Public Opinion Quarterly Advance Access originally published online on June 18, 2009
Public Opinion Quarterly 2009 73(3):497-520; doi:10.1093/poq/nfp028
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Medicaid Underreporting in the CPS
Results from a Record Check Study
Address correspondence to Joanne Pascale; e-mail: joanne.pascale{at}census.gov
The use of survey data can be significantly hampered by the occurrence of measurement error, particularly that engendered by respondent misreporting. Previous studies have shown that public program participation tends to be substantially misreported and underestimated. Comparison with administrative records shows such a situation with the reporting of Medicaid enrollment in the U.S. Census Bureau's Current Population Survey (CPS); for 36.2 percent of enrollees, their coverage was not reported in the survey. While false positive reporting also occurs, it is, on a percentage basis, much less frequent. To understand and correct for the false negative reporting, and to develop improvements to surveys to mitigate the occurrence of misreporting, it is useful to understand the factors that relate to it. This research sought to establish the relationship between false negative Medicaid reporting and various factors associated with the coverage (such as recency and intensity), the enrollee (such as demographics and the use of services), and differences in coverage status between the respondent and the person for whom he or she was reporting. Results show that coverage patterns including shared coverage, recency, and intensity of coverage all strongly relate to false negative Medicaid reporting in the CPS. The findings provide important guidance for questionnaire design improvements as well as model-based adjustments to the survey data.
JOANNE PASCALE is with the U.S. Census Bureau, 4600 Silver Hill Road, Suitland, MD 20233, USA. MARC I. ROEMER is at 2001 12th Street NW #210, Washington DC 20009, USA. DEAN MICHAEL RESNICK is with the U.S. Census Bureau, 4600 Silver Hill Road, Suitland, MD 20233, USA. We gratefully acknowledge financial support from the State Health Access Data Assistance Center (SHADAC), via a grant from the Robert Wood Johnson Foundation (grant no. 052084 awarded to Michael Davern, PI), with additional support supplied by the Office of the Assistant Secretary for Planning and Evaluation (ASPE) and the Centers for Medicare and Medicare Services (CMS), and we thank Rob Stewart for ongoing support of research on how to best measure health insurance. We also thank Jeff Moore and the anonymous reviewers for helpful comments on earlier drafts of this paper. And finally we are extremely grateful to Jennifer Rothgeb, who launched and supervised a series of experimental research split-ballot field surveys which were invaluable to our current knowledge of measurement error in health insurance surveys. This report is released to inform interested parties of research and to encourage discussion. The views expressed are those of the authors and not necessarily those of the U.S. Census Bureau.