Two public hospitals within the Central Adelaide Local Health Network (CALHN) have become the first in Australia to implement an artificial intelligence system providing advanced warning to medical staff of patients deteriorating.
CALHN said in a statement that the Ainsoff system monitored a host of patient variables and pathology results and used machine learning to anticipate deteriorations in patient status, automatically alerting medical staff and allowing them to intervene sooner.
“Following a successful silent trial, a live trial is now underway at the Royal Adelaide Hospital and the Queen Elizabeth Hospital,” CALHN said.
“Early reports from staff show the system is already providing benefits,” it said.
“By supplying clear and immediate information on patient deterioration, it empowers nursing staff to lead the decision-making process with the clinical team.”
CALHN said the success of the silent trial encouraged the launch of a live three-month trial in the same four wards to notify nursing shift coordinators with important alerts by text message.
“After six weeks, staff will begin analysing the effect, starting by examining the number of daily alerts generated per ward,” it said.
“If the system is proven to be successful, Ainsoff could then be rolled out across CALHN.”
CALHN said that experienced medical doctors and computer scientists developed the Ainsoff system to monitor patients the way a senior clinician would.
“The current Electronic Medical Record system alerts medical staff if there is an issue with a given observation based on set criteria,” it said.
“Ainsoff, however, monitors for changes in blood pressure, heart rate, respiratory rate, oxygen saturation, temperature and renal function, and delivers a tailored text message to nursing shift coodinators with a summary of the patient’s vital signs, their location and their risk of deterioration,” CALHN said.
