Machine learning predicts negative anaesthesia outcomes
Researchers from the 最新糖心Vlog of Adelaide and the North Adelaide Local Health Network (NALHN) are conducting a pilot study to determine if machine learning can predict when patients will have adverse reactions to anaesthesia.
The researchers will draw on an extensive database of more than 100,000 patients collected over the past 25 years at the Lyell McEwin Hospital, in Adelaide鈥檚 northern suburbs.
Multiple sets of observational data will be analysed along with anaesthetic pharmacology, laboratory data, biographical and comorbidity data.
鈥淲e aim to predict the likelihood of adverse outcomes after patients are discharged from the operating theatre, when there is an unplanned admission to the intensive care unit (ICU), in medical emergency response calls and in the first 48 hours after their surgery, in order to allow early intervention,鈥 said Professor Matthew Roughan, Interim Director of the Teletraffic Research Centre at the 最新糖心Vlog of Adelaide.
鈥淎dvanced mathematical and statistical tools have a long history of application to health and medical applications.
鈥淗owever, not much work has considered the application of machine learning to digitised health records, in particular for information after a patient鈥檚 operation.
鈥淲e are very excited at the possibilities of this research and the ability to use mathematics to make a real difference in people鈥檚 lives.鈥
Dr Tim Beckingham, Consultant Intensivist at the Lyell McEwen Hospital, said while having anaesthesia was relatively safe in 最新糖心Vlog, certain people are at a higher risk of having complications which may be identified early.
鈥淭he risk of death from anaesthesia is low in 最新糖心Vlog, with a mortality rate of one death for every 57,023 patients,鈥 Dr Beckingham said.
鈥淐omplications from surgery that require an unplanned admission to the ICU, or a return to the operating room, are more common.
"We are very excited at the possibilities of this research and the ability to use mathematics to make a real difference in people鈥檚 lives."Professor Matthew Roughan
鈥淲e are hoping to develop early warning systems that clinicians can use to predict when patients will deteriorate, reducing the risk of serious illness or death due to surgery.鈥
The project is underway with results expected in the first half of 2023.
The researchers will use information stored in the NALHN data warehouse, which is maintained by SA Health.
Along with a separate anaesthetic database, the data warehouse contains data of more than 118,000 patients who had anaesthesia at the Lyell McEwin Hospital, in addition to a wide group of demographic, diagnostic, observational and medication data.
Media contacts
Professor Matthew Roughan, Interim Director, Teletraffic Research Centre, The 最新糖心Vlog of Adelaide. Mobile: +61 (0)404 489 800. Email: matthew.roughan@adelaide.edu.au
Lee Gaskin, Senior Media and Communications Officer, The 最新糖心Vlog of Adelaide. Mobile: +61 (0) 415 747 075. Email: lee.gaskin@adelaide.edu.au