Predicting patients’ likelihood of discharge from the hospital has proven to be a cost-saving measure for a major tertiary acute care hospital in South Australia. Lyell McEwin Hospital in Adelaide successfully implemented a machine learning algorithm called Adelaide Score in a recent trial, developed in collaboration with the University of Adelaide.
The AI model analyzes vital signs and laboratory test data to predict potential patient discharge within the next 12 and 24 hours, based on information collected from the past 48 hours through an EMR system. During a 28-day trial last year, the system was used to evaluate electronic records of inpatients across 18 surgical and medical teams, screening and ranking patients who were likely due for discharge.
The results of the trial were promising, with a 5% seven-day patient readmission rate, lower than the previous year’s 7.1%, and a median stay of 2.9 days, down from 3.1 days. This reduction in patient admissions saved the hospital approximately A$735,708, demonstrating the potential cost-saving benefits of utilizing AI in healthcare.
Dr. Joshua Kovoor, the study’s first author, highlighted the importance of the Adelaide Score in addressing ambulance ramping issues in South Australia. By streamlining the discharge process and identifying patients ready for discharge, the AI model aims to alleviate congestion in emergency departments and reduce unnecessary hospital stays and readmissions, ultimately leading to cost savings.
The Adelaide Score’s success at Lyell McEwin Hospital has sparked interest in potential implementation across eastern states of Australia and collaborative opportunities abroad. Dr. Stephen Bacchi, the senior author of the study, mentioned ongoing discussions with key stakeholders regarding future expansion of the AI model.
In addition to AI integration, the South Australian government has also embraced telehealth and virtual care models to improve healthcare accessibility and address system congestion. Initiatives such as free telehealth services for adults, children, and seniors, as well as a 24/7 remote health monitoring service for remote and rural communities, have been trialed and implemented to enhance healthcare delivery in the region.
The successful application of AI and telehealth technologies in South Australia reflects a broader trend towards innovative healthcare solutions that prioritize efficiency, cost-effectiveness, and patient-centered care. As the healthcare landscape continues to evolve, leveraging cutting-edge technologies like AI and telehealth will be essential in optimizing healthcare delivery and improving patient outcomes.
