title: A systematic review of validated methods for identifying systemic lupus erythematosus (SLE) using administrative or claims data.
abstract: OBJECTIVE
  To examine the validity of billing, procedural, or diagnosis code, or pharmacy claim-based algorithms used to identify patients with systemic lupus erythematosus (SLE) in administrative and claims databases.
  
  
  METHODS
  We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to SLE. We also searched the reference lists of included studies. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria. The two reviewers independently extracted data regarding participant and algorithm characteristics and assessed a study's methodologic rigor using a pre-defined approach.
  
  
  RESULTS
  Twelve studies included validation statistics for the identification of SLE in administrative and claims databases. Seven of these studies used the ICD-9 code of 710.0 in selected populations of patients seen by a rheumatologist or patients who had experienced the complication of SLE-associated nephritis, other kidney disease, or pregnancy. The other studies looked at limited data in general populations. The algorithm in the selected populations had a positive predictive value (PPV) in the range of 70-90% and of the limited data in general populations it was in the range of 50-60%.
  
  
  CONCLUSIONS
  Few studies use rigorous methods to validate an algorithm for the identification of SLE in general populations. Algorithms including ICD-9 code of 710.0 in physician billing and hospitalization records have a PPV of approximately 60%. A requirement that the code is obtained from a record based on treatment by a rheumatologist increases the PPV of the algorithm but limits the generalizability in the general population.
authors: Division of Drug Information Service, College of Pharmacy, The University of Iowa, USA. Electronic address: kevin-moores@uiowa.edu.
authors: Kevin G
authors: KG
authors: Moores
authors: Vanderbilt Evidence-based Practice Center, Vanderbilt University Medical Center, Suite 600, 2525 West End Avenue, Nashville, TN 37203-1738, USA. Electronic address: nila.sathe@vanderbilt.edu.
authors: Nila A
authors: NA
authors: Sathe
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*; D008180:Lupus Erythematosus, Systemic / Q000453:epidemiology*
keywords: ACR; Administrative database; Algorithm validation; American College of Rheumatology; CI; CPT; Current Procedural Terminology; ESRD; ICD; ICD-9; Incidence calculation; International Classification of Diseases; KPNC; Kaiser Permanente Northern California; N; NR; Positive predictive value (PPV); SLE; Systemic lupus erythematosus (SLE); US Renal Data System; USRDS; confidence interval; end stage renal disease; not reported; number; systemic lupus erythematosus