The Errors in Reporting Medicare Coverage: A Comparison of Survey Data and Administrative Records.

Objectives: We examine survey reporting of Medicare coverage of the older population by evaluating discordance between survey responses and administrative records. Method: We link data from the 2014 Current Population Survey Annual Social and Economic Supplement (CPS ASEC) and 2014 Medicare Enrollment Database to evaluate the extent to which individuals misreport Medicare coverage in the CPS ASEC. Using regression analyses, we assess factors associated with misreporting. Results: We find the CPS ASEC undercounts the population aged 65 years and older with Medicare by 4.5%. Misreporting of Medicare coverage is associated with citizenship status, immigration year of entry, employment, coverage of other household members, and imputation of Medicare responses. Adjusting for misreporting, Medicare coverage among older individuals increases from 93.4% to 95.6%. Discussion: The CPS ASEC underestimates Medicare coverage for the older population. Administrative records may be useful to evaluate and improve survey imputation of Medicare coverage when missing.

Indian Health Service Coverage among American Indians and Alaska Natives in Federal Tribal Areas.

Compared with other racial/ethnic groups, American Indians and Alaska Natives (AIANs) have higher uninsured rates and worse health outcomes. Using data from the 2010-2014 American Community Survey, we employ logistic regression techniques to assess the characteristics associated with Indian Health Service (IHS) coverage among working-age AIANs who have health insurance or are uninsured. Across all insurance categories, geographic residence is a factor in IHS coverage. Among the uninsured, those with and without IHS coverage are more dissimilar than similar across socioeconomic characteristics. When controlling for confounding characteristics, people who are uninsured or have Medicaid have a much higher IHS coverage rate compared with those with employer-sponsored insurance. This indicates IHS coverage is an important component for the uninsured and it complements Medicaid services. This work identifies a need for increased outreach to eligible AIANs about IHS programs, particularly those without comprehensive care.

Joining, Leaving, and Staying in the American Indian/Alaska Native Race Category Between 2000 and 2010.

Conceptualizing and operationalizing American Indian populations is challenging. Each census for decades has seen the American Indian population increase substantially more than expected, with indirect and qualitative evidence that this is due to changes in individuals' race responses. We apply uniquely suited (but not nationally representative) linked data from the 2000 and 2010 decennial censuses (N = 3.1 million) and the 2006-2010 American Community Survey (N = 188,131) to address three research questions. First, to what extent do American Indian people have different race responses across data sources? We find considerable race response change, especially among multiple-race and/or Hispanic American Indians. Second, how are people who change responses different from or similar to those who do not? We find three sets of American Indians: those who (1) had the same race and Hispanic responses in 2000 and 2010, (2) moved between single-race and multiple-race American Indian responses, and (3) added or dropped the American Indian response, thus joining or leaving the enumerated American Indian population. People in groups (1) and (2) were relatively likely to report a tribe, live in an American Indian area, report American Indian ancestry, and live in the West. Third, how are people who join a group different from or similar to those who leave it? Multivariate models show general similarity between joiners and leavers in group (1) and in group (2). Population turnover is hidden in cross-sectional comparisons; people joining each subpopulation of American Indians are similar in number and characteristics to those who leave it.