Objective: To assess measures of Medicaid and Children's Health Insurance Program (CHIP) coverage duration for potential inclusion in a core set of children's health care quality measures as called for by the Children's Health Insurance Program Reauthorization Act (CHIPRA) of 2009.
Methods: We reviewed published and unpublished reports and spoke to researchers, analysts, and program officials at the federal level and in selected states. Measures available in administrative data were assessed with regard to the feasibility of implementation and their validity in terms of their association with child health outcomes and state policy choices.
Results: Although many measures are feasible to construct using existing administrative data, prospective measures of duration that examine a cohort of new enrollees were found to be the most valid measures based on research linking their outcomes to program policies and their consistent interpretation across states with similar enrollment and renewal structures. However, the inability of some states to link together data from their Medicaid and CHIP enrollment files affects the interpretation of these and other measures across states.
Conclusions: Prospective and retrospective measures of duration were recommended for inclusion in the core set of quality measures. Although the prospective and retrospective measures were ranked high in terms of validity and importance by the Subcommittee on Quality Measures for Children's Health Care in Medicaid and CHIP, concerns were raised about feasibility given that no state currently uses these measures to monitor program performance. Additional technical and financial resources and enhancements to administrative data systems will be needed to support state efforts in this area of quality assessment, particularly in the areas of linking Medicaid and CHIP data files, improving reason for dis-enrollment codes, and improving race and ethnicity coding. Monitoring how well states are doing at enrolling and retaining children in Medicaid and CHIP is a critical component to assessing overall program performance and quality and for interpreting many of the other proposed quality measures.
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