Predictive risk modelling – what does the future hold?

Ong K1

1Pride Living


As an industry, Aged Care has traditionally looked at risk mitigation through hindsight. But what if we could use foresight to better manage and minimise risk to our organisations and consumers?

With Serious Incident Response Scheme expected to commence in April 2021, providers need to ensure they look for innovative ways to take a proactive risk management approach. This includes best practice incident management such as Root Cause Analysis and analysing relevant data to identify preventable risks.

As an industry, we are yet to embrace the practice of predictive risk modelling to identify potential future risks and the associated benefits of utilising this information.

Pride Living is working on the concept of a Predictive Risk Management Model for providers, that can enable them to identify and manage preventable events.

In this session, we discuss:

–  Predictive risk modelling as a concept

–  How quantitative and qualitative data can be used to determine high impact high prevalence risks to consumers

–  How this form of modelling improves organisational governance and continuous improvement

The use of data analysis to develop predictive risk modelling enables providers to minimise risk within their organisation in a proactive way and to formulate an approach to risk that supports sustainability and viability.


With substantial experience in clinical practice within aged care as a Registered nurse, Katrina has worked to transform the way in which resident care is delivered in aged care services. She has a particular interest in supporting providers, large and small, to develop effective quality management systems as well as to ensure their systems respond to the new aged care quality standards.

As someone who has worked ‘hands on’ in the aged care industry, she offers an authentic understanding of the challenges providers face in delivering exceptional resident care in an ever more complex and consumer driven environment.

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