Improving the quality of aged care in Australia

Predictive analytics and decision support

This project involves a dashboard of predictive analytics and decision support to drive care quality and person-centred outcomes in aged care.

Project sponsors: The National Health and Medical Research Council through a partnership project grant with Anglicare (APP1170898)

About the project

The quality of aged care is a concern for all Australians. The Royal Commission into Aged Care Quality and Safety indicated a system facing significant challenges. Australians need better quality aged care and greater transparency and a system that:

• responds to older peoples’ needs
• identifies when they are at risk
• answers in effective and compassionate ways.

Our aged care sector is data rich but information poor. Although providers now collect vast amounts of electronic clinical and care management data, very little attention has been placed on the power of analytics to exploit this data to deliver actionable information about aged care quality. This includes:

• enabling preventive action by creating predictive risk models to provide earlier identification of older Australians who are at risk of adverse events
• implementing real-time integrated data views, such as clinical dashboards, that provide overviews and alerts of areas of care requiring attention.

Learn more about the MQ-Dash project.

Project goals

This is a five-year mixed-methods study that aims to:

1. co-develop an aged care dashboard which presents a visual overview of key indicators and embedded decision support to guide care decisions in residential aged care settings
2. identify and assess design and work process features which support the integration of dashboard use and decision support by multiple user groups (eg facility managers, staff and GPs, clients/families) into their everyday practice and lives
3. implement and evaluate the impact of the dashboard on evidence-based care decisions (eg medication use) and client outcomes (eg hospitalisations, client reported wellbeing) using a randomised controlled trial, and process and economic evaluations.

• Professor Andrew Georgiou
• Dr Guogui Huang
• Dr Amy Nguyen
• Associate Professor Magdalena Raban
• Maeve Ryan
• Dr Karla Seaman
• Dr Sandun Malpriya Silva
• Dr Nasir Wabe
• Professor Johanna Westbrook

• Restorative and wellbeing care – Deeble Institute
• Effectiveness of fall prevention interventions in residential aged care and community settings: An umbrella review – Health & Medicine Week via NewsRx.com
• Predictive falls risk model for aged care – Australian Ageing Agenda
• Falls risk: over 65% of at-risk people missed by routine assessment – Hospital and Healthcare
• Experts say falls tool is a safety risk – Aged Care Insite
• Peninsula Health Falls Risk Assessment Tool ‘poor’, says Macquarie University study – The Weekly Source
• Researchers developing data tool to identify at-risk residents – Australian Ageing Agenda

This project is in collaboration with:

• Aged Care Quality and Safety Commission
• Anglicare
• Australian Healthcare and Hospitals Association
• Deeble Institute for Health Policy Research
• Northern Sydney Local Health District
• Sydney North Primary Health Network.