title: Administrative data accurately identified intensive care unit admissions in Ontario.
abstract: OBJECTIVE
  To evaluate the accuracy of Ontario administrative health data for identifying intensive care unit (ICU) patients.
  
  
  METHODS
  Records from the Critical Care Research Network patient registry (CCR-Net) were linked to the Ontario Health Insurance Program (OHIP) database and the Canadian Institute for Health Information (CIHI) database. The CCR-Net was considered the criterion standard for assessing the accuracy of different OHIP or CIHI codes for identifying ICU admission.
  
  
  RESULTS
  The highest positive predictive value (PPV) for ICU admission (91%) was obtained using a CIHI special care unit (SCU) code, but its sensitivity was poor (26%). A strategy based on a combination of CIHI SCU codes yielded a lower PPV (84%) but a higher sensitivity (92%). A strategy based purely on OHIP claims yielded further reductions in PPV (73%), gains in specificity (99%), and moderate sensitivity (56%). The highest sensitivity (100%) was obtained using a combination of CIHI and OHIP codes in exchange for poor PPV (32%).
  
  
  CONCLUSIONS
  Administrative databases can be used to identify ICU patients, but no single strategy simultaneously provided high sensitivity, specificity, and PPV. Researchers should consider the study purpose when selecting a strategy for health services research on ICU patients.
authors.affiliation: Department of Critical Care, Sunnybrook and Women's College Health Sciences Centre, University of Toronto, G1 06, 2075 Bayview Avenue, Toronto, Ontario, Canada. damon.scales@utoronto.ca
authors.forename: Damon C
authors.initials: DC
authors.lastname: Scales
authors.forename: Jun
authors.initials: J
authors.lastname: Guan
authors.forename: Claudio M
authors.initials: CM
authors.lastname: Martin
authors.forename: Donald A
authors.initials: DA
authors.lastname: Redelmeier
mesh_terms: D019992:Databases as Topic; D006302:Health Services Research; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007344:Insurance Claim Reporting; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D008498:Medical Record Linkage; D009864:Ontario; D017063:Outcome Assessment, Health Care / Q000379:methods*; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity