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Professor Jonathan Morris
Sydney Health Partners researchers are using cutting-edge analytics and informatics techniques to mine de-identified hospital patient records, with the aim of demonstrating that better use of data can improve health care.
A multidisciplinary team led by Professors David Brieger from Concord Hospital and Jonathan Morris from Royal North Shore Hospital, is using previously untapped information stored in the hospital records of a select group of patients who present with acute chest pain.
The SPEED-EXTRACT project uses a variety of de-identified patient data from Royal North Shore, Ryde and Hornsby hospitals, including doctor’s notes stored in Electronic Medical Records (EMR).
Utilising this information, the researchers are able to characterise the management and outcomes of patients suspected of suffering from a very serious type of heart attack known as ST Elevation Myocardial Infarction (STEMI).
“There is clear guidance for the treatment of these patients, and we are now in a position to explore and understand the reasons for variation in care across institutions in NSW,” said Professor Morris, who is the Director of Biomedical and Health Informatics at the University of Sydney.
“One of Sydney Health Partners’ aims is to demonstrate through inter-disciplinary research that, by extracting knowledge from diverse data types housed within the EMR and applying cutting-edge machine learning techniques, we can improve the appropriateness, specificity and efficiency of health care delivery.”
The SPEED-EXTRACT project requires a multidisciplinary team of cardiologists, digital health experts, engineers and data scientists from across Sydney Health Partners’ membership, including the University of Sydney, Northern Sydney, Western Sydney and Sydney Local Health Districts, The Centre for Translational Data Science and Sydney Informatics Hub.
Professor Morris said that if the study does prove the feasibility of data extraction from EMR, the next step would be to standardise the process and scale it up to improve the care of acute coronary patients across the health system.
“We hope this study will provide a foundation for a future where near real-time clinical data audits and feedback-driven practice improvement support clinical decision-making, inform continuing medical education and lead to better patient health outcomes.”