title: A systematic review of validated methods for identifying transverse myelitis using administrative or claims data.
abstract: OBJECTIVE
  To identify and assess billing, procedural, or diagnostic code algorithms used to identify transverse myelitis in administrative databases.
  
  
  METHODS
  We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to transverse myelitis. We also searched the reference lists of included studies. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria. Two reviewers independently extracted data regarding participant and algorithm characteristics.
  
  
  RESULTS
  Three studies met criteria for inclusion in this review. The only algorithm based solely on administrative claims data with a reported positive predictive value included five ICD-9 codes (codes 341.20, 341.21, 341.22, 323.8, 323.9). The positive predictive value for physician-diagnosed acute transverse myelitis was 62%.
  
  
  CONCLUSIONS
  More research is needed to establish an accurate algorithm to identify transverse myelitis in large administrative databases using diagnosis and/or procedure codes. Use of standardized consensus definitions, clear description for algorithm selection, and reporting of validation procedure and results would be most beneficial.
authors: Vanderbilt Vaccine Research Program, Vanderbilt University Medical Center, USA. Electronic address: elizabeth.williams@vanderbilt.edu.
authors: S Elizabeth
authors: SE
authors: Williams
authors: Department of Epidemiology, University of Iowa College of Public Health, S437 CPHB University of Iowa, 105 River Street, Iowa City, IA 52242, USA. Electronic address: ryan-carnahan@uiowa.edu.
authors: Ryan
authors: R
authors: Carnahan
authors: Vanderbilt Evidence-based Practice Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Suite 600, 2525 West End Avenue, Nashville, TN 37203-1738, USA. Electronic address: shanthi.krishnaswami@vanderbilt.edu.
authors: Shanthi
authors: S
authors: Krishnaswami
authors: Vanderbilt Evidence-based Practice Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Suite 600, 2525 West End Avenue, Nashville, TN 37203-1738, USA; Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Suite 600, 2525 West End Avenue, Nashville, TN 37203-1738, USA. Electronic address: melissa.mcpheeters@vanderbilt.edu.
authors: Melissa L
authors: ML
authors: McPheeters
mesh_terms: D000465:Algorithms; D016208:Databases, Factual / Q000706:statistics & numerical data*; D004812:Epidemiologic Methods; D006801:Humans; D015994:Incidence; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D038801:International Classification of Diseases / Q000706:statistics & numerical data*; D009188:Myelitis, Transverse / Q000453:epidemiology*
keywords: ATM; Administrative database; CSF; ICD; ICD-9; International Classification of Diseases; KPNC; Kaiser Permanente Northern California; MRI; N; NR; PPV; Positive predictive value; TM; Transverse myelitis; acute transverse myelitis; cerebrospinal fluid; magnetic resonance imaging; not reported; number; positive predictive value; transverse myelitis