Sepsis is a time critical medical emergency that arises when the body starts to attack its own tissues and organs in response to an infection. Sepsis can result in organ dysfunction, multi-organ failure and death if not treated promptly, and is a leading cause of death in children worldwide. Sepsis often presents with non-specific signs common to many mild infections, making it difficult to detect early and accurately, leading to delaying appropriate treatments and resulting in severe sepsis. Therefore, it is vital to identify new approaches to rapidly identify the type of infection and predict the severity of the condition in patients presenting with suspected sepsis to enable early initiation of appropriate treatments.
Recent advances in genomic technologies have shown that gene expression based infection testing has the potential to provide much faster and more precise results. This results in more accurate diagnosis of infections and appropriate timely treatments. Our study will utilise an advanced gene expression analysis approach named single-cell RNA sequencing to identify new approaches for sepsis diagnosis. This could lead to development of a rapid testing method which can predict the type of infection (bacterial or viral) and the severity of the condition with a quick turnaround time for results, improving patient outcomes, reducing unnecessary antibiotic use, and shortening hospital length of stay.READ MORE
In-flight hypotension (low blood pressure) leading to patient deterioration is a common and challenging clinical problem in aeromedical trauma patients. Predicting this risk is currently primarily based on clinical gestalt, without specific validated risk prediction tools. The Triage Revised Trauma Score (TRTS) is a clinical risk prediction tool calculated using only vital signs, making it well suited to the resource-limited pre-hospital environment.
A Life Flight Retrieval Medicine internal audit in 2021 suggested an association between the TRTS and in-flight hypotension for trauma patients. Based on these preliminary findings, this study will address the research question, “what is the relationship between pre-flight TRTS and in-flight hypotension in trauma patients undergoing aeromedical retrieval?”.
Knowledge gained from this study may allow aeromedical doctors to make more informed decisions about their patients before aeromedical transport.READ MORE
Feedback improves performance. Yet establishing effective feedback practices in emergency medicine (EM) is challenging. Supervisors need to balance delivering patient care with delivering feedback in fast-paced environments. These challenges are particularly burdensome in regional settings where the workforce is less experienced, and teams are less established.
To resolve this challenge, efforts are often directed towards developing supervisors’ feedback skills. Yet with the challenges experienced by regional EM supervisors, the model of ‘supervisor driving feedback’ is inefficient. What has been overlooked is developing trainees as active participants in feedback practices. Evidence suggests that this approach may improve feedback practices in EM and offers a way to alleviate the feedback burden experienced by EM supervisors in regional settings.READ MORE
This study will adopt a system-wide view to capture relationships and interactions between flow metrics to identify access issues and inform the design of interventions/solutions to improve patient flow at a system level. A system-wide approach covering prehospital and ED services offers the potential for improving patient flow at the ambulance/hospital interface. By integrating ambulance, ED and inpatient data, it is possible to identify blockages along the entire patient journey that have a flow-on effect on ED access. It is also possible to identify critical hospital and ambulance service levels when performance starts to degrade, suggesting where the system would benefit from revised strategies.
The project ‘Study on Patient Flow in Queensland’s public hospitals’ is conducted by a research team comprising experts from CSIRO, Queensland Health, UQ and QAS.READ MORE
Emergency department (ED) waiting times are a significant predictor of the patient experience.
Simple prediction methods, such as rolling average, are used by hospitals in Australia to predict waiting time for patients. Although this approach is inexpensive to implement, the forecasts have limited accuracy and consequently most Australian hospital EDs do not report expected waiting times to the public.
A solution that is capable of sourcing data from ED information systems and feed it into prediction models to generate waiting time forecasts would bring practical benefits for staff and patients. There is also potential to assist clinicians and nurses to estimate demand for care and calibrate workflow.
For patients, the knowledge may reduce anxiety associated with uncertainty about the waiting time and reduce the number of patients who leave before treatment.
This project aims to use advanced statistical models and machine-learning algorithms to capture dynamic fluctuations in waiting time, to implement and validate the prediction performance of these models. The project will also build ED research capacity by educating staff on forecast modelling and data management techniques.READ MORE
Australia is five years behind the US’ opioid epidemic (>15,000 US deaths/year). General Practitioners and EDs frequently prescribe opioids for isolated musculoskeletal pain (e.g. “whiplash”) from RTCs, but this potentially inappropriate opioid prescribing likely leads to unnecessary opioid exposures. In the last decade, opioid overdoses in Australia have more than doubled. 75% of opioid overdose deaths involve prescription opioids; annual death rates exceed road traffic deaths.
Emergency Departments (EDs) commonly prescribe opioids on discharge for patients with non-serious road traffic crash (RTC) injury. This potentially compromises recovery and contributes to continued opioid use and potential misuse in the community.
The project will address the gap on whether, or for how long, short courses of opioids are continued following acute non-serious RTC injury, and to what extent this causes subsequent problems, by measuring patterns of use, impacts, and costs of opioid use in EDs and following discharge over a 12-month period.
The project will provide the first Australian data on opioid prescribing in ED for acute minor RTC injuries and link ED data to community data to explore longitudinal prescribing patterns post RTC.READ MORE
Sepsis is devastating infection, leading to organ dysfunction. Sepsis kills more children in Australia than road traffic accidents. One out of three survivors will suffer from long-term health problems. Faster recognition of sepsis can save lives. However, recognising sepsis in children can be difficult, as children with sepsis initially present with symptoms similar to common infections. Currently, the recognition of sepsis is based on physician assessment of patients, and laboratory tests. Sadly, a common finding in Coroner`s investigations of sepsis deaths is that parents represented several times to health-care facilities, stating their concerns that “something is wrong” with their child. There is at present great debate as to what role parental concern should have in sepsis recognition.
We hypothesise that parents as experts of their child provide important information to recognise disease severity in their child. We will perform questionnaires with parents, and with medical and nursing staff when a child is evaluated for sepsis. We will compare the value of measuring parental concern in comparison to healthcare worker assessment, clinical signs and symptoms, and routine infection markers.READ MORE
Our study aims to test whether a mindfulness program delivered by a smartphone app can reduce occupational stress levels among Emergency Department (ED) staff. This study will recruit staff at two regional EDs. Staff will practice short session mindfulness daily, for four weeks, using a smartphone meditation app. The study will determine if, by using the app, staff levels of occupational stress are reduced and overall wellness increased. The levels of stress reduction will be compared before and after the intervention.
Working in an ED can be stressful. It has been suggested that up to half ED doctors and nurses may suffer from burnout due to high workload, overcrowding and limited resources. Staff stress and its negative consequence pose challenging issues to both individual clinicians and healthcare organisations. Sub-optimal wellness of staff is closely associated with poor patient care, more medical incidents and a high staff turnover rate. One way to reduce staff stress levels is by promoting staff coping skills and wellness. Mindfulness is a mental technique to focus self-awareness at the present moment and non-judgmentally. It has been used widely to promote staff workplace wellness. Smartphone apps are a relatively new delivery method for mindfulness that has not yet been tested among ED staff.READ MORE
Queensland is known for its ability to attract mass gathering events of international significance, such as the 2018 Commonwealth Games, 2023 FIFA Women’s World Cup and the 2032 Olympic Games. Such events have the potential to impact the normal operational capacity of our emergency health services.
The objective of this study is to describe the impact of the 2018 Commonwealth Games on the emergency departments in the Gold Coast region. This research has two key aims, which align with two discrete but related studies:
Study 1 Aim: To describe and determine whether changes in patient, health service, and economic outcomes occur before, during and after the Commonwealth Games.
Study 2 Aim: To explore healthcare staff experience of planning, preparedness and lessons learnt from the Commonwealth Games.
Patient health records contain a significant amount of information through each episode of care provided at a healthcare facility. However, due to the unstructured nature of the clinical information in each record, the clinical data is not readily accessible for research or administrative use unless an expensive and time-consuming manual process is used. Methods of data extraction through various algorithms are available but require training and testing a dataset of annotated health records.
To address this issue, my key aim is to generate structured clinical data from previously inaccessible and unstructured electronic records. I am attempting to develop a process of automatically extracting clinical data from electronic records of patients who present with chest pain to emergency departments in Queensland. The clinical data extracted will be composed of the documented cardiac risk stratification for each patient and major adverse cardiac events.
To develop this data extraction process, an annotation scheme was designed using a widely accepted standardized reporting guideline. Using the annotation scheme, emergency clinicians annotate patient records to produce an annotated dataset for both training and testing machine learning algorithms.READ MORE