One in four surgery patients encounters major complications, making surgery the third leading global cause of mortality. In Australia, 1 in 5 citizens are diagnosed with cancer, with 60 per cent requiring surgery.
Electronic Health Records (EHR) promise to reshape patient care by constructing risk predictive models. Existing risk calculators designed for non-cancer surgeries overlook the unique needs of Australian cancer patients.
Dr Ismail developed an AI-based Baseline Predictive Model, in collaboration with the Melbourne Data Analytics Platform (MDAP) using a North American dataset. ANCHOR seeks to validate this model for Australian cancer surgical patients, using data from the Peter MacCallum Cancer Centre (PMCC). Utilizing Artificial Intelligence, the project aims to craft a Surgical Risk Calculator tailored to the nuances of cancer surgery. Supported by PMCC's Department of Digital Innovation, MDAP, and the clinical leadership of chief investigator A Ismail, and associate investigators Professors Riedel and Denehy, with a decade-long focus on cancer surgery pre-optimization, the project will Integrate a Clinical Decision Support System (CDSS) to guide clinicians optimize modifiable risks and reshape patient outcomes.
The collaboration of health informatics, data analytics, artificial intelligence, and clinical expertise holds transformative potential for cancer perioperative care in Australia.
Dr Hilmy Ismail, Associate Professor Kate Burbury, Dr Jason Li, Peter MacCallum Cancer Centre, Melbourne.
The project was awarded A$89,267 (including scholarship) funding through the ANZCA research grants program for 2024.