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Predictive Analysis for Better Aged-Care

Decision Support Software for Aged Care

AU$ 1 million partnership by RMIT University, an Australian-based provider of software for healthcare providers and funders, and the Digital Health Cooperative Research Centre will develop decision support software over the next two years.

As reported, the new software, which will be part of the provider’s residential aged care software suite, will analyse the clinical data of aged care residents for signs of deteriorating health.

Benefits of Decision Support Software

  • This could reduce emergency hospitalisations and allow more time for end of life plans.
  • Significantly, it will mark the introduction of clinical decision support software to predict deterioration into aged care.
  • The project had enormous potential to keep more aged care residents out of avoidable emergency care, as well as to provide earlier indications when residents are approaching end of life.
  • Emergency hospitalisations are stressful for aged care residents and their families. Add to that how it also places significant additional demand on hospitals.
  • Being able to treat residents earlier as well as avert the need for hospitalisation is extremely important.
  • Similarly, the earlier it is ascertained that an aged care resident is approaching end of life, the earlier time will be given to enact their advance care plan and honour their preferences.
  • Doing so is an important process for the aged care resident, their carers and families, and the aged care provider.
  • Importantly for aged care providers, better prediction of care needs is expected to enable more effective planning of staffing and clinical resources, which has been identified as a crucial factor by providers who use the aged care software.

Who are Involved?

  • The RMIT Professor of Computer Science explained that the research team will work with gerontologists and aged care staff to interpret historical data and develop new predictive analytics techniques.
  • They will also adapt 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.
  • The company has offered providers using its software to participate in the research, which has been met with a positive response from several providers.
  • As part of the Digital Health CRC’s Industry-PhD program, a PhD student will be embedded within the team.
  • Through this innovative PhD program, they are able to help build the digital health workforce Australia will need in the future.
  • The project is one of many being rolled out over the coming months through the Digital Health CRC, one of the world’s largest digital health R&D cooperatives.

Predictive Analysis Software

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 the company’s Clinical and Care Management software.

The project recognises how deeply the community cared about the effectiveness of advanced care plans.

While most people assume Advanced Care Directives will be enacted, the reality is that often this does not occur due to a lack of knowledge that the end of life is approaching.

Use of predictive analytics will enable more aged care providers, residents and their families to enact appropriate plans for end of life, according to the wishes of that person.


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