Michel Boudreaux 1 , Jeanette Y Ziegenfuss , Peter Graven , Michael Davern , Lynn A Blewett . Show Affiliations »
Abstract
OBJECTIVE: To compare health insurance coverage estimates from the American Community Survey (ACS) to the Current Population Survey (CPS-ASEC). DATA SOURCES/STUDY SETTING: The 2008 ACS and CPS-ASEC, 2009. STUDY DESIGN: We compare age-specific national rates for all coverage types and state-level rates of uninsurance and means-tested coverage. We assess differences using t-tests and p-values, which are reported at <.05, <.01, and <.001. An F-test determines whether differences significantly varied by state. PRINCIPAL FINDINGS: Despite substantial design differences, we find only modest differences in coverage estimates between the surveys. National direct purchase and state-level means-tested coverage levels for children show the largest differences. CONCLUSIONS: We suggest that the ACS is well poised to become a useful tool to health services researchers and policy analysts, but that further study is needed to identify sources of error and to quantify its bias. © Health Research and Educational Trust.
OBJECTIVE: To compare health insurance coverage estimates from the American Community Survey (ACS) to the Current Population Survey (CPS-ASEC ). DATA SOURCES/STUDY SETTING: The 2008 ACS and CPS-ASEC , 2009. STUDY DESIGN: We compare age-specific national rates for all coverage types and state-level rates of uninsurance and means-tested coverage. We assess differences using t-tests and p-values, which are reported at <.05, <.01, and <.001. An F-test determines whether differences significantly varied by state. PRINCIPAL FINDINGS: Despite substantial design differences, we find only modest differences in coverage estimates between the surveys. National direct purchase and state-level means-tested coverage levels for children show the largest differences. CONCLUSIONS: We suggest that the ACS is well poised to become a useful tool to health services researchers and policy analysts, but that further study is needed to identify sources of error and to quantify its bias. © Health Research and Educational Trust.
Entities: Disease
Species
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Year: 2010
PMID: 21029089 PMCID: PMC3034271 DOI: 10.1111/j.1475-6773.2010.01193.x
Source DB: PubMed Journal: Health Serv Res ISSN: 0017-9124 Impact factor: 3.402