The DARE Centre opened in May 2018.

Data science and data analytics

Data science greatly accelerates the rate of clinical research findings, allows for the analysis of more complex datasets than traditional research, and provides clinicians with information that allows them to make data-driven decisions.

The field of big data analytics is developing quickly, and the establishment of the DARE Centre places Austin Health at the forefront of this new area of research, particularly in healthcare

Our mission

• To develop and expand analytic ability and capacity in relation to electronic data available in the Austin Clinical Research Data Warehouse and beyond
• To use our analytic ability to conduct research in multiple aspects of hospital care at Austin Health and beyond with the aim of improving patient care and outcomes

Our research

Researchers at the Centre published their first research paper in August 2018 in the Journal of Critical Care. That research showed that it is possible to identify which patients presenting to the Emergency Department with a suspected infection (sepsis) are at higher risk of mortality and a long stay in the Intensive Care, using three pieces of data: blood pressure, respiratory rate and mental functioning.

We have an expanding number of research projects generated via large electronic data sets at Austin Health and published in high quality peer-reviewed international journals. A landmark paper published in Intensive Care Medicine has used the power of natural language processing to improve detection of possible delirium in intensive care unit patients and has garnered international attention.

The DARE Centre is currently collaborating on research with a number of the other departments at Austin Health, including Oncology, Intensive Care, Emergency Medicine, Anaesthesia, Spinal, Endocrinology, Cardiac Surgery, Renal, Infectious Diseases, and others.

Projects underway include:

• Predicting the outcome of major surgery in the very elderly (people over the age of 80);
• Determining the significance of having anaemia for people having abdominal surgery (in collaboration with Anaesthesia);
• Using data available on admission to identify which patients will be in hospital for longer than a week (particularly in collaboration with General Medicine), so as to identify interventions that may reduce these patients' hospital stay; and
• Using natural language processing to identify cancer and Intensive Care patients with delirium from doctors' patient notes, and following up the treatment that they receive.

Data science greatly accelerates the rate of clinical research findings, allows for the analysis of more complex datasets than traditional research, and provides clinicians with information that allows them to make data-driven decisions.

For more information or to make an enquiry, please contact:

Professor Rinaldo Bellomo
Director, Data Analytics Research and Evaluation Centre
rinaldo.bellomo@austin.org.au

Dr. Natasha Holmes
Senior Research Fellow
natasha.holmes@austin.org.au