The largest portion of the Medicaid undercount is caused by survey reporting error—that is, Medicaid recipients misreport their enrollment in health insurance coverage surveys. In this study, we sampled known Medicaid enrollees to learn how they respond to health insurance questions and to document correlates of accurate and inaccurate reports. We found that Medicaid enrollees are fairly accurate reporters of insurance status and type of coverage, but some do report being uninsured. Multivariate analyses point to the prominent role of program-related factors in the accuracy of reports. Our findings suggest that the Medicaid undercount should not undermine confidence in survey-based estimates of uninsurance.

Objective. Principal Findings. Participation in MC and HF programs is determined by a combination of family-level predisposing, perceived need, and enabling/disabling factors, and county-level enabling/disabling factors. The strongest predictors of MC enrollment were family-level immigration status, ethnicity, and income, and the presence of a countylevel ''expansion program''; and the county-level ratio of OEWs to eligible children. Important HF enrollment predictors included family-level ethnicity, age, number of hours a parent worked, and urban residence; and county-level population size and outreach and media expenditure. Conclusions. MC and HF outreach/enrollment efforts should target poorer and immigrant families (especially Latinos), older children, and children living in larger and urban counties. To reach uninsured eligible children, it is important to further simplify the application process and fund selected outreach efforts. Local health insurance expansion programs increase children's enrollment in MC.Key Words. Medicaid, SCHIP, eligibility, outreach, enrollmentIn California, and throughout the nation, many low-income children are eligible for but not enrolled in Medicaid or the State Children's Health Insurance Program (SCHIP) and thus remain uninsured. How to best identify, enroll, and retain eligible children in these public programs is a persistent

Health foundations, such as the Robert Wood Johnson Foundation (RWJF), make multimillion-dollar investments in programs to expand insurance coverage. These efforts are driven largely by estimates of the number of uninsured people derived from population surveys, which might overestimate the number of uninsured people if they under-count people enrolled in Medicaid. This paper reports the results of the RWJF-funded California Medicaid Undercount Experiment (CMUE) to estimate the extent of underreporting of Medicaid in the California Health Interview Survey (CHIS) and its effect on estimates of uninsurance. Although some over- and underreporting occurs, overall CHIS Medicaid estimates match administrative counts for adults.

Context There is high demand for local-level population health data. A national system of state and local data collection would help improve both population health and health care delivery. The primary source of state-level population health data for adults is the Behavioral Risk Factor Surveillance System. However, many states need data on children and adolescents, racial and ethnic subpopulations, consistent estimates for localities, or more in-depth information on key topics than the Behavioral Risk Factor Surveillance System provides. Eleven state health surveys (SHSs) have emerged in an effort to address these gaps. Design Semistructured telephone interviews were conducted in 2009 with representatives of 9 SHSs. The interviews were recorded, and data were transcribed, organized, and analyzed according to the query structure. This analysis identified (1) the core elements of SHS that have been successful in meeting needs for local data and (2) the processes and strategies used by state officials in creating these surveys. Results Key findings include the following: (1) SHSs provide concrete data on local health issues that meet the needs of policy makers who wish to adopt evidence-based public health policies; (2) data from SHSs allow researchers to identify issues, apply for grants, and evaluate, assess, and track health indicators; (3) a “champion” is required to build the case for a survey and push through barriers to obtain funding and stakeholder buy-in; and (4) SHSs face challenges such as inconsistent funding and lack of uniform standards. Conclusion Opportunities to support SHSs include (1) identifying sustained funding sources; (2) providing technical assistance and facilitating training to foster best practices, quality standards, and comparability across states; and (3) supporting an organization for SHS researchers to share resources, information, and experiences.