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Diagnosis based injury severity scaling: investigation of a method using Australian and New Zealand hospitalisations


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.

Design: 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.

Setting: Australia and New Zealand.

Patients or subjects: 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).

Interventions: None.

Main outcome measures: 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.

  • AIS, Abbreviated Injury Scale
  • ICD, International Classification of Diseases
  • ICISS, ICD injury severity score
  • SRR, survival risk ratio
  • International Classification of Diseases
  • 10th revision (ICD-10)
  • injury severity score
  • outcome prediction

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