Quantifying Spatial and Temporal Variation in Injury-Related Bloodstream Infections across Queensland, 2000-2019
Conference
Format: CPS Abstract - TIES 2024
Keywords: "bayesian, "data_linkage, bloodstream_infections, injuries, spatio-temporal, spatiotemporal
Abstract
Injuries are a leading cause of hospitalisation, disability and deaths in Australia, making them a major health concern and a national health priority. Bloodstream infection (BSI) is a serious complication among injured patients. Despite Queensland being the second largest state by area in Australia, the major trauma centres are only in Brisbane and Townsville. Injured people residing far away from Brisbane and Townsville must travel a significant distance to access specialised care. BSIs can also be influenced by seasonal variations, but the impact of residential location and seasonal changes on injury-related BSIs in Queensland is unknown. This study aimed to examine the disparities in residential location and the effect of temporal variations on people with injury-related BSIs in Queensland using population-based linked data. The linked data for this study consists of patient admission data from Queensland Hospital Admitted Patient Data Collection (QHAPDC), pathology data from AUSLAB and death data from the Death Registry for Queenslanders across 20 years from 2000 - 2019. Besag-York-Mollié (BYM) models were fitted to examine the spatial variations and Bayesian spatio-temporal conditional autoregressive models were fitted to examine the spatio-temporal variations. Markov Chain Monte Carlo simulations were used to fit the models. Across the entire 20 year period, 4530 people experienced an injury-related BSI. There was marked spatial variation across the state, with particularly high rates observed in remote and very remote areas in Queensland. Bayesian spatial and spatio-temporal models enable the identification of high-risk areas and periods with higher incidence. The results are beneficial for medical staff and policymakers to identify the disparities in care and improve patient outcomes.