title: Chronic rhinosinusitis identification in administrative databases and health surveys: A systematic review.
abstract: Much of the epidemiological data on chronic rhinosinusitis (CRS) are based on large administrative databases and health surveys. The accuracy of CRS identification with these methods is unknown.
  
  
  
  A systematic review was performed to identify studies that measured the accuracy of CRS diagnoses in large administrative databases or within health surveys. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess study quality.
  
  
  
  Of 512 abstracts initially identified, 122 were selected for full-text review; only three studies (2.5%) measured the accuracy of CRS patient identification. In a single, large administrative database study with a CRS prevalence of 54.8%, a single International Classification of Diseases-9th Revision diagnostic code for CRS had a positive predictive value (PPV) of only 34%. A diagnostic code algorithm identified CRS patients with a PPV of 91.3% (95% confidence interval [CI], 85.3-95.1); in a population with a CRS prevalence of 5%, this algorithm had a PPV of 31%. In health survey studies having an estimated CRS prevalence of 25% to 46%, self-reported symptom-based CRS diagnosis had a PPV of 62% (95% CI, 50.2-72.1) when nasal endoscopy was the gold standard for CRS diagnosis, and 70% (95% CI, 57.4-80.8) when otolaryngologist-based CRS diagnosis (after interview and nasal endoscopy) was the gold standard.
  
  
  
  Most health administrative data and health surveys examining CRS did not consider the accuracy of case identification. For unselected populations, administrative data and health surveys using self-reported diagnoses inaccurately identify patients with CRS. Epidemiological results based on such data should be interpreted with these results in mind. Laryngoscope, 126:1303-1310, 2016.
authors.affiliation: Department of Otolaryngology-Head and Neck Surgery, University of Ottawa, Ottawa, Ontario, Canada.
authors.forename: Kristian I
authors.initials: KI
authors.lastname: Macdonald
authors.affiliation: Department of Otolaryngology-Head and Neck Surgery, University of Ottawa, Ottawa, Ontario, Canada.
authors.forename: Shaun J
authors.initials: SJ
authors.lastname: Kilty
authors.affiliation: Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada.|Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
authors.forename: Carl
authors.initials: C
authors.lastname: van Walraven
mesh_terms: D000465:Algorithms; D002908:Chronic Disease; D000068598:Data Accuracy; D016208:Databases, Factual / Q000706:statistics & numerical data*; D004724:Endoscopy / Q000706:statistics & numerical data; D006306:Health Surveys / Q000706:statistics & numerical data*; D006801:Humans; D038801:International Classification of Diseases; D059747:Nasal Surgical Procedures / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D015995:Prevalence; D012220:Rhinitis / Q000175:diagnosis* / Q000453:epidemiology; D012852:Sinusitis / Q000175:diagnosis* / Q000453:epidemiology
keywords: Chronic rhinosinusitis; administrative database; health surveys; self-reported