New ‘what if’ tool sheds light on future of cardiovascular disease

Researchers at the Sax Institute are using computer simulation to peer into the future of cardiovascular disease (CVD) and forecast the best ways to prevent and treat Australia’s leading cause of death.

The computer model, developed by the Sax Institute’s Decision Analytics team, draws on knowledge from clinicians, health economists, policy makers and researchers to form one of Australia’s most comprehensive mapping tools for CVD. It’s also a low-risk way to test policy scenarios before they’re implemented in the real world.

Currently, CVD affects one in five Australian adults, and is the leading cause of death for Australians. If that’s not bad enough, the Sax Institute’s model predicts the number of CVD-related hospitalisations and deaths are set to rise, with an estimated 80% increase over the next 20 years.

The numbers are dire, but with the help of dynamic modelling, researchers can now ask ‘what if’ questions about the effect of long-term treatment and prevention strategies. Critically, they found that more timely care – such as immediate use of defibrillator and reducing the arrival time at hospitals following a heart attack or stroke – could reduce deaths by up to 8.7%. However, doing so without improving cardiovascular health and preventing CVD in the first place, results in higher hospitalisations later.

So what are the options for prevention? Researchers discovered that building a supportive environment that helps people maintain better heart health – such as by encouraging food companies to reduce levels of salt in processed foods, facilitating the creation of walkable neighbourhoods and keeping up efforts to discourage tobacco smoking – could prevent both hospitalisations and deaths by up to 4%. This would translate to billions of dollars in economic benefits over the next 20 years thanks to a healthier and more productive population.

Project lead Ms Cindy Peng, Senior Research Officer in the Sax Institute’s Decision Analytics team, says these findings force us to expand our perspective on CVD. “This is a high-level strategic decision tool that has helped us look at the dynamics in the CVD space,” she says. “We can see there is an increasing public health burden here, but by experimenting with different treatment and prevention scenarios in this safe virtual environment, we can also explore smart, cost-effective solutions.”


 Dynamic modelling has identified the most effective strategies for reducing CVD-related hospitalisations and deaths.
Dynamic modelling has identified the most effective strategies for reducing CVD-related hospitalisations and deaths.

Read the full Evidence Brief here.


The Sax Institute’s Decision Analytics team harnesses the latest technologies and methods to develop adaptable decision support tools that forecast the impact of alternative decision options before they are implemented in the real world.

We work in partnership with government departments, policy agencies and program planners in health and social sectors, applying computer simulation and other technologies to provide decision makers with a low-risk way of understanding which combinations of interventions are likely to be the most effective over time. Find out more about the Sax Institute’s Decision Analytics here.