were enrolled in Medicaid in more than one state during the year). The extent to which the Medicaid enrollee data were adjusted for imperfect concept alignment reduces the raw Medicaid undercount considerably (by 12 percentage points). However, survey response errors play an even larger role with 43 percent of Medicaid enrollees answering the CPS as though they were not enrolled and 17 percent reported being uninsured. The CPS is widely used for health policy analysis but is a poor measure of Medicaid enrollment at any time during the year because many people who are enrolled in Medicaid fail to report it and may be incorrectly coded as being uninsured. This discrepancy should be considered when using the CPS for policy research.
    Health Services Research 02/2009; 44(3):965-87. · 2.29 Impact Factor

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