title: Determining the most effective level of TRISS-derived probability of survival for use as an audit filter.
abstract: OBJECTIVE
  To determine the most effective cut-off of TRISS-derived probability of survival (TRISS-PS) for the selection of trauma deaths for audit, using a large sample of trauma deaths from the United Kingdom (UK).
  
  
  METHODS
  TRISS-PS and avoidability of death (as judged by an independent peer review panel) were compared for a sample of 222 trauma deaths. Sensitivity, specificity and predictive values were calculated for the 0.5 screening cut-off. ROC curves were derived to assess the ability of different levels of TRISS-PS to identify avoidable deaths. Calculations were made for both the raw sample and the sample adjusted for the sampling method used.
  
  
  RESULTS
  For the weight-adjusted sample, the sensitivity of TRISS-PS greater than 0.5 for the detection of avoidable death is 80% (95% CI 61-91%), the specificity is 86% (95% CI 80-90%), PPV 42% (95% CI 29-56%) and NPV 97% (95% CI 93-99%). Twenty percent of avoidable deaths would have been 'missed' if the 0.5 level of audit filter had been used. Based on the same sample, the best cut-off is at TRISS-PS 0.33, with a sensitivity of 90% and specificity of 80%. It is estimated that this cut-off would have selected 62 deaths for audit and failed to identify 2 out of 25 avoidable deaths.
  
  
  CONCLUSIONS
  The previously accepted audit filter of TRISS-PS of greater than 0.5 fails to identify a significant proportion of avoidable deaths. This study suggests that the most effective level of audit filter cut-off of TRISS-PS for the trauma system studied is 0.33. This level would identify 90% of avoidable deaths with 80% specificity. Similar ROC curve analysis could be used to determine appropriate TRISS-PS cut-offs for institutions or other trauma systems.
authors.affiliation: Department of Emergency Medicine, Western Hospital, Footscray, and the University of Melbourne, Victoria, Australia. anne-maree.kelly@wh.org.au
authors.forename: Anne-Maree
authors.initials: AM
authors.lastname: Kelly
authors.forename: Jon
authors.initials: J
authors.lastname: Nicholl
authors.forename: Janette
authors.initials: J
authors.lastname: Turner
mesh_terms: D000368:Aged; D005260:Female; D006801:Humans; D015601:Injury Severity Score; D008297:Male; D008875:Middle Aged; D011336:Probability; D012372:ROC Curve; D012680:Sensitivity and Specificity; D016019:Survival Analysis; D015599:Trauma Severity Indices; D014947:Wounds and Injuries / Q000401:mortality*