This applicationseeks a New Investigator Training Award to providesupport to a junior faculty member to further develop independent research skillsat a newly established injury research center. Based on his experience using ICD-9-CM and the National Electronic Injury Surveillance System (NEISS), the applicant proposes to validate the childhood injury diagnosis codes in Medicaid emergency department (ED) claims data. Medicaid claims data are readily available for injury research and program evaluation due to mandatory submissionof such data by all states to the Center for Medicare and Medicaid Service. However, little is known about the accuracy of the injury diagnosis codes in the data. The specific aims of the study are to: (1) examine the quality of key demographic variables in Medicaid claims data; (2) investigate the accuracy and the sensitivityof injury diagnosiscodes to identify children's injuries; and (3) evaluate comparability of the NEISS and the ICD-9-CM injury diagnosis codes. A stratified sample from 21,554 injury cases captured by the NEISS in 2003 at the study site will result in 851 Medicaid injury cases. This studywill link injury data captured by the NEISS with Medicaid claims data. Standards in CDC Data Elements for Emergency Department Systems will be used to examine the data quality of key demographic variables (e.g. date of birth and gender) in Medicaid claims data. Medical records review will investigate the accuracy and the sensitivity of ICD-9-CM injury diagnosis codes. An innovative bridging scheme will evaluate the comparability of the NEISS injurydiagnosiscodes and ICD-9-CM injurydiagnosis codes. This project is the first part of a multi-component research programdeveloped by the applicantto investigate injuries among poor children and those with disabilities.If proved valid and reliable, funding will be sought next by the applicant to use Medicaid claims data to studythe injury medical care costs among Medicaid children and the injury risk among children with mental health problems.