needs. In New Hampshire, the legislature wanted data on eligibility at the county level in order to understand in which areas problems needed to be addressed. In Connecticut, as Mary Alice Lee showed, data by town revealed a decrease in enrollment in Hartford. A subsequent survey in Hartford of those leaving the program indicated that the major reason was transfer to employer-based insurance. These experiences emphasize the importance of analyzing the distribution within the state of the uninsured population and movements in and out of SCHIP in order to better understand the reasons for changes.

In its discussion of the issues presented at the workshop bearing on the problems in estimating the numbers of children eligible for SCHIP, the panel drew the following conclusions:

  • Better ways are needed to estimate eligibility and insurance coverage status from state and national survey data.

  • More work is needed to determine what data elements needed for estimating eligibility are included in each of the national surveys, how they are defined, and how differences in their content and definitions can be reconciled.

  • States should explore ways to supplement national sample efforts in such surveys as the Behavioral Risk Factor Sample Survey (BRFSS), the State and Local Area Integrated Telephone Survey (SLAITS), and other national surveys in order to expand the size of their state samples.

  • Measurement of SCHIP eligibility can be understood only while simultaneously measuring eligibility for Medicaid. It is necessary to measure both in SCHIP eligibility surveys.



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement