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The Uninsured at the Starting Line: Findings from the 2013 Kaiser Survey of Low-Income Americans and the ACA

This report is based on findings from the 2013 Kaiser Survey of Low-Income Americans and the ACA. This survey, conducted by the Kaiser Family Foundation (KFF) in summer 2013, examines health insurance coverage, health care use and barriers to care, and financial security among insured and uninsured adults across the income spectrum, with a focus on populations targeted for coverage expansions under the Affordable Care Act (ACA). The survey provides a baseline against which future surveys can assess the impact of the ACA on low-and moderate-income adults. The survey includes a national sample as well as three state-specific samples in California (conducted with support from the Blue Shield of California Foundation (BSCF)), Missouri (conducted with support from the Missouri Foundation for Health (MFH)), and Texas.

The survey was designed and analyzed by researchers at KFF, with feedback on the California and Missouri state-specific components from BSCF and MFH, respectively. Social Science Research Solutions (SSRS) collaborated with KFF researchers on sample design and weighting; SSRS also supervised the fieldwork.

The survey was conducted by telephone from July 24 through September 29, 2013, from representative random samples of California, Missouri, and Texas residents between the ages of 19-64, along with respondents from the remaining 47 states and the District of Columbia. In total, 8,762 interviews were completed; of these, 2,558 were with respondents living in California, 1,872 with respondents in Missouri, 1,809 with respondents in Texas, and 2,523 with respondents from other states. Computer-assisted telephone interviews (CATI) conducted by landline (4,529) and cell phone (4,233) were carried out in English and Spanish by SSRS.

Because the study was designed to focus on the low-income population, the sample was designed to over-sample this group. To efficiently reach lower-income respondents, the sample was stratified based on the estimated income level of geographic areas within the nation and within each of the three states with state-specific samples. This process was done separately for the landline and cell phone sampling frames. For the landline sample, strata were defined based on the median income within telephone exchanges; for the cell phone sample, strata were defined based on the household income associated with the billing rate-center to which the cell phone number is linked. The exact criteria for distinguishing between the strata varied from state to state. In addition, 684 interviews (359 on landline and 325 on cell phone) were conducted with respondents who were previously interviewed by SSRS as part of omnibus surveys of the general public and indicated they were ages 19-64, resided in the appropriate geography for the sample (if part of one of the state samples), and reported annual income of less than $25,000. These previous surveys were conducted with nationally representative, random-digit-dial landline and cell phone samples.

Screening for the survey involved verifying that the respondent (or another member of the household for the landline sample) met the criteria of:  1) being 19-64 years old; and 2) providing income information that allowed them to be classified by family income. Respondents were classified by family income as a share of the federal poverty level (FPL) based on their family size and total annual gross income.1 Poverty level groups included income < 138% of FPL (the income range for the Medicaid expansion), income of 139-400% FPL (the income range for Marketplace tax credits), and income above 400% of FPL (eligible only for unsubsidized coverage). For the landline sample, if two or more people met the criteria, a respondent was randomly selected by the CATI program.  Selected respondents were asked to confirm their state of residence.

A multi-stage weighting approach was applied to ensure an accurate representation of the various income groups ages 19 to 64. The weighting process involved corrections for sample design as well as sample weighting to match known demographics of the target populations in order to correct for systematic non-response along these parameters.  The base weight accounted for the oversamples used in the sample design, as well as the likelihood of non-response for the re-contact sample, number of eligible household members for the landline sample, and a correction to account for the fact that respondents with both a landline and cell phone have a higher probability of selection. Demographic weighting parameters were based on population estimates for the 19-64 year old poverty-level population in each state based on the U.S. Census Bureau’s 2011 American Community Survey (ACS). The weighting parameters for each poverty-level group within the three state-specific samples and the remaining national sample were: age, education, race/ethnicity, presence of own child in the household, marital status, region, and phone-status. All statistical tests of significance account for the effect of weighting.

The margin of sampling error (including the design effect) for national estimates, state estimates and state-by-poverty-level estimates are shown in Table A. For the national sample, the margin of sampling error is plus or minus 3.5 percentage points for both the low- and moderate-income groups. For results based on other subgroups, the margin of sampling error may be higher. Sample sizes and margin of sampling errors for other subgroups are available by request. In reporting results, any estimate with a relative standard error (standard error divided by the point estimate) greater than 30 percent or based on a cell size less than 50 is considered unreliable and not reported. Note that sampling error is only one of many potential sources of error in this or any other survey.

Table A: Number of Respondents and Margin of Sampling Error for National and State-Specific Samples
N Margin of Sampling Error
U.S. Total  8,762 +/- 2%
U.S. < 138% FPL 3,536 +/- 4%
U.S. 139%-400% FPL 3,570 +/- 4%
U.S. >400% 1,656 +/- 5%
California Total 2,558 +/- 3%
CA < 138% FPL 1,020 +/- 5%
CA 139% – 400% FPL 1,007 +/- 5%
CA >400% 531 +/- 6%
Missouri Total  1,872 +/- 4%
MO < 138% FPL 760 +/- 5%
MO 139% – 400% FPL 791 +/- 5%
MO >400% 321 +/- 8%
Texas Total 1,809 +/- 4%
TX <138% FPL 754 +/- 6%
TX 139% – 400% FPL 753 +/- 5%
TX >400% 302 +/- 8%

In analyzing results, we group respondents into mutually exclusive insurance categories of: Uninsured (report that they are not covered by health insurance), Employer Coverage (report that they have a plan through their own employer, a spouse’s employer, or a parent’s employer), Nongroup Coverage (report that they purchase their coverage themselves, and Medicaid (including people who are dually eligible for Medicare coverage). In capturing Medicaid coverage, state-specific program names were used. A small number of people report that they are covered by other sources, including Medicare (<3%), a government program besides Medicaid or Medicare (<3%), or some other source such as the VA, school-based coverage, or an unnamed source (<1%). We do not report results for people covered by these other coverage categories, as cell sizes were generally too small for reliable estimates.

Because eligibility for two of the law’s main coverage provisions– the Medicaid expansion and tax credits to purchase insurance on the Marketplaces– is based on an individual’s family income relative to the federal poverty level (FPL), in most cases we report survey results by FPL categories that match eligibility levels under the ACA. These categories are 1) those with incomes 138% FPL or less (roughly $32,000 a year for a family of 4), the income range for the Medicaid expansion; 2) those with incomes of 139 to 400% FPL (roughly $32,000-$94,000 for a family of 4), the income range for tax credits in the Marketplace; and 3) those with incomes above 400% FPL, who are not be eligible for financial assistance in gaining coverage. This classification is not intended to fully capture eligibility, as not everyone in these income ranges will be eligible for coverage under the ACA. For example, as of January 2014, 23 states were not planning to expand their Medicaid programs, and 2 states were planning on implementing their Medicaid expansion after January 2014.2 Further, undocumented immigrants are ineligible for coverage under the ACA, and recent legal immigrants cannot receive Medicaid coverage (though they can purchase subsidized coverage in the Marketplace). Last, some people may be ineligible for Marketplaces subsidies because they have access to affordable employer coverage. However, the income categories provide a picture of the population targeted by various expansions, rather than a picture of the specific population eligible under the law.

For results that examine the uninsured population’s readiness for the ACA (Section V), we exclude individuals who are undocumented immigrants, as this group is ineligible for any coverage under the ACA. In other sections, which aim to describe the experience of the entire uninsured population, we include undocumented immigrants in the results. We define undocumented immigrants as those who reported 1) they were born outside the United States, 2) are not a citizen, 3) did not have a green card when they arrived in the United States, and 4) have not received a green card or become a permanent resident since arriving.  This measure may be subject to error in several ways. First, it relies on self-reporting, and respondents have an incentive not to reveal unlawful immigration status. Second, those that did not answer all questions in the series of immigration status items (75 respondents) were not able to be categorized as undocumented and were therefore included; if they are in fact undocumented, then the results may differ slightly. Third, a small number of people may have a legal status besides permanent residency or green card (such as refugees, asylees or other humanitarian immigrants). Unfortunately, due to time constraints, the survey was not able to fully explore all of these immigration pathways.

This report includes analysis of findings from the survey that may inform early challenges in implementing health reform. It does not include a full reporting of all the findings from the survey. Future reports will provide additional analysis of other survey findings. Survey toplines with overall frequencies for all items in the questionnaire are available upon request.

Conclusion and Policy Implications Appendix: Additional Tables