Using Trauma Injury Severity Score (TRISS) variables to predict length of hospital stay following trauma in New Zealand

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Author(s)
Schluter, PJ
Cameron, CM
Davey, TM
Civil, I
Orchard, J
Dansey, R
Hamill, J
Naylor, H
James, C
Dorrian, J
Christey, G
Pollard, C
McClure, RJ
Griffith University Author(s)
Year published
2009
Metadata
Show full item recordAbstract
Aim 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. Method 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 ...
View more >Aim 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. Method 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 ?=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ?=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.
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View more >Aim 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. Method 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 ?=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ?=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.
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Journal Title
New Zealand Medical Journal
Volume
122
Issue
1302
Publisher URI
Copyright Statement
© 2009 New Zealand Medical Association. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
Subject
Biomedical and clinical sciences