A dashboard of predictive analytics and decision support: Improving the quality of aged care in Australia
A dashboard of predictive analytics and decision support to drive care quality and person-centred outcomes in aged care
This project is supported by an NHMRC Partnership Project grant with Anglicare (APP1170898).
Dr Amy Nguyen
Project description, aims and methods
The quality of aged care is a concern for all Australians. The ongoing Royal Commission into Aged Care Quality and Safety indicates a system facing significant challenges. Australians need better quality aged care and greater transparency; a system that responds to older peoples’ needs, identifies when they are at risk, and 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, and implementing real-time integrated data views, such as clinical dashboards, that provide overviews and alerts of areas of care requiring attention.
This is a five-year mixed-methods study that aims to:
- Co-develop an aged care dashboard which presents a visual overview of key indicators and embedded decision support to guide care decisions in residential and community-based aged care settings
- Identify and assess design and work process features which support the integration of dashboard use and decision support by multiple user groups (e.g. facility managers, staff and GPs, clients/families) into their everyday practice and lives
- Implement and evaluate the impact of the dashboard on evidence-based care decisions (e.g. medication use) and client outcomes (e.g. hospitalisations; client reported wellbeing) using a hybrid stepped-wedge cluster randomised controlled trial, and process and economic evaluations.
- National Health and Medical Research Council
- Sydney North Primary Health Network
- Northern Sydney Local Health District
- Deeble Institute for Health Policy Research
- Australian Healthcare and Hospitals Association
- Aged Care Quality and Safety Commission
Ludlow K, Westbrook J, Jorgensen M, Lind KE, Baysari MT, Gray LC, et al. Co-designing a dashboard of predictive analytics and decision support to drive care quality and client outcomes in aged care: a mixed-method study protocol. BMJ Open. 2021;11(8):e048657.
Lind K.E, Raban M.Z, Brett L, Jorgenson M.L, Georgiou G, Westbrook J.I (2020). Measuring the prevalence of 60 health conditions in older Australians in residential aged care with electronic health records: a retrospective dynamic cohort study. Population Health Metrics
News and Media
Predictive falls risk model for aged care
Dr Karla Seaman attended the Australian Association of Gerontology national conference this week and reported on the research currently being undertaken in the Aged Care Evaluation and Research (ACER) team working with aged care provider Anglicare to develop a predictive falls risk model for the aged care sector. This research was reported on in Australian Ageing Agenda, please see the full article here.
- Australian Ageing Agenda – September 4, 2019
Researchers developing data tool to identify at-risk residents
- Australian Institute of Health Innovation - August 29, 2019
New technology to unlock critical care information
Dr Amy Nguyen
Related stream of research
Centres Related to this Project
Content owner: Australian Institute of Health Innovation Last updated: 24 Nov 2022 11:49am