This presentation explores the development of predictive models for key aged care quality indicators including falls, pressure injuries, unplanned weight loss, and functional decline. Drawing on large-scale benchmarking data, the session examines how individual-level risk modelling can support earlier identification of residents at higher risk of adverse outcomes.

The talk will outline the current state of these models, how risk adjustment and individual-level prediction can inform care planning and monitoring, and how providers can use this information to prioritise preventative interventions. It will also discuss the limitations of current approaches and areas where improved data capture and modelling techniques could further strengthen predictive capability.