摘要：Objectives. We examined whether 3 nationally representative data sources produce consistent estimates of disparities and rates of uninsurance among the American Indian/Alaska Native (AIAN) population and to demonstrate how choice of data source impacts study conclusions. Methods. We estimated all-year and point-in-time uninsurance rates for AIANs and non-Hispanic Whites younger than 65 years using 3 surveys: Current Population Survey (CPS), National Health Interview Survey (NHIS), and Medical Expenditure Panel Survey (MEPS). Results. Sociodemographic differences across surveys suggest that national samples produce differing estimates of the AIAN population. AIAN all-year uninsurance rates varied across surveys (3%–23% for children and 18%–35% for adults). Measures of disparity also differed by survey. For all-year uninsurance, the unadjusted rate for AIAN children was 2.9 times higher than the rate for White children with the CPS, but there were no significant disparities with the NHIS or MEPS. Compared with White adults, AIAN adults had unadjusted rate ratios of 2.5 with the CPS and 2.2 with the NHIS or MEPS. Conclusions. Different data sources produce substantially different estimates for the same population. Consequently, conclusions about health care disparities may be influenced by the data source used. Access to quality health care is a priority for the nation. Access to such care is designated in Healthy People 2010 as one of the 10 Leading Health Indicators, marking it as a priority area for improving the health of the nation 1 and reducing health disparities. 2 American Indians/Alaska Natives (AIANs) are one group that continues to have substantial health disparities compared with other racial groups. 3 – 8 However, disparities in health care coverage and access for AIANs have received only intermittent attention, 9 – 13 leaving a marked gap in our understanding. Previously documented issues for research on AIAN health care disparities include gaps in data availability for AIANs 14 , 15 as well as problems with national-level estimates masking the differences across geographic areas. 13 , 16 However, it is also possible that there are differences in the magnitude of estimates or the conclusions drawn, depending on which data source is used to examine health care disparities. Because no single data source contains all possible measures of health and health care, different data sources are often used to answer complementary but different questions. In the case of national surveillance and annual snapshot reports, information from numerous data sources are used to present a more complete picture of health for the US population. Healthy People 2010 uses National Health Interview Survey (NHIS) data to monitor insurance coverage and access to a usual source of care and uses National Vital Statistics System data to monitor access to prenatal care. 1 In the chapter on access to care, the National Healthcare Disparities Report also uses NHIS data to examine uninsurance and access to a usual source of care but uses the Medical Expenditure Panel Survey (MEPS) to examine all-year uninsurance and access to a primary care provider. 17 A few recent studies that examined health care access for AIANs used other data sources, such as the National Survey of America's Families 12 or the Behavioral Risk Factor Surveillance Survey. 13 We use 3 general population surveys commonly used for health care coverage and access research to examine the implications of using different data sources for estimating health care disparities specific to AIANs. We use uninsurance disparities as an example but acknowledge at the outset that different data sources measure insurance coverage in different ways. Our purpose is not to critically review measures of uninsurance or to critique the surveys that collect these data. Rather, we aim to demonstrate that choice of data source matters for disparities research, often for a variety of reasons. Our intent is 2-fold: (1) to examine whether 3 nationally representative data sources produce trustworthy and consistent estimates of the AIAN population in the United States and (2) to highlight the impact that choice of data source can have on conclusions about uninsurance disparities.
