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1.
Australas Emerg Care ; 26(4): 308-313, 2023 Dec.
Article in English | MEDLINE | ID: mdl-36934014

ABSTRACT

BACKGROUND: The leading global cause of death for people aged 5-29 years is road traffic injury, a quarter of which is borne by pedestrians. The epidemiology of major hospitalised pedestrian injury across Australia is not reported. This study aims to address this gap using data from the Australia New Zealand Trauma Registry. METHODS: The registry hosts information on patients admitted to 25 major trauma centres across Australia who sustain a major injury (ISS > 12) or die following injury. Patients were included if they were injured due to pedestrian injury from 1st July 2015-30 th June 2019. Analysis included patient and injury characteristics, injury patterns and in-hospital outcomes. Primary endpoints included risk-adjusted mortality and length of stay. RESULTS: There were 2159 injured pedestrians; of these, 327 died. Young adults (20-25 years) were the largest group, especially on weekends. Older adults (70 + years) were the largest cohort in pedestrian deaths. The most common injuries were head (42.2 %). One-third of patients were intubated prior to or on ED arrival (n = 731, 34.3 %). CONCLUSION: Emergency clinicians should have a high index for severe pedestrian injury. Further reduction in road speed in residential areas could reduce all-age pedestrian injury in Australia.


Subject(s)
Pedestrians , Young Adult , Humans , Aged , New Zealand/epidemiology , Accidents, Traffic , Australia/epidemiology , Registries , Hospitals
2.
Injury ; 53(6): 1893-1903, 2022 Jun.
Article in English | MEDLINE | ID: mdl-35369988

ABSTRACT

INTRODUCTION: In Australia, people living in rural areas, compared to major cities are at greater risk of poor health. There is much evidence of preventable disparities in trauma outcomes, however research quantifying geographic variations in injuries, pathways to specialised care and patient outcomes is scarce. AIMS: (i) To analyse the Australia New Zealand Trauma Registry (ATR) data and report patterns of serious injuries according to rurality of the injury location ii) to examine the relationship between rurality and hospital mortality and iii) to compare ATR death rates with all deaths from similar causes, Australia-wide. METHOD: A retrospective cohort study of patients in the ATR from 1st July 2015 to 30th June 2019 was conducted. Descriptive analyses of trauma variables according to rurality was performed. Logistic regression quantified the moderating effect of rurality on trauma variables and hospital mortality. Australian death data on similar injuries were sourced to quantify the additional mortality attributable to severe injury occurring outside Major Trauma Centres (MTCs). RESULTS: Compared to major cities, rural patients were younger, more likely to have spinal cord injuries, and sustain traffic-related injuries that are 'off road'. Injuries occurring outside people's homes are more likely. Mortality risk was greater for patients sustaining severe traumatic brain injury (TBI) spinal cord injury (SCI) and head trauma in addition to intentional injuries. Compared to the ATR data, Australian population-wide trauma mortality rates showed diverging trends according to rurality. The ATR only captures 14.1% of all injury deaths occurring in major cities and, respectively, 6.3% and 3.2% of deaths in regional and remote areas. CONCLUSION: Compared to major cities, injuries occurring in rural areas of Australia often involve different mechanisms and result in different types of severe injuries. Patients with neurotrauma and intentional injuries who survived to receive definitive care at a MTC were at higher risk of hospital death. To inform prevention strategies and reduce morbidity and mortality associated with rural trauma, improvements to data systems are required that involve data linkage and include information about patient care from pre-hospital providers, regional hospitals and major trauma centres.


Subject(s)
Wounds and Injuries , Australia/epidemiology , Hospital Mortality , Humans , New Zealand/epidemiology , Registries , Retrospective Studies
3.
BMJ Open ; 11(8): e050795, 2021 08 23.
Article in English | MEDLINE | ID: mdl-34426470

ABSTRACT

OBJECTIVES: Adequate risk adjustment for factors beyond the control of the healthcare system contributes to the process of transparent and equitable benchmarking of trauma outcomes. Current risk adjustment models are not optimal in terms of the number and nature of predictor variables included in the model and the treatment of missing data. We propose a statistically robust and parsimonious risk adjustment model for the purpose of benchmarking. SETTING: This study analysed data from the multicentre Australia New Zealand Trauma Registry from 1 July 2016 to 30 June 2018 consisting of 31 trauma centres. OUTCOME MEASURES: The primary endpoints were inpatient mortality and length of hospital stay. Firth logistic regression and robust linear regression models were used to study the endpoints, respectively. Restricted cubic splines were used to model non-linear relationships with age. Model validation was performed on a subset of the dataset. RESULTS: Of the 9509 patients in the model development cohort, 72% were male and approximately half (51%) aged over 50 years . For mortality, cubic splines in age, injury cause, arrival Glasgow Coma Scale motor score, highest and second-highest Abbreviated Injury Scale scores and shock index were significant predictors. The model performed well in the validation sample with an area under the curve of 0.93. For length of stay, the identified predictor variables were similar. Compared with low falls, motor vehicle occupants stayed on average 2.6 days longer (95% CI: 2.0 to 3.1), p<0.001. Sensitivity analyses did not demonstrate any marked differences in the performance of the models. CONCLUSION: Our risk adjustment model of six variables is efficient and can be reliably collected from registries to enhance the process of benchmarking.


Subject(s)
Hospitals , Risk Adjustment , Aged , Australia/epidemiology , Humans , Length of Stay , Male , Registries
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