title: Trauma registry injury coding is superfluous: a comparison of outcome prediction based on trauma registry International Classification of Diseases-Ninth Revision (ICD-9) and hospital information system ICD-9 codes.
abstract: BACKGROUND
  Trauma registries are an essential but expensive tool for monitoring trauma system performance. The time required to catalog patients' injuries is the source of much of this expense. Typically, 15 minutes of chart review per patient are required, which in a busy trauma center may represent 25% of a full-time employee. We hypothesized that International Classification of Disease-Ninth Revision (ICD-9) codes generated by the hospital information system (HI) would be similar to those coded by a dedicated trauma registrar (TR) and would be as accurate as TR ICD-9 codes in predicting outcome.
  
  
  METHODS
  One thousand eight hundred twelve patients admitted to a Level I trauma center during 2 years had International Classification of Disease Injury Severity Scores (ICISS) calculated based on HI and TR ICD-9 codes. The relative predictive powers of these two ICISSs were then compared for every patient using Receiver Operator Characteristic Curve Area (ROC) and Hosmer Lemeshow Statistics.
  
  
  RESULTS
  Eighty-nine percent of patients (1,608 of 1,812) had identical HI and TR ICISSs. Eleven patients' ICISSs differed by >0.1, and only two patients' scores differed by >0.2. ICISS proved to be a powerful predictor of outcome whether derived from HI (ROC = 0.884; 95% confidence interval (CI) = 0.850-0.917) or TR (ROC = 0.872; 95% CI = 0.837-0.908). Although these predictive powers were not significantly different (p = 0.076), the trend was for HI to perform better than TR. ISS calculated for the same data set using the MacKenzie dictionary proved significantly less predictive of outcome than either ICISS (ROC(MacKenzie) = 0.843; 95% CI = 0.792-0.884; p = 0.034).
  
  
  CONCLUSIONS
  We conclude that in our hospital TR data on individual injuries can be replaced by HI data without loss of predictive power. ISS based on the MacKenzie dictionary should be abandoned because it is much less predictive of outcome than ICISS.
authors.affiliation: Department of Surgery, College of Medicine, University of Vermont, Burlington 05405, USA.
authors.forename: T M
authors.initials: TM
authors.lastname: Osler
authors.forename: M
authors.initials: M
authors.lastname: Cohen
authors.forename: F B
authors.initials: FB
authors.lastname: Rogers
authors.forename: L
authors.initials: L
authors.lastname: Camp
authors.forename: R
authors.initials: R
authors.lastname: Rutledge
authors.forename: S R
authors.initials: SR
authors.lastname: Shackford
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D003953:Diagnosis-Related Groups / Q000592:standards*; D005260:Female; D006751:Hospital Information Systems; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D015601:Injury Severity Score; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care / Q000592:standards*; D011237:Predictive Value of Tests; D011379:Prognosis; D012372:ROC Curve; D012042:Registries / Q000592:standards*; D015203:Reproducibility of Results; D014947:Wounds and Injuries / Q000145:classification* / Q000453:epidemiology