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Background: There are 27 receiving trauma hospitals in the Republic of Ireland. There has not been an audit system in place to monitor and measure processes and outcomes of care. The National Office of Clinical Audit (NOCA) is now working to implement Major Trauma Audit (MTA) in Ireland using the well-established National Health Service (NHS) UK Trauma Audit and Research Network (TARN)., Aims: The aim of this report is to highlight the implementation process of MTA in Ireland to raise awareness of MTA nationally and share lessons that may be of value to other health systems undertaking the development of MTA., Methods: The National Trauma Audit Committee of the Royal College of Surgeons in Ireland, consisting of champions and stakeholders in trauma care, in 2010 advised on the adaptation of TARN for Ireland. In 2012, the Emergency Medicine Program endorsed TARN and in setting up the National Emergency Medicine Audit chose MTA as the first audit project. A major trauma governance group was established representing stakeholders in trauma care, a national project co-ordinator was recruited and a clinical lead nominated. Using Survey Monkey, the chief executives of all trauma receiving hospitals were asked to identify their hospital's trauma governance committee, trauma clinical lead and their local trauma data co-ordinator. Hospital Inpatient Enquiry systems were used to identify to hospitals an estimate of their anticipated trauma audit workload., Results: There are 25 of 27 hospitals now collecting data using the TARN trauma audit platform. These hospitals have provided MTA Clinical Leads, allocated data co-ordinators and incorporated MTA reports formally into their clinical governance, quality and safety committee meetings. There has been broad acceptance of the NOCA escalation policy by hospitals in appreciation of the necessity for unexpected audit findings to stimulate action., Conclusion: Major trauma audit measures trauma patient care processes and outcomes of care to drive quality improvement at hospital and national level. MTA will facilitate the strategic development of trauma care in Ireland by monitoring processes and outcomes and the effects of changes in trauma service provision., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Introduction: Low systolic blood pressure (SBP) is an important secondary insult following traumatic brain injury (TBI), but its exact relationship with outcome is not well characterised. Although a SBP of <90 mmHg represents the threshold for hypotension in consensus TBI treatment guidelines, recent studies suggest redefining hypotension at higher levels. This study therefore aimed to fully characterise the association between admission SBP and mortality to further inform resuscitation endpoints., Methods: We conducted a multicentre cohort study using data from the largest European trauma registry. Consecutive adult patients with AIS head scores >2 admitted directly to specialist neuroscience centres between 2005 and July 2012 were studied. Multilevel logistic regression models were developed to examine the association between admission SBP and 30 day inpatient mortality. Models were adjusted for confounders including age, severity of injury, and to account for differential quality of hospital care., Results: 5057 patients were included in complete case analyses. Admission SBP demonstrated a smooth u-shaped association with outcome in a bivariate analysis, with increasing mortality at both lower and higher values, and no evidence of any threshold effect. Adjusting for confounding slightly attenuated the association between mortality and SBP at levels <120 mmHg, and abolished the relationship for higher SBP values. Case-mix adjusted odds of death were 1.5 times greater at <120 mmHg, doubled at <100 mmHg, tripled at <90 mmHg, and six times greater at SBP<70 mmHg, p<0.01., Conclusions: These findings indicate that TBI studies should model SBP as a continuous variable and may suggest that current TBI treatment guidelines, using a cut-off for hypotension at SBP<90 mmHg, should be reconsidered., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Traumatic injury is the leading cause of death in the first four decades of life. However, current estimates for traumatic injury rates fail to take into account burns. The aim of this work was to estimate the contribution of burns to serious traumatic injury in England and Wales. We have determined population-based burns rates using the International Burn Injury Database (iBID, www.ibidb.org) which collects data from regional burn centres, and non-burns rate using data from the Trauma Audit and Research Network (TARN) which collects data from emergency departments (ED, www.TARN.ac.uk). Due to incomplete national coverage of TARN, non-burns rates were estimated using data from 94 EDs that contributed data to TARN. Both non-burn and burns rates were calculated nationally and for each regional burn service catchment area (n=17). Only serious injuries (≥72 h admission or death) were included. Burns rate was 4.7 and non-burns rate 82.7 per 100,000 per year nationally. Burns therefore contributed 5.4% of all serious traumatic injuries. Contribution of burns in different regional burn service catchment areas was between 1.5% and 12%. This data suggests that burns contribute significantly to the overall trauma workload, and should be carefully considered in healthcare planning and policy., (Copyright © 2011 Elsevier Ltd and ISBI. All rights reserved.)

Background: In the Trauma Audit and Research Network (TARN), currently the largest trauma network in Europe, outcome prediction is performed using the TRISS methodology since 1989. Its database contains 200,000 hospital admissions from 110 hospitals over the country, but a large amount of data is lost for the modelling because of missing data. To improve some of the shortcomings of TRISS a new model was developed., Methods: The data for modelling consisted of 100,399 hospital trauma admissions over the period 1996 to 2001. Using the Glasgow Coma Score (GCS) instead of RTS has dramatically reduced the number of missing cases. Gender and its interaction with age have also been included in the model. The model was tested on different subsets of cases traditionally excluded, such as children, those with penetrating injuries, and ventilated and transferred patients. The new model included all those subsets using age, a transformation of ISS, GCS, gender and gender by age interaction as predictors., Results: The model has shown a good discriminant ability tested by the area under the receiver operating characteristic (AROC) curve. The values of the AROC for the new model were 0.947 (95% CI: 0.943-0.951) on the prediction set and 0.952 (95% CI: 0.946-0.957) on the validation set compared respectively with 0.937 (95% CI: 0.932-0.943) and 0.941 (95% CI: 0.936-0.952) for TRISS., Conclusion: The new model has enabled us to include most of the cases that were excluded under the TRISS's inclusion criteria, less missing data are incurred and the predictive performance was significantly better than that of the TRISS model as shown by the AROC curves.