title: A systematic review of validated methods for identifying acute respiratory failure using administrative and claims data.
abstract: OBJECTIVE
  The Food and Drug Administration's (FDA) Mini-Sentinel pilot program initially aims to conduct active surveillance to refine safety signals that emerge for marketed medical products. A key facet of this surveillance is to develop and understand the validity of algorithms for identifying health outcomes of interest (HOIs) from administrative and claims data. This paper summarizes the process and findings of the algorithm review of acute respiratory failure (ARF).
  
  
  METHODS
  PubMed and Iowa Drug Information Service searches were conducted to identify citations applicable to the anaphylaxis HOI. Level 1 abstract reviews and Level 2 full-text reviews were conducted to find articles using administrative and claims data to identify ARF, including validation estimates of the coding algorithms.
  
  
  RESULTS
  Our search revealed a deficiency of literature focusing on ARF algorithms and validation estimates. Only two studies provided codes for ARF, each using related yet different ICD-9 codes (i.e., ICD-9 codes 518.8, "other diseases of lung," and 518.81, "acute respiratory failure"). Neither study provided validation estimates.
  
  
  CONCLUSIONS
  Research needs to be conducted on designing validation studies to test ARF algorithms and estimating their predictive power, sensitivity, and specificity.
authors.affiliation: United BioSource Corporation, Lexington, MA 02420, USA.
authors.forename: Natalie
authors.initials: N
authors.lastname: Jones
authors.forename: Gary
authors.initials: G
authors.lastname: Schneider
authors.forename: Sumesh
authors.initials: S
authors.lastname: Kachroo
authors.forename: Philip
authors.initials: P
authors.lastname: Rotella
authors.forename: Ruzan
authors.initials: R
authors.lastname: Avetisyan
authors.forename: Matthew W
authors.initials: MW
authors.lastname: Reynolds
mesh_terms: D000208:Acute Disease; D000465:Algorithms; D016208:Databases, Factual / Q000706:statistics & numerical data*; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data; D038801:International Classification of Diseases; D017063:Outcome Assessment, Health Care / Q000379:methods; D010865:Pilot Projects; D011237:Predictive Value of Tests; D012131:Respiratory Insufficiency / Q000453:epidemiology*; D012680:Sensitivity and Specificity; D014481:United States; D014486:United States Food and Drug Administration; D054928:Validation Studies as Topic