title: Using Trauma Injury Severity Score (TRISS) variables to predict length of hospital stay following trauma in New Zealand.
abstract: OBJECTIVE
  To develop and assess the predictive capabilities of a statistical model that relates routinely collected Trauma Injury Severity Score (TRISS) variables to length of hospital stay (LOS) in survivors of traumatic injury.
  
  
  METHODS
  Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until discharge from Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Cubic-root transformed LOS was analysed using two-level mixed-effects regression models.
  
  
  RESULTS
  1498 eligible patients were identified, 1446 (97%) injured from a blunt mechanism and 52 (3%) from a penetrating mechanism. For blunt mechanism trauma, 1096 (76%) were male, average age was 37 years (range: 15-94 years), and LOS and TRISS score information was available for 1362 patients. Spearman's correlation and the median absolute prediction error between LOS and the original TRISS model was p=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was p=0.38 and 6.0 days, respectively. Insufficient data were available for the analysis of penetrating mechanism models.
  
  
  CONCLUSIONS
  Neither the original TRISS model nor the refined model has sufficient ability to accurately or reliably predict LOS. Additional predictor variables for LOS and other indicators for morbidity need to be considered.
authors.affiliation: School of Public Health and Psychosocial Studies, AUT University, Auckland, New Zealand. philip.schluter@aut.ac.nz
authors.forename: Philip J
authors.initials: PJ
authors.lastname: Schluter
authors.forename: Cate M
authors.initials: CM
authors.lastname: Cameron
authors.forename: Tamzyn M
authors.initials: TM
authors.lastname: Davey
authors.forename: Ian
authors.initials: I
authors.lastname: Civil
authors.forename: Jodie
authors.initials: J
authors.lastname: Orchard
authors.forename: Rangi
authors.initials: R
authors.lastname: Dansey
authors.forename: James
authors.initials: J
authors.lastname: Hamill
authors.forename: Helen
authors.initials: H
authors.lastname: Naylor
authors.forename: Carolyn
authors.initials: C
authors.lastname: James
authors.forename: Jenny
authors.initials: J
authors.lastname: Dorrian
authors.forename: Grant
authors.initials: G
authors.lastname: Christey
authors.forename: Cliff
authors.initials: C
authors.lastname: Pollard
authors.forename: Rod J
authors.initials: RJ
authors.lastname: McClure
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009017:Morbidity / Q000639:trends; D009520:New Zealand / Q000453:epidemiology; D011237:Predictive Value of Tests; D012372:ROC Curve; D012189:Retrospective Studies; D015599:Trauma Severity Indices; D014947:Wounds and Injuries / Q000145:classification / Q000175:diagnosis* / Q000453:epidemiology; D055815:Young Adult