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.
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.
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.
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 insurance coverage; state health policy; current population survey; American community survey
The Integrated Health Interview Series (IHIS) is a public data repository that harmonizes four decades of the National Health Interview Survey (NHIS). The NHIS is the premier source of information on the health of the U.S. population. Since 1957 the survey has collected information on health behaviors, health conditions, and health care access. The long running time series of the NHIS is a powerful tool for health research. However, efforts to fully utilize its time span are obstructed by difficult documentation, unstable variable and coding definitions, and non-ignorable sample re-designs. To overcome these hurdles the IHIS, a freely available and web-accessible resource, provides harmonized NHIS data from 1969-2010. This paper describes the challenges of working with the NHIS and how the IHIS reduces such burdens. To demonstrate one potential use of the IHIS we examine utilization patterns in the U.S. from 1972-2008.
Health care utilization; Cohort study; NHIS; Medicare
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.
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).
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.
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.
We use data from the National Health Interview Survey (2000–2006) to examine the social determinants of health insurance coverage and access to care for immigrant children by 10 global regions of birth. We find dramatic differences in the social and economic characteristics of immigrant children by region of birth. Children from Mexico and Latin America fare worse than immigrant children born in the U.S. with significantly lower incomes and little or no education. These social determinants, along with U.S. public health policies regarding new immigrants, create significant barriers to access to health insurance coverage, and increase delayed or foregone care. Uninsured immigrant children had 6.5 times higher odds of delayed care compared with insured immigrant children.
Immigration; uninsurance; immigrant children; health access
Disparities in healthcare coverage and access have a prominent place on the national health policy agenda. It is, therefore, essential to understand strengths and limitations of national surveys that provide annual or periodic data for population-based healthcare disparities research and monitoring. Importantly, publicly available data on healthcare coverage and access are needed for disparities populations defined by race, ethnicity, or immigrant group (REI).
To document public use data availability for REI groups, insurance coverage, and access to care measures in selected national surveys used for healthcare disparities research.
We examined public use data for general population surveys that collect information on healthcare coverage and access on an annual or periodic basis for the nation. Data sources examined include the following: Current Population Survey, Survey of Income and Program Participation, National Health Interview Survey (NHIS), National Health and Nutrition Examining Survey, National Survey of Children’s Health, Behavioral Risk Factor Surveillance System, and Medical Expenditure Panel Survey-Household Component.
Although each survey has strengths for healthcare disparities research, there is no single survey that has detailed REI group identifiers, comprehensive measures of coverage and access, and geographic identifiers.
Current Population Survey and NHIS have detailed REI identifiers. NHIS and Medical Expenditure Panel Survey-Household Component have comprehensive measures of coverage and access but are limited by smaller samples and no geography. Findings summarized in this article will assist with identifying existing data to examine healthcare coverage and access disparities and highlight areas for improvement in public use data availability.
access to care; health disparities; health insurance; survey data; race/ethnicity
To introduce the American Community Survey (ACS) and its measure of health insurance coverage to researchers and policy makers.
Data Sources/Study Setting
We compare the survey designs for the ACS and Current Population Survey (CPS) that measure insurance coverage.
We describe the ACS and how it will be useful to health policy researchers.
Relative to the CPS, the ACS will provide more precise state and substate estimates of health insurance coverage at a point-in-time. Yet the ACS lacks the historical data and detailed state-specific coverage categories seen in the CPS.
The ACS will be a critical new resource for researchers. To use the new data to the best advantage, careful research will be needed to understand its strengths and weaknesses.
Health insurance coverage; state health policy; current population survey; American community survey
We sought to determine whether aggregate national data for American Indians/Alaska Natives (AIANs) mask geographic variation and substantial subnational disparities in prenatal care utilization.
We used data for US births from 1995 to 1997 and from 2000 to 2002 to examine prenatal care utilization among AIAN and non-Hispanic White mothers. The indicators we studied were late entry into prenatal care and inadequate utilization of prenatal care. We calculated rates and disparities for each indicator at the national, regional, and state levels, and we examined whether estimates for regions and states differed significantly from national estimates. We then estimated state-specific changes in prevalence rates and disparity rates over time.
Prenatal care utilization varied by region and state for AIANs and non-Hispanic Whites. In the 12 states with the largest AIAN birth populations, disparities varied dramatically. In addition, some states demonstrated substantial reductions in disparities over time, and other states showed significant increases in disparities.
Substantive conclusions about AIAN health care disparities should be geographically specific, and conclusions drawn at the national level may be unsuitable for policymaking and intervention at state and local levels. Efforts to accommodate the geographically specific data needs of AIAN health researchers and others interested in state-level comparisons are warranted.
We examined rates of uninsurance among workers in the US health care workforce by health care industry subtype and workforce category.
We used 2004 to 2006 National Health Interview Survey data to assess health insurance coverage rates. Multivariate logistic regression analyses were conducted to estimate the odds of uninsurance among health care workers by industry subtype.
Overall, 11% of the US health care workforce is uninsured. Ambulatory care workers were 3.1 times as likely as hospital workers (95% confidence interval [CI]=2.3, 4.3) to be uninsured, and residential care workers were 4.3 times as likely to be uninsured (95% CI=3.0, 6.1). Health service workers had 50% greater odds of being uninsured relative to workers in health diagnosing and treating occupations (odds ratio [OR]=1.5; 95% CI=1.0, 2.4).
Because uninsurance leads to delays in seeking care, fewer prevention visits, and poorer health status, the fact that nearly 1 in 8 health care workers lacks insurance coverage is cause for concern.
To examine the impact of full-year versus intermittent public and private health insurance coverage on the immunization status of children aged 19–35 months.
2001 State and Local Area Integrated Telephone Survey's National Survey of Children with Special Health Care Needs (NS-CSHCN) and the 2000–2002 National Immunization Survey (NIS).
Linked health insurance data from 2001 NS-CSHCN with verified immunization status from the 2000–2002 NIS for a nationally representative sample of 8,861 nonspecial health care needs children. Estimated adjusted rates of up-to-date (UTD) immunization status using multivariate logistic regressions for seven recommended immunizations and three series.
Children with public full-year coverage were significantly more likely to be UTD for two series of recommended vaccines, (4:3:1:3) and (4:3:1:3:3), compared with children with private full-year coverage. For three out of 10 immunizations and series tested, children with private part-year coverage were significantly less likely to be UTD than children with private full-year coverage.
Our findings raise concerns about access to needed immunizations for children with gaps in private health insurance coverage and challenge the prevailing belief that private health insurance represents the gold standard with regard to UTD status for young children.
Immunization; vaccine; health care access
The National Health Interview Survey (NHIS) is a primary source of information on the changing health of the U.S. population over the past four decades. The full potential of NHIS data for analyzing long-term change, however, has rarely been exploited. Time series analysis is complicated by several factors: large numbers of data files and voluminous documentation; complexity of file structures; and changing sample designs, questionnaires, and variable-coding schemes. We describe a major data integration project that will simplify cross-temporal analysis of population health data available in the NHIS. The Integrated Health Interview Series (IHIS) is a Web-based system that provides an integrated set of data and documentation based on the NHIS public use files from 1969 to the present. The Integrated Health Interview Series enhances the value of NHIS data for researchers by allowing them to make consistent comparisons across four decades of dramatic changes in health status, health behavior, and healthcare.
To determine whether the imputation procedure used to replace missing data by the U.S. Census Bureau produces bias in the estimates of health insurance coverage in the Current Population Survey's (CPS) Annual Social and Economic Supplement (ASEC).
Eleven percent of the respondents to the monthly CPS do not take the ASEC supplement and the entire supplement for these respondents is imputed by the Census Bureau. We compare the health insurance coverage of these “full-supplement imputations” with those respondents answering the ASEC supplement. We then compare demographic characteristics of the two groups and model the likelihood of having insurance coverage given the data are imputed controlling for demographic characteristics. Finally, in order to gauge the impact of imputation on the uninsurance rate we remove the full-supplement imputations and reweight the data, and we also use the multivariate regression model to simulate what the uninsurance rate would be under the counter-factual simulation that no cases had the full-supplement imputation.
The noninstitutionalized U.S. population under 65 years of age in 2004.
Data Extraction Methods
The CPS-ASEC survey was extracted from the U.S. Census Bureau's FTP web page in September of 2004 (http://www.bls.census.gov/ferretftp.htm).
In the 2004 CPS-ASEC, 59.3 percent of the full-supplement imputations under age 65 years had private health insurance coverage as compared with 69.1 percent of the nonfull-supplement imputations. Furthermore, full-supplement imputations have a 26.4 percent uninsurance rate while all others have an uninsurance rate of 16.6 percent. Having imputed data remains a significant predictor of health insurance coverage in multivariate models with demographic controls. Both our reweighting strategy and our counterfactual modeling show that the uninsured rate is approximately one percentage point higher than it should be for people under 65 (i.e., approximately 2.5 million more people are counted as uninsured due to this imputation bias).
The imputed ASEC data are coding too many people to be uninsured. The situation is complicated by the current survey items in the ASEC instrument allowing all members of a household to be assigned coverage with the single press of a button. The Census Bureau should consider altering its imputation specifications and, more importantly, altering how it collects survey data from those who respond to the supplement.
Implications for Policy Delivery or Practice
The bias affects many different policy simulations, policy evaluations and federal funding allocations that rely on the CPS-ASEC data.
Primary Funding Source
The Robert Wood Johnson Foundation.
Health insurance coverage; current population survey; annual social and economic supplement; hotdeck imputation; item nonresponse; missing data
To examine whether the usual source of preventive care, (having a usual place for care only or the combination of a usual place and provider compared with no usual source of preventive care) is associated with adults receiving recommended screening and prevention services.
Using cross-sectional survey data for 24,138 adults (ages 18–64) from the 1999 National Health Interview Survey (NHIS), we estimated adjusted odds ratios using separate logistic regression models for receipt of five preventive services: influenza vaccine, Pap smear, mammogram, clinical breast exam, and prostate specific antigen.
Having both a usual place and a usual provider was consistently associated with increased odds for receiving preventive care/screening services compared to having a place only or neither. Adults ages 50–64 with a usual place/provider had 2.8 times greater odds of receiving a past year flu shot compared with those who had neither. Men ages 50–64 with a usual place/provider had nearly 10 times higher odds of receiving a PSA test compared with men who had neither. Having a usual place/provider compared with having neither was associated with 3.9 times higher odds of clinical breast exam among women ages 20–64, 4.1 times higher odds of Pap testing among women ages 21–64, and 4.8 times higher odds of mammogram among women ages 40–64.
Having both a usual place and usual provider is a key variable in determining whether adults receive recommended screening and prevention services and should be considered a fundamental component of any medical home model for adults.
source of care; medical home; usual provider; preventive care; health insurance
Critically review estimates of health insurance coverage available from different sources, including the federal government, state survey initiatives, and foundation-sponsored surveys for use in state policy research.
Study Setting and Design
We review the surveys in an attempt to flesh out the current weaknesses of survey data for state policy uses. The main data sources assessed in this analysis are federal government surveys (such as the Current Population Survey's Annual Social and Economic Supplement, and the National Health Interview Survey), foundation-supported surveys (National Survey of America's Families, and the Community Tracking Survey), and state-sponsored surveys.
Despite information on estimates of health insurance coverage from six federal surveys, states find the data lacking for state policy purposes. We document the need for state representative data on the uninsured and the recent history of state data collection efforts spurred in part by the Health Resources Services Administration State Planning Grant program. We assess the state estimates of uninsurance from the Current Population Survey and make recommendations for a new consolidated federal survey with better state representative data.
We think there are several options to consider for coordinating a federal and state data collection strategy to inform state and national policy on coverage and access.
Uninsurance; state health policy; household surveys
This article describes the role states could play in a national effort to measure and monitor the public health safety net. The authors developed a data collection framework using information from five states on two components of the safety net: structure and demand. Because states are the primary vehicle for access expansions and programs to care for the poor, the authors suggest that they be the primary coordinating mechanism for data collection on the safety net. Because the necessary mechanisms for more uniform standards or criteria to evaluate state data collection activities and capacity remain undeveloped, they recommend using existing data to begin building state capacity to measure and monitor the safety net.
To assess the extent and consistency of geographic differences in the use of post-acute care (PAC), and the stability of this pattern of variation.
The 5 percent Medicare data sample for 1996, 1997, and the first eight months of 1998 were used.
Patterns of PAC use for various Diagnosis-related Groups (DRGs) across states (33 with enough cases per year) and census divisions were examined. The consistency of relative rankings for overall PAC use and use within defined DRGs was compared.
PAC use varied substantially across regions. For example, the extent of any PAC use for stroke patients varied by 12 percentage points among census regions in 1998. The pattern of PAC use was quite consistent across years; 30 of the 36 possible Spearman rank order correlations were statistically significant with coefficients ranging from 0.35 to 0.95 among the DRGs studied. The correlations among DRGs were generally high. For skilled nursing facility use, all the correlations were above 0.5 and were statistically significant; in general the patterns were highest within medical DRGs (0.65–0.93).
The variation in PAC use is not a statistical artifact. It is likely the result of several forces: practice styles, supply of services, and local regulatory practices.
Geographic variation; post-acute care; Medicare; supply effects