AI-powered tool predicts health risks in aged care
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An AI-powered tool developed by Telstra Health and RMIT University is transforming the way aged care facilities monitor and manage residents' health by predicting risks such as falls, depression, and mortality.
With nearly half a million older Australians relying on aged care services as of June 30, 2023, the sector faces immense pressure to provide high-quality care.
In response, the collaboration between Telstra Health, RMIT University, and the Digital Health Cooperative Research Centre has resulted in an AI-driven tool designed to predict health risks and improve care outcomes in aged care settings.
Dr. Tabinda Sarwar, the project lead and data scientist from RMIT University, highlights the significance of the tool in alleviating the strain on nursing staff.
"The tool is capable of automatically monitoring both structured and free-text electronic patient records for 36 evidence-based indicators of deterioration," Dr. Sarwar explains. "These indicators help predict various health risks, supporting nursing staff and improving resident care."
Aged care nursing staff juggle numerous responsibilities, including daily caregiving and health monitoring.
Given the heavy workload, manual screening tools are not always practical. The new digital health tool is designed to reduce this burden by predicting adverse health events before they occur, making it a game-changer for aged care facilities.
The tool, which has won the 2024 Research Australia's Digital & Data Health Innovation Award, analyzes daily operational data, including health-related notes and records.
Using advanced natural language processing (NLP) and machine learning techniques, the tool generates predictive alerts for potential health risks like falls, depression, and even mortality.
"By applying advanced data analysis to daily-collected information, we are able to predict signs of deterioration, giving care teams more time to respond," Dr. Sarwar says. "This includes assessing risks such as falls, depression, and mortality based on data extracted from geriatric assessments, observation charts, and progress notes."
The collaboration leveraged Telstra Health's Clinical Manager system, which is already deployed in over 360 facilities across Australia, ensuring a broad reach.
The project also benefited from the expertise of nursing staff and the support of the Digital Health CRC, bridging the gap between academia and industry to create a highly effective solution.
Developing a universal tool that could address diverse challenges faced by nursing staff across different aged care facilities was a significant hurdle. "We had to design a solution that could have a meaningful impact on a larger population," Dr. Sarwar explains.
To ensure the tool's usability, the team conducted independent studies, using statistical and machine learning techniques to validate its performance and clinical feasibility.
The tool is currently being rolled out by Telstra Health, with several aged care homes already expressing interest in adopting it.
While its potential for expansion is significant, including applications in hospitals and other healthcare settings, the next steps depend on Telstra Health's future strategies.
"This tool has the potential to extend to various healthcare settings and could play a key role in transforming the healthcare industry," Dr. Sarwar concludes, emphasizing the wide-reaching impact of this AI-driven solution in improving healthcare outcomes for vulnerable populations.
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AI-powered tool predicts health risks in aged care
Listen to article An AI-powered tool developed by Telstra Health and RMIT University is transforming the way aged care facilities monitor and manage residents' health by predicting risks such as falls, depression, and mortality. With nearly half a million older Australians relying on aged care services as of June 30, 2023, the sector faces immense pressure to provide high-quality care. In response, the collaboration between Telstra Health, RMIT University, and the Digital Health Cooperative Research Centre has resulted in an AI-driven tool designed to predict health risks and improve care outcomes in aged care settings. Dr. Tabinda Sarwar, the project lead and data scientist from RMIT University, highlights the significance of the tool in alleviating the strain on nursing staff. "The tool is capable of automatically monitoring both structured and free-text electronic patient records for 36 evidence-based indicators of deterioration," Dr. Sarwar explains. "These indicators help predict various health risks, supporting nursing staff and improving resident care." Aged care nursing staff juggle numerous responsibilities, including daily caregiving and health monitoring. Given the heavy workload, manual screening tools are not always practical. The new digital health tool is designed to reduce this burden by predicting adverse health events before they occur, making it a game-changer for aged care facilities. The tool, which has won the 2024 Research Australia's Digital & Data Health Innovation Award, analyzes daily operational data, including health-related notes and records. Using advanced natural language processing (NLP) and machine learning techniques, the tool generates predictive alerts for potential health risks like falls, depression, and even mortality. "By applying advanced data analysis to daily-collected information, we are able to predict signs of deterioration, giving care teams more time to respond," Dr. Sarwar says. "This includes assessing risks such as falls, depression, and mortality based on data extracted from geriatric assessments, observation charts, and progress notes." The collaboration leveraged Telstra Health's Clinical Manager system, which is already deployed in over 360 facilities across Australia, ensuring a broad reach. The project also benefited from the expertise of nursing staff and the support of the Digital Health CRC, bridging the gap between academia and industry to create a highly effective solution. Developing a universal tool that could address diverse challenges faced by nursing staff across different aged care facilities was a significant hurdle. "We had to design a solution that could have a meaningful impact on a larger population," Dr. Sarwar explains. To ensure the tool's usability, the team conducted independent studies, using statistical and machine learning techniques to validate its performance and clinical feasibility. The tool is currently being rolled out by Telstra Health, with several aged care homes already expressing interest in adopting it. While its potential for expansion is significant, including applications in hospitals and other healthcare settings, the next steps depend on Telstra Health's future strategies. "This tool has the potential to extend to various healthcare settings and could play a key role in transforming the healthcare industry," Dr. Sarwar concludes, emphasizing the wide-reaching impact of this AI-driven solution in improving healthcare outcomes for vulnerable populations.
