title: A systematic review of validated methods for identifying suicide or suicidal ideation using administrative or claims data.
abstract: OBJECTIVE
  As part of the Mini-Sentinel pilot program, under contract with the Food and Drug Administration, an effort has been made to evaluate the validity of algorithms useful for identifying health outcomes of interest, including suicide and suicide attempt.
  
  
  METHODS
  Literature was reviewed to evaluate how well medical episodes associated with these events could be identified in administrative or claims data sets from the USA or Canada.
  
  
  RESULTS
  Six studies were found to include sufficient detail to assess performance characteristics of an algorithm on the basis of International Classification of Diseases, Ninth Revision, E-codes (950-959) for intentional self-injury. Medical records and death registry information were used to validate classification. Sensitivity ranged from 13.8% to 65%, and positive predictive value range from 4.0% to 100%. Study comparisons are difficult to interpret, however, as the studies differed substantially in many important elements, including design, sample, setting, and methods. Although algorithm performance varied widely, two studies located in prepaid medical plans reported that comparisons of database codes to medical charts could achieve good agreement.
  
  
  CONCLUSIONS
  Insufficient data exist to support specific recommendations regarding a preferred algorithm, and caution should be exercised in interpreting clinical and pharmacological epidemiological surveillance and research that rely on these codes as measures of suicide-related outcomes.
authors.affiliation: Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ 08901-1293, USA. walkup@rci.rutgers.edu
authors.forename: James T
authors.initials: JT
authors.lastname: Walkup
authors.forename: Lisa
authors.initials: L
authors.lastname: Townsend
authors.forename: Stephen
authors.initials: S
authors.lastname: Crystal
authors.forename: Mark
authors.initials: M
authors.lastname: Olfson
mesh_terms: D000465:Algorithms; D002170:Canada / Q000453:epidemiology; D016208:Databases, Factual / Q000706:statistics & numerical data; D015340:Epidemiologic Research Design; D006801:Humans; D038801:International Classification of Diseases; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D059020:Suicidal Ideation; D013405:Suicide / Q000706:statistics & numerical data*; D014481:United States / Q000453:epidemiology; D014486:United States Food and Drug Administration; D054928:Validation Studies as Topic