title: Expanding the use of administrative claims databases in conducting clinical real-world evidence studies in multiple sclerosis.
abstract: OBJECTIVE
  Administrative claims databases provide a wealth of data for assessing the effect of treatments in clinical practice. Our aim was to propose methodology for real-world studies in multiple sclerosis (MS) using these databases.
  
  
  METHODS
  In three large US administrative claims databases: MarketScan, PharMetrics Plus and Department of Defense (DoD), patients with MS were selected using an algorithm identified in the published literature and refined for accuracy. Algorithms for detecting newly diagnosed ('incident') MS cases were also refined and tested. Methodology based on resource and treatment use was developed to differentiate between relapses with and without hospitalization.
  
  
  RESULTS
  When various patient selection criteria were applied to the MarketScan database, an algorithm requiring two MS diagnoses at least 30 days apart was identified as the preferred method of selecting patient cohorts. Attempts to detect incident MS cases were confounded by the limited continuous enrollment of patients in these databases. Relapse detection algorithms identified similar proportions of patients in the MarketScan and PharMetrics Plus databases experiencing relapses with (2% in both databases) and without (15-20%) hospitalization in the 1 year follow-up period, providing findings in the range of those in the published literature.
  
  
  CONCLUSIONS
  Additional validation of the algorithms proposed here would increase their credibility.
  
  
  CONCLUSIONS
  The methods suggested in this study offer a good foundation for performing real-world research in MS using administrative claims databases, potentially allowing evidence from different studies to be compared and combined more systematically than in current research practice.
authors: Novartis Pharma AG , Basel , Switzerland.
authors: Gorana
authors: G
authors: Capkun
authors: Raquel
authors: R
authors: Lahoz
authors: Elisabetta
authors: E
authors: Verdun
authors: Xue
authors: X
authors: Song
authors: Weston
authors: W
authors: Chen
authors: Jonathan R
authors: JR
authors: Korn
authors: Frank
authors: F
authors: Dahlke
authors: Rita
authors: R
authors: Freitas
authors: Kathy
authors: K
authors: Fraeman
authors: Jason
authors: J
authors: Simeone
authors: Barbara H
authors: BH
authors: Johnson
authors: Beth
authors: B
authors: Nordstrom
mesh_terms: D000328:Adult; D000465:Algorithms; D016208:Databases, Factual / Q000706:statistics & numerical data*; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000175:diagnosis / Q000503:physiopathology / Q000628:therapy*; D012008:Recurrence; D014481:United States
keywords: Administrative claims; Algorithm; Multiple sclerosis; Real-world evidence; Relapse