P0686 - Medicaid/CHIP Eligibility and Insurance Status in Foreign-Born Children Living in the United States

Background
Foreign-born children are subject to an ongoing natural experiment in the United States. Each state independently decides criteria for their enrollment in Medicaid/Children’s Health Insurance Program (CHIP), resulting in three categories: 19 states follow the federal mandate of enrollment after 5 years permanent residency, 25 states offer enrollment without a waiting period for permanent residents, and 6 states have expansive criteria that allow enrollment regardless of documentation status.

Methods
Using the 2016-2017 National Survey of Children’s Health (N=2308), this study evaluated the effect of states’ discrepant criteria for foreign-born children in the primary outcomes of insurance status and access to sick care. A regression model was generated using a backward-step approach, and data were visualized as an interactive choropleth (heat map).

Results
States with more expansive criteria encompassed more children from non-white backgrounds (P=0.004), more foreign-born parents (P=0.02) and more families over the 400% federal poverty level (P=0.02). Comparisons between the exposure (state-based insurance) showed significant associations of current health insurance (P=0.02), public-type insurance (P<0.001), >1 preventive exam in past year (P=0.02) but no difference in usual source of sick care (P=0.68) in states with expansive criteria. The regression model demonstrated foreign-born children in states with expansive Medicaid/CHIP criteria were most likely to be currently insured (P=0.004; aOR 2.31, 95% CI 1.30-4.11), compared to states with no waiting period for permanent residents (P=0.40; aOR 1.17, 95% CI 0.82-1.67), compared to the reference of states that follow the federal mandate.

Conclusion
Foreign-born children are a marginalized community in the United States, and analysis of states' discrepant policies in Medicaid/CHIP eligibility for these children show that expansive criteria are linked to improved insurance rates, which is already well-established in improving nearly every health metric. This analysis and subsequent data visualization are intended to guide further advocacy efforts and policy decisions.