New research refines injury severity scoring for better predictive accuracy
MUARC researchers have published a significant paper in Injury Prevention that improves how we measure injury severity in hospitalised patients using the International Classification of Disease Injury Severity Score (ICISS).
The study, by Associate Professor Janneke Berecki-Gisolf, Ehsan Rezaei-Darzi, Dr Tharanga Fernando, and Dr Angelo D'Elia, aimed to refine the ICISS method by linking morbidity and mortality data to evaluate its effectiveness and compare various methods for predicting injury outcomes.
The research analysed data from New South Wales, Australia, covering patient records from 2008 to 2017. By comparing different ICISS scales based on in-hospital and three-month mortality rates, the study found that the ‘worst injury’ ICISS consistently provided better predictions of injury severity compared to the ‘multiplicative injury’ ICISS. The results showed that while the ICISS method’s predictive accuracy was generally strong, it varied based on the scale used, with rates of serious injury ranging from 10% to 31% in the tested data.
The study concludes that using in-hospital death data is ideal for immediate clinical settings, while three-month death data is better suited for long-term outcomes like injury compensation. These findings offer valuable insights for improving injury severity assessments and have implications for trauma care and related injury management practices.