title: A systematic review of validated methods for identifying ventricular arrhythmias using administrative and claims data.
abstract: BACKGROUND
  Drug-induced pro-arrhythmia is a serious and unexpected event. Large administrative and claims databases can potentially identify drugs or interactions leading to cardiac arrhythmias. The purpose of this study is to evaluate the evidence supporting the validity of algorithms or codes to identify ventricular arrhythmias using administrative and claims data.
  
  
  METHODS
  A search of MEDLINE database is supplemented by manual searches of bibliographies of key relevant articles. We selected all studies in which an administrative and claims data algorithm or code was validated against a medical record. We report the positive predictive value (PPV) for ICD-9 codes compared to medical records.
  
  
  RESULTS
  Our search strategy yielded 664 studies, of which only seven met our eligibility criteria. Two additional studies were identified by peer reviewers. The most commonly included databases were Medicare and Medicaid, and the most commonly evaluated ICD-9 codes were 426.x and 427.x. The individual use of ICD-9 codes 427.x yielded a high PPV (78%-100%). The highest PPV was seen when both ICD-9 codes 427.x and 798.x were used (92%). The same codes yielded the highest PPV when found in the principal diagnosis position (100%).
  
  
  CONCLUSIONS
  The use of ICD-9 codes 427.x, alone or in combination with code 798.x, in the principal position is appropriate for the identification of ventricular arrhythmias in administrative and claims databases.
authors.affiliation: Department of Medicine, Miller School of Medicine at the University of Miami, Miami, FL 33136, USA. ltamariz@med.miami.edu
authors.forename: Leonardo
authors.initials: L
authors.lastname: Tamariz
authors.forename: Thomas
authors.initials: T
authors.lastname: Harkins
authors.forename: Vinit
authors.initials: V
authors.lastname: Nair
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000139:chemically induced / Q000175:diagnosis / Q000453:epidemiology*; D016208:Databases, Factual / Q000706:statistics & numerical data; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data; D038801:International Classification of Diseases / Q000706:statistics & numerical data*; D017063:Outcome Assessment, Health Care / Q000379:methods; D011237:Predictive Value of Tests; D054928:Validation Studies as Topic