Access to care and utilization among children: estimating the effects of public and private coverage.
Division of Modeling and Simulation, Center for Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality, Rockville, Maryland 20850, USA. tselden@ahrq.gov
OBJECTIVES: We examine the relationship between health insurance coverage and children's access to and utilization of medical care. Access measures we study are having a usual source of care (USC) and lacking a USC for financial or insurance reasons. We also examine indicators for ambulatory visits, well-child visits, dental visits, emergency room use, and inpatient hospital stays. METHODS: We pool data from the first 7 years of the Medical Expenditure Panel Survey (MEPS), 1996 to 2002. Pooling yields a large sample of children, enabling us to analyze access and utilization using simple descriptive statistics, multivariate analysis, and instrumental variables estimation (IV). IV estimation is of particular interest given the possibility of bias caused by confounding factors (such as child health or parent attitudes) and measurement error in insurance coverage. We also compare estimates from IV linear probability models to estimates from IV probit with residual inclusion. RESULTS: As previous studies have found, public and private coverage are both associated with large increases in access and utilization. Simple mean comparisons suggest that private coverage has a larger effect than does public coverage. Differences between public and private coverage are reduced (and often reversed) when we control for other characteristics of children and their families. IV coverage effect estimates from both linear probability and residual inclusion probit models are substantially greater than conventional estimates across a wide range of access and utilization measures. CONCLUSIONS: Despite concerns that conventional estimates overstate the impact of coverage on access and use, our results suggest that the reverse may be true. One explanation may be that conventional estimates are biased toward zero due to error in the reporting of insurance coverage. The magnitude of the coverage effects we find highlights the importance of reducing uninsurance among children.
PMID: 16625060 [PubMed - indexed for MEDLINE]