title: Accuracy of administrative data for identification of patients with infective endocarditis.
abstract: BACKGROUND
  Infective endocarditis is associated with high morbidity and mortality rates that have plateaued over recent decades. Research to improve outcomes for these patients is limited by the rarity of this condition. Therefore, we sought to validate administrative database codes for the diagnosis of infective endocarditis.
  
  
  METHODS
  We conducted a retrospective validation study of International Classification of Diseases (ICD-10-CM) codes for infective endocarditis against clinical Duke criteria (definite and probable) at a large acute care hospital between October 1, 2013 and June 30, 2015. To identify potential cases missed by ICD-10-CM codes, we also screened the hospital's valvular heart surgery database and the microbiology laboratory database (the latter for patients with bacteremia due to organisms commonly causing endocarditis).
  
  
  RESULTS
  Using definite Duke criteria or probable criteria with clinical suspicion as the reference standard, the ICD-10-CM codes had a sensitivity (SN) of 0.90 (95% confidence interval (CI), 0.81-0.95), specificity (SP) of 1 (95% CI, 1-1), positive predictive value (PPV) of 0.78 (95% CI, 0.68-0.85) and negative predictive value (NPV) of 1 (95% CI, 1-1). Restricting the case definition to definite Duke criteria resulted in an increase in SN to 0.95 (95% CI, 0.86-0.99) and a decrease in PPV to 0.6 (95% CI, 0.49-0.69), with no change in specificity.
  
  
  CONCLUSIONS
  ICD-10-CM codes can accurately identify patients with infective endocarditis, and so administrative databases offer a potential means to study this infection over large jurisdictions, and thereby improve the prediction, diagnosis, treatment and prevention of this rare but serious infection.
authors.affiliation: Sunnybrook Research Institute, Toronto, Canada.
authors.forename: Charlie
authors.initials: C
authors.lastname: Tan
authors.affiliation: Division of Cardiology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada.
authors.forename: Mark
authors.initials: M
authors.lastname: Hansen
authors.affiliation: Division of Cardiac Surgery, Department of Surgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada.
authors.forename: Gideon
authors.initials: G
authors.lastname: Cohen
authors.affiliation: Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada.
authors.forename: Karl
authors.initials: K
authors.lastname: Boyle
authors.affiliation: Sunnybrook Research Institute, Toronto, Canada; Division of Infectious Diseases, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada; Institute for Clinical Evaluative Sciences, Toronto, Canada. Electronic address: nick.daneman@sunnybrook.ca.
authors.forename: Nick
authors.initials: N
authors.lastname: Daneman
authors.affiliation: Sunnybrook Research Institute, Toronto, Canada; Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada; Interdepartmental Division of Critical Care, University of Toronto, Toronto, Canada.
authors.forename: Neill K J
authors.initials: NK
authors.lastname: Adhikari
mesh_terms: D002170:Canada; D000068598:Data Accuracy; D016208:Databases, Factual / Q000592:standards / Q000706:statistics & numerical data; D004696:Endocarditis / Q000175:diagnosis*; D006801:Humans; D038801:International Classification of Diseases; D058996:Quality Improvement; D012189:Retrospective Studies
keywords: Administrative data; Infective endocarditis; Validation