To estimate a national disenrollment rate among children in Medicaid and the Children's Health Insurance Program (CHIP); to determine what share of disenrollment is due to acquiring other insurance or losing eligibility; and to examine what demographic and policy factors make disenrollment more likely.
Insurance status, income, and demographics from the Current Population Survey (CPS) March Supplement (1998–2001); eligibility data from the National Governors Association; and policy data from the former Health Care Financing Administration (HCFA), state welfare offices, and previous research.
The study used a nationally representative sample of 5,551 children in Medicaid or CHIP. The key outcomes were the percentage of children still enrolled 1 year later, and the share of disenrollees who became uninsured despite remaining eligible. Multivariate logistic regression was used to explore demographics and policies predictive of disenrollment.
CPS data were extracted using the Census Bureau's Federal Electronic Research and Review Extraction Tool 1.0. Data analysis was performed using (Stata Corporation 2001).
Of the children enrolled in Medicaid or CHIP, 27.7 percent were no longer enrolled 12 months later. Of those, 45.4 percent dropped out despite apparently remaining eligible and having no other insurance—corresponding to 3.0 million children annually. Drop‐out varied significantly across states. Children without siblings in public insurance were at a higher risk for drop‐out. Children with more educated parents were more likely to leave Medicaid for private insurance or to lose Medicaid eligibility, while black children and infants were less likely to lose their eligibility. Decreased Medicaid provider reimbursement rates were strongly associated with drop‐out, while Medicaid managed care increased the exodus to private insurance.
Drop‐out from Medicaid and CHIP is a significant policy concern and helps explain the persistence of uninsurance among millions of eligible children. Clinical encounters with providers appear to play a key role in preventing drop‐out.
Data Collection and Analysis