The epidemiology of critically ill patients in urban Australia and the impact of Cultural And Linguistic Diversity (CALD) on emergency medicine.

Emergency Departments (EDs) are the frontline of the Australian Healthcare system and represents the first step in a patient’s hospital presentation and journey. The ED provides life-saving treatment and urgent care to undifferentiated patients presenting with a myriad of conditions ranging from the most benign to life-threatening with known or unknown medical histories and underlying pre-existing conditions.

Yet, Australian researchers, ED healthcare providers, and healthcare policymakers are bereft of a deep clinical epidemiological erudition of Australia’s annual over 8 million ED presentations, particularly knowledge of who presents to the ED (and from where), their  severity at presentation, and whether the ED and healthcare professionals provide quality and equitable care effectively. Knowledge of this may well lead to improvements in the quality, equity, and efficiency of care provided to all ED patients as well as improved ED resource allocation. These questions can be easily and inexpensively answered with the use of clinical epidemiology and data mining techniques.

This PhD aims to provide an initial insight into the epidemiology, socio-demographics, demographics, mapping, and predicative modelling of patients with and without a CALD background presenting to Australian EDs, focusing on EDs within the South West Sydney Local Health District (SWSLHD). To achieve this, SWSLHD 2018-2019 ED and in-hospital data were electronically linked together and the data was utilised to describe the cultural and ethnic differences between patients with and without a CALD background presenting to SWSLHD EDs in terms of patient presentation, utilisation, and timeliness of critically important diagnostic and imaging investigations, treatment interventions, and patient outcomes. The thesis will then discuss the impact of having a CALD background and socio-cultural factors on their ED presentation and clinical outcomes and provide a sub-analysis of the traditional CALD definition to allow explanatory factors and granularity to be seen. From there, the data will be mapped to indicate where patients come from and predicatively model which patients have a higher risk in presenting with suspected sepsis and which group is physiologically more unstable on arrival to the ED.