Search

Background: Self-employed workers are 10% of the US labor force, with growth projected over the next decade. Whether existing policy mechanisms are sufficient to ensure health insurance coverage for self-employed workers, who do not have access to employer-sponsored coverage, is unclear. Objective: To determine whether self-employment is associated with lack of health insurance coverage. Data Sources: Secondary analysis of Medical Expenditure Panel Survey (MEPS) data collected 2014-2017. Study Design: Participants were working age (18-64 years), employed, civilian noninstitutionalized US adults with two years of Medical Expenditure Panel Survey (MEPS) participation in 2014-2017. We compared those who were employees vs those who were self-employed. Key outcomes were self-report of health insurance coverage, and of delaying needed medical care. Data Extraction Methods: Longitudinal design among individuals who were employees during study year 1, comparing health insurance coverage among those who did vs did not transition to self-employment in year 2. Principal Findings: 16 335 individuals, representing 121 473 345 working-age adults, met inclusion criteria; of these, 147, representing 1 097 582 individuals, transitioned to self-employment. In unadjusted analyses, 25.7% of those who became self-employed were uninsured in year 2, vs 8.1% of those who remained employees (P < .0001). In adjusted models, self-employment was associated with greater risk of being uninsured (26.1% vs 8.0%, risk difference 18.0%, 95% confidence interval [CI] 9.2% to 26.9%, P = .0001). A time-by-employment type product term suggests that 10.0 percentage points (95%CI 0.3 to 19.7 percentage points, P = .04) of the risk difference may be attributable to the change to self-employment. Self-employment was also associated with delaying needed medical care (12.0% vs 3.1%, risk difference: 8.9%, 95% CI 3.1% to 14.6%, P = .003). Conclusions: One in four self-employed workers lack health insurance coverage. Given the rise in self-employment, it is imperative to identify ways to improve health care insurance access for self-employed working-age US adults. KEYWORDS employment, health insurance, medically uninsured, self-employment, 1 | INTRODUCTION Self-employment is increasing in the American workforce. The US Bureau of Labor Statistics reports that as of 2016, 10% of all workers are self-employed, and that, after [...]

Objective. To determine which area-based socioeconomic status (SES) indicator is best suited to monitor health care disparities from a delivery system perspective. Data Sources/Study Setting. 142,659 adults seen in a primary care network from January 1, 2009 to December 31, 2011. Study Design. Cross-sectional, comparing associations between area-based SES indicators and patient outcomes. Data Collection. Address data were geocoded to construct area-based SES indicators at block group (BG), census tract (CT), and ZIP code (ZIP) levels. Data on health outcomes were abstracted from electronic records. Relative indices of inequality (RIIs) were calculated to quantify disparities detected by area-based SES indicators and compared to RIIs from self-reported educational attainment. Principal Findings. ZIP indicators had less missing data than BG or CT indicators [p < .0001). Area-based SES indicators were strongly associated with self-report educational attainment (p < .0001). ZIP, BG, and CT indicators all detected expected SES gradients in health outcomes similarly. Single-item, cut point defined indicators performed as well as multidimensional indices and quantile indicators. Conclusions. Area-based SES indicators detected health outcome differences well and may be useful for monitoring disparities within health care systems. Our preferred indicator was ZIP-level median household income or percent poverty, using cut points. Key Words. Socioeconomic status, delivery of health care, quality of health care, health care disparities, geographic mapping, Tracking 'prevailing disparities in health care delivery as it relates to racial factors and socioeconomic factors in priority populations' is a public health priority (Agency for Healthcare Research and Quality [...]