Geoffrey Henley

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.

A comparison of methods for measurement of injury severity

Background The ICD-based Injury Severity Score (ICISS) provides a criterion for selecting severe injuries, useful when reporting trends in injury incidence because less affected by extraneous factors than total hospitalised cases. We assessed the relative performance of some variants of ICISS. Method Records from the Australian National Hospital Morbidity Database were included if Principal Diagnosis was S00-T89 (ICD10AM), the episode ended in the 2 years to 30 June 2007 and the mode of separation was not transfer to another acute-care hospital or statistical discharge. The ICISS variants studied were: multiplicative; worst injury; treating comorbidity as a covariate (instead of and as well as age); hybrid (precoordinating multiple injury codes within each body region); and omitting same-day cases. Survival proportions specific to each injury diagnosis code (Oslers ‘SRR’) were used to calculate ICISS, the method differing between variants. Performance of each variant in predicting survival was assessed by logistic regression modelling. Findings Multiplicative and worst injury approaches had similar discrimination and calibration (H-L statistic). Replacing age with comorbidity improved discrimination in multiplicative and worst injury models but calibration deteriorated. Including both comorbidity and age improved discrimination (multiplicative and worst injury); calibration did not change in the former, and deteriorated slightly in the latter. The hybrid approaches did not improve the models. Excluding same-day cases had little effect. Conclusion In this setting (all hospitalised injuries; ICD10AM coding) the best overall performance was for the multiplicative approach with both age and comorbidity as covariates.