title: Accuracy of Administrative Data for the Coding of Acute Stroke and TIAs.
abstract: OBJECTIVE
  Administrative data validation is essential for identifying biases and misclassification in research. The objective of this study was to determine the accuracy of diagnostic codes for acute stroke and transient ischemic attack (TIA) using the Ontario Stroke Registry (OSR) as the reference standard.
  
  
  METHODS
  We identified stroke and TIA events in inpatient and emergency department (ED) administrative data from eight regional stroke centres in Ontario, Canada, from April of 2006 through March of 2008 using ICD-10-CA codes for subarachnoid haemorrhage (I60, excluding I60.8), intracerebral haemorrhage (I61), ischemic (H34.1 and I63, excluding I63.6), unable to determine stroke (I64), and TIA (H34.0 and G45, excluding G45.4). We linked administrative data to the Ontario Stroke Registry and calculated sensitivity and positive predictive value (PPV).
  
  
  RESULTS
  We identified 5,270 inpatient and 4,411 ED events from the administrative data. Inpatient administrative data had an overall sensitivity of 82.2% (95% confidence interval [CI 95%]=81.0, 83.3) and a PPV of 68.8% (CI 95%=67.5, 70.0) for the diagnosis of stroke, with notable differences observed by stroke type. Sensitivity for ischemic stroke increased from 66.5 to 79.6% with inclusion of I64. The sensitivity and PPV of ED administrative data for diagnosis of stroke were 56.8% (CI 95%=54.8, 58.7) and 59.1% (CI 95%=57.1, 61.1), respectively. For all stroke types, accuracy was greater in the inpatient data than in the ED data.
  
  
  CONCLUSIONS
  The accuracy of stroke identification based on administrative data from stroke centres may be improved by including I64 in ischemic stroke type, and by considering only inpatient data.
authors.affiliation: 1Institute for Clinical Evaluative Sciences,Toronto,Ontario,Canada.
authors.forename: Ruth
authors.initials: R
authors.lastname: Hall
authors.affiliation: 1Institute for Clinical Evaluative Sciences,Toronto,Ontario,Canada.
authors.forename: Luke
authors.initials: L
authors.lastname: Mondor
authors.affiliation: 1Institute for Clinical Evaluative Sciences,Toronto,Ontario,Canada.
authors.forename: Joan
authors.initials: J
authors.lastname: Porter
authors.affiliation: 1Institute for Clinical Evaluative Sciences,Toronto,Ontario,Canada.
authors.forename: Jiming
authors.initials: J
authors.lastname: Fang
authors.affiliation: 1Institute for Clinical Evaluative Sciences,Toronto,Ontario,Canada.
authors.forename: Moira K
authors.initials: MK
authors.lastname: Kapral
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D002170:Canada / Q000453:epidemiology; D016208:Databases, Factual / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D038801:International Classification of Diseases; D002546:Ischemic Attack, Transient / Q000175:diagnosis* / Q000453:epidemiology*; D008297:Male; D008875:Middle Aged; D012042:Registries; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012737:Sex Factors; D020521:Stroke / Q000175:diagnosis* / Q000453:epidemiology*; D055815:Young Adult
keywords: Diagnostic accuracy; Health administrative data; Health services research; Predictive value; Sensitivity; Stroke