Using emergency trauma team activations to measure trauma activity and injury severity: 10 years of experience using an Australian major trauma centre registry.

OBJECTIVES: To describe the outcomes of Emergency Department trauma team activations over a 10-year period with respect to injury severity and hospital length of stay. METHODS: This was a retrospective study using trauma registry data at a single Major Trauma Centre in Australia. All trauma team activations and arrivals on pre-hospital major trauma (T1) protocol recorded in the trauma registry between June 2006 and July 2016 were included. The outcome of interest was major trauma, defined as an Injury Severity Score (ISS) >12 or length of stay >3 days or requiring urgent operative intervention or admission to the Intensive Care Unit following trauma. RESULTS: A total of 9876 hospital trauma activations were analysed from January 2006 to June 2016. Of these 53.3% were admitted as an in-patient and 16.6% were classified as having an ISS >15. Major trauma occurred in 38% of cases. With respect to hospital utilisation, patients with an ISS <16 accounted for around half of total cumulative in-patient bed-days. CONCLUSIONS: Analysis of data from trauma team activations in ED has allowed a description of trauma activity and hospital bed day utilisation as a function of injury severity. The results confirm that those with minor trauma accounted for the vast majority of cases and around half of all hospital in-patient bed-days.

Health status and return to work in trauma patients at 3 and 6 months post-discharge: an Australian major trauma centre study.

INTRODUCTION: The aim of this study was to describe post-discharge outcomes, and determine predictors of 3 and 6 months health status outcomes in a population of trauma patients at an inner city major trauma centre. METHODS: This was a prospective cohort study of adult trauma patients admitted to this hospital with 3 and 6 months post-discharge outcomes assessment. Outcome measures were the Physical Component Scores (PCS) and Mental Component Scores (MCS) of the Short Form 12, EQ-5D, and return to work (in any capacity) if working prior to injury. Repeated measures mixed models and generalised estimating equation models were used to determine predictors of outcomes at 3 and 6 months. RESULTS: One hundred and seventy-nine patients were followed up. Patients with lower limb injuries reported lower mean PCS scores between 3 and 6 months (coefficient -4.21, 95 % CI -7.58, -0.85) than those without lower limb injuries. Patients involved in pedestrian incidents or assaults and those with pre-existing mental health diagnoses reported lower mean MCS scores. In adjusted models upper limb injuries were associated with reduced odds of return to work at 3 and 6 months (OR 0.20, 95 % CI 0.07, 0.57) compared to those without upper limb injuries. DISCUSSION: Predictors of poorer physical health status were lower limb injuries and predictors of mental health were related to the mechanism of injury and past mental health. Increasing injury severity score and upper limb injuries were the only predictors of reduced return to work. The results provide insights into the feasibility of routine post-discharge follow-up at a trauma service level.

Refining the trauma triage algorithm at an Australian major trauma centre: derivation and internal validation of a triage risk score.

PURPOSE: To derive and internally validate a clinical prediction rule for trauma triage. METHODS: Ambulance presentations requiring trauma team activation between 2007 and 2011 at a single inner city major trauma centre were analysed. The primary outcome was major trauma, defined as Injury Severity Score >15, intensive care unit admission or in-hospital death. Demographic details, vital signs on arrival at hospital, mechanism of injury and injured body regions were used in the modelling process. Multivariable logistic regression was used on a randomly selected derivation sample. Receiver operating characteristic (ROC) analysis and Hosmer-Lemeshow tests were used to assess the discrimination and calibration of the derived model. The model was further tested using bootstrapping cross-validation. RESULTS: A total of 3027 patients were identified. Predictors selected for the prediction model were age ≥65 years (OR 1.58, 95 %CI 1.08-2.32, p = 0.02), abnormal vital signs (OR 3.72, 95 %CI 2.64-5.25), Glasgow Coma Scale score ≤13 (OR 14, 95 %CI 9.23-23.34 p < 0.001), penetrating injury (OR 5.13, 95 %CI 2.76-9.54, p < 0.001), multiregion injury (OR 4.72 95 %CI 3.45-6.46, p < 0.001), falls (OR 1.51 95 %CI 1.06-2.15, p = 0.02) and motor vehicle crashes (OR 0.56, 95 %CI 0.35-0.90, p = 0.02). The ROC area under the curve (AUC) for the final model was 0.85 (95 %CI 0.83-0.87) with a Hosmer-Lemeshow test statistic p = 0.83. Bootstrapping cross-validation demonstrated an identical AUC. CONCLUSION: We have derived and internally validated a trauma risk prediction rule using trauma registry data. This may assist with the formulation of revised local and regional trauma triage protocols. External validation is required before implementation.