Establishment of a national multiple sclerosis (MS) surveillance registry (MSSR) is a primary goal of the Department of Veterans Affairs (VA) MS Center of Excellence. The initial query of Veterans Health Administration (VHA) databases identified 25,712 patients (labeled "VHA MS User Cohort") from fiscal years 1998 to 2002 based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code; service-connection for MS; and/or disease-modifying agent (DMA) use. Because of ICD-9-CM limitations, the initial query was overinclusive and resulted in many non-MS cases. Thus, we needed a more rigorous case-finding method. Our gold standard was chart review of the Computerized Patient Record System for the mid-Atlantic VA medical centers. After chart review, we classified patients as not having MS or having MS/possible MS. We also applied a statistical algorithm to classify cases based on service-connection for MS, DMA use, and/or at least one healthcare encounter a year with MS coded as the primary diagnosis. We completed two analyses with kappa coefficient and sensitivity analysis. The first analysis (efficacy) was limited to cases with a definitive classification based on chart review (n = 600). The kappa coefficient was 0.85, sensitivity was 0.93, and specificity was 0.92. The second analysis (effectiveness) included unknown cases that were classified as MS/possible MS (N = 682). The kappa coefficient was 0.82, sensitivity was 0.93, and specificity was 0.90. These findings suggest that the database algorithm reliably eliminated non-MS cases from the initial MSSR population and is a reasonable case-finding method at this intermediate stage of MSSR development.