Related Experiment Videos
American Indian/Alaska Native uninsurance disparities: a comparison of 3 surveys
Pamela Jo Johnson1, Lynn A Blewett, Kathleen Thiede Call
1State Health Access Data Assistance Center, Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, USA. johns245@umn.edu
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.
Related Concept Videos
Surveys
One-Way ANOVA: Equal Sample Sizes
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
One-Way ANOVA: Unequal Sample Sizes
Stereotypes, Prejudice, and Discrimination
Bias in Epidemiological Studies
One-Way ANOVA