title: Validation of coding algorithms for the identification of patients with primary biliary cirrhosis using administrative data.
abstract: BACKGROUND
  Large-scale epidemiological studies of primary biliary cirrhosis (PBC) have been hindered by difficulties in case ascertainment.
  
  
  OBJECTIVE
  To develop coding algorithms for identifying PBC patients using administrative data--a widely available data source.
  
  
  METHODS
  Population-based administrative databases were used to identify patients with a diagnosis code for PBC from 1994 to 2002. Coding algorithms for confirmed PBC (two or more of antimitochondrial antibody positivity, cholestatic liver biochemistry and/or compatible liver histology) were derived using chart abstraction data as the reference. Patients with a recorded PBC diagnosis but insufficient confirmatory data were classified as 'suspected PBC'.
  
  
  RESULTS
  Of 189 potential PBC cases, 119 (60%) had confirmed PBC and 28 (14%) had suspected PBC. The optimal algorithm including two or more uses of a PBC code had a sensitivity of 94% (95% CI 71% to 100%) and positive predictive values of 73% (95% CI 61% to 75%) for confirmed PBC, and 89% (95% CI 82% to 94%) for confirmed or suspected PBC. Sensitivity analyses revealed greater accuracy among women, and with the use of multiple data sources and one or more years of data. Inclusion of diagnosis codes for conditions frequently misclassified as PBC did not improve algorithm performance.
  
  
  CONCLUSIONS
  Administrative databases can reliably identify patients with PBC and may facilitate epidemiological investigations of this condition.
authors.affiliation: Liver Unit, Division of Gastroenterology, Department of Medicine, University of Calgary, 3280 Hospital Drive Northwest, Calgary, Alberta. rpmyers@ucalgary.ca
authors.forename: Robert P
authors.initials: RP
authors.lastname: Myers
authors.forename: Abdel Aziz M
authors.initials: AA
authors.lastname: Shaheen
authors.forename: Andrew
authors.initials: A
authors.lastname: Fong
authors.forename: Alex F
authors.initials: AF
authors.lastname: Wan
authors.forename: Mark G
authors.initials: MG
authors.lastname: Swain
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Hilsden
authors.forename: Lloyd
authors.initials: L
authors.lastname: Sutherland
authors.forename: Hude
authors.initials: H
authors.lastname: Quan
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D016208:Databases, Factual; D004812:Epidemiologic Methods; D015340:Epidemiologic Research Design; D005260:Female; D005568:Forms and Records Control / Q000379:methods; D006801:Humans; D008105:Liver Cirrhosis, Biliary / Q000175:diagnosis* / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D055815:Young Adult