Defining underinsurance among children with special health care needs: a Virginia sample.

Objectives: The study sought to: 1) examine the national Children with Special Health Care Needs (CSHCN) survey to determine whether there are items that can serve to operationalize alternative definitions of underinsurance; 2) construct definitions from the survey items that are consistent with Structural and Economic definitions of underinsurance and devise an algorithm for determining underinsurance for each; and 3) compare these two underinsurance definitions with the Maternal and Child Health definition of inadequate insurance, a definition that takes an Attitudinal approach to the construct.

Methods: Analyses included Virginia children who were insured throughout the survey period. Survey items from the national CSHCN survey were examined to identify items related to underinsurance. Items were divided into groups corresponding to three definitions of insurance (Attitudinal, Structural, and Economic). Algorithms were established, and underinsurance rates calculated for each definition. Logistic regression models were constructed to investigate demographic characteristics related to underinsurance.

Results: Different percentages of Virginia CSHCN were found to be underinsured based on the definitions of Attitudinal (28.9%), Economic (25.6%), and Structural (2.9%). Eight demographic characteristics and the pervasiveness of the child's special health care needs were examined in relation to underinsurance. For the Attitudinal definition, poverty level and pervasiveness were significant predictors in the model. In the model predicting Economic underinsurance status, pervasiveness and three of the demographic characteristics significantly predicted underinsurance status. In the multivariate logistic regression model for the Structural definition, none of the predictors was significantly related to underinsurance.

Conclusions: These findings demonstrate that alternative definitions of underinsurance yield dramatically different underinsurance rates. Further, even when yielding similar rates, alternative definitions may identify substantially different sets of children. The likelihood of being underinsured has a strong association with low-income status and pervasiveness of the child's special health care needs. Understanding these factors and their implications will be important when planning accessible and comprehensive health plans and care systems for CSHCN.