Data from: Validation of an algorithm for identifying MS cases in administrative health claims datasets

William J. Culpepper, Ruth Anne Marrie, Annette Langer-Gould, Mitchell T. Wallin, Jonathan D. Campbell, Lorene M. Nelson, Wendy E. Kaye, Laurie Wagner, Helen Tremlett, Lie H. Chen, Stella Leung, Charity Evans, Shenzhen Yao & Nicholas G. LaRocca
Objective: To develop a valid algorithm for identifying multiple sclerosis (MS) cases in administrative health claims (AHC) datasets. Methods: We used 4 AHC datasets from the Veterans Administration (VA), Kaiser Permanente Southern California (KPSC), Manitoba (Canada), and Saskatchewan (Canada). In the VA, KPSC, and Manitoba, we tested the performance of candidate algorithms based on inpatient, outpatient, and disease-modifying therapy (DMT) claims compared to medical records review using sensitivity, specificity, positive and negative predictive values, and...
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