Home | News | New software to help providers better prepare for end of life, reduce ED presentations

New software to help providers better prepare for end of life, reduce ED presentations

New software could predict the failing health of aged care residents and reduce presentations at hospital emergency departments.

According to the Australian Institute of Health and Welfare, there are approximately 270,559 people aged 65 and over in aged care, and these residents make up between 20 and 40 per cent of all emergency department presentations.

The clinical decision support software is being developed as part of Telstra Health’s residential aged care software suite over the next two years, in a $1 million partnership with RMIT University, Telstra Health and the Digital Health Cooperative Research Centre.

The clinical decision support software to predict deterioration, which is already used in acute care settings, will be introduced into the aged care setting with a view to treating patients earlier and provide earlier notice when a resident is nearing the end of life.

Dr Victor Pantano, CEO of the Digital Health CRC said: “Emergency hospitalisations are not only stressful for aged care residents and their families, but they also place significant additional demand on hospitals.

“Similarly, the earlier we can ascertain that an aged care resident is approaching end of life, the earlier we can enact their advance care plan and honour their preferences – an important process for the aged care resident, their carers and families, and the aged care provider.”

The team hope that better prediction of care needs will enable providers to be more effective in planning for staffing and clinical resources.

RMIT Professor of Computer Science, Lawrence Cavedon, said the research team will work with gerontologists and aged care staff to interpret historical data and develop new predictive analytics techniques, as well as adapting existing decision support methods from the acute care sector.

“Researchers will work closely with clinicians to understand reliable signs of patient deterioration, how this might be identified from recorded data, and to manage any related ethical issues,” Professor Cavedon said.

The new algorithms will first be tested using historical data and then applied to current data in a trial setting. Ultimately, they will be integrated into Telstra Health’s Clinical and Care Management software.

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