title: Diagnosis based injury severity scaling: investigation of a method using Australian and New Zealand hospitalisations.
abstract: OBJECTIVE
  To assess the performance of the International Classification of Diseases (ICD) based injury severity score, ICISS, when applied to two versions of the 10th edition of ICD, ICD-10 and ICD-10-AM.
  
  
  METHODS
  ICISS was assessed on its ability to predict threat to life using logistic regression modelling. Models used ICISS and age as predictors and survival as the outcome.
  
  
  METHODS
  Australia and New Zealand. Patients or
  
  
  METHODS
  Hospitalisations with an ICD-10-AM principal diagnosis in the range S00-T89 from 1 July 1999 to 30 June 2001 (Australia) or 1 July 1999 to 31 December 2001 (New Zealand).
  
  
  METHODS
  None.
  
  
  METHODS
  The models were assessed in terms of their discrimination, measured by the concordance score, and calibration, measured using calibration curves and the Hosmer-Lemeshow statistic.
  
  
  RESULTS
  523 633 Australian and 124 767 New Zealand hospitalisations were selected, including 7230 and 1565 deaths respectively. Discrimination was high in all the fitted models with concordance scores of 0.885 to 0.910. Calibration results were also promising with all calibration curves being close to linear, though ICISS appeared to underestimate mortality somewhat for cases with an ICISS score less than 0.6. Overall ICISS performed better when applied to the Australian than the New Zealand hospitalisations. Australian and New Zealand hospitalisations were very similar. ICISS was also only a little more successful when ICD-10-AM rather than mapped ICD-10 was used.
  
  
  CONCLUSIONS
  ICISS appears to be a reasonable way to estimate severity for databases using ICD-10 or ICD-10-AM. It is also likely to work well for other clinical variants of ICD-10.
authors.affiliation: Injury Prevention Research Unit, University of Otago, New Zealand.
authors.forename: S
authors.initials: S
authors.lastname: Stephenson
authors.forename: G
authors.initials: G
authors.lastname: Henley
authors.forename: J E
authors.initials: JE
authors.lastname: Harrison
authors.forename: J D
authors.initials: JD
authors.lastname: Langley
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001315:Australia / Q000453:epidemiology; D002648:Child; D002675:Child, Preschool; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D015601:Injury Severity Score; D016015:Logistic Models; D008875:Middle Aged; D009520:New Zealand / Q000453:epidemiology; D016019:Survival Analysis; D014947:Wounds and Injuries / Q000175:diagnosis / Q000401:mortality*