Conference presentation for Australian Association of Gerontology 2020.

1. Visualising
the
Dementias in
Australia:
A Data Driven
Model
• Authors:
• Hamish Robertson
• Nick Nicholas
• University of Technology Sydney

2. Contents
• The dementias in Australia
• Continuing data problems
• Model
• Visualisation
• Data integration
• Applications
• Conclusion

3. The Dementias in Australia
• Mid-tier OECD population ageing, peaking in approximately 2050
• Dementia a broad rubric with many single conditions and growing
overlap e.g. mixed dementia category
• Dementia landscape is dynamic, hence modelling flexibility is useful,
worthwhile and increasingly viable
• Interaction between funding, policy, population and things like Royal
Commissions make managing change more important in modelling
and response activities
• Expansion and extensibility therefore are key considerations

4. Continuing
Data
Problems

5. Model
• Census data at SA2 level
• AIHW population projections to 2032 at SA2 level
• Dementia prevalence estimates 2017-2032
• Sub-type prevalence (AD, Vascular, Other) – base data and slider
option
• Severity estimates included to allow for more complex needs
identification and planning
• Frailty measures – base data and slider option being added
• Per capita formal cost of care estimates in development

6. Visualisation

9. Dementia Time Series Data

10. Time Series for Severity Estimates

11. Data Structure

12. Data Integration
• Many different data sets included within the one model
• Connected at the geographic level so geography provides the
integrative dimension linking all data types
• Readily extensible and expandable – new and additional data sets
from different parts of the ‘system’ can be integrated within the same
modelling environment
• Scalable – from national level, state and territory level, down to small
area (SA2 here but S1, meshblock etc. all viable)

13. Applications
• Consistent data modelling and scenario development across service
providers e.g. analyse against service provider types, model emerging
demand, identify areas of higher need versus lower (quantitively)
• Easily adjustable based on new or additional data (e.g. new
prevalence data from research and/or administrative data sets)
• Financial modelling extensibility – per capita cost, area-based costing
or system and sub-system costings (e.g. all of acute care or
components of acute care, all of residential care or networks of
providers or individual providers)
• Add in a severity measure to connect demand, cost and resourcing
sensitivity

14. Conclusion
• More and better data will expand and improve the detail of the
dementia ‘picture’ in Australia e.g. below state and territory level
• Dynamic nature of the dementias (mixed dementia etc.) and their
interaction with a shifting demographic profile e.g. differential growth
in older cohorts
• Data viz and spatial applications can assist multiple providers in
tailoring responses, conserving resources and improving outcomes
• The same approaches can be used to support and develop
community understanding and participation in building an age-
friendly society e.g. volunteers and carers