Top Menu

Visualising service demand: who, where and when


With the latest modelling tools, aged care organisations can now start to map all the elements in the complicated service equation, write Hamish Robertson and Nick Nicholas.

Hamish Robertson

We know that Australia’s population is ageing. We know that neurodegenerative conditions increase with age and that multi-morbidities produce complex disability scenarios for many older people.

Gerontology and a range of health sciences tell us that older people and their capacity to manage these experiences vary enormously – from the very successful to those needing much greater support and monitoring.

Ageing is complex, complicated and diverse. Knowing who is coping well or poorly, where they are situated and when things are at a tipping point are, however, still beyond our current knowledge base.

Dementia assessments in primary care are still hit and miss, and ageing is still often seen as more of a problem than a result of societal ageing. Yet we are on pathway to becoming an aged society, one in which ageing is the norm and not an unusual or exceptional state.

Congruent with these needs to be a normalisation of the difficulties associated with ageing. The search for cures takes time and older people need effective interventions and care both now and as their numbers grow.

Nick Nicholas

As with disability, the dementias generally increase with age. We know in general terms who is mostly likely to begin exhibiting signs of a neurodegenerative condition. But where they are living, and when those first signs of progressive change begin, remain problematic elements of the equation.

One of the opportunities for addressing this current gap in our knowledge and understanding is through modelling and visualisation.

Here, we provide some ways forward for connecting what we know about the bigger picture of dementia prevalence with the local, community-based experiences of individuals, families and communities who have to cope with the outcomes of ageing.

Not every community has the same resources available to work with emerging need. Having a better-informed sense of how much need is likely to emerge, and the complexity of that need, contribute to the preparedness of local communities.

With contemporary mapping software (known as geographic information systems, or GIS, software), we can map, overlay and analyse information about the community, client groups, patient numbers, their severity and access to services including elements such as residential care beds (and type), dementia experts or certified practitioners, home care services.

This means we can map the whole, certainly most of, the mix in a complicated service equation. Then we can map the connections between those data, looking for concentrations of factors, such as a group of people in need of assistance, or identify emerging gaps in terms of service provision and corresponding resources.

This map shows the projected Alzheimer’s disease population by location across metropolitan Sydney in 2027

The map above shows the projected Alzheimer’s population by location across metropolitan Sydney 10 years from now. These are at the SA2 level, which is the smallest geographic scale at which the Australian Bureau of Statistics released population projection data for 2012 to 2027.

This provides a picture of how Alzheimer’s disease is likely to play out, assuming prevalence rates stay the same and no new variables affect these outcomes. We can also map ‘what-if’ scenarios as well, so if rates rise or fall their likely effects on service demand and supply can be investigated.

In a second map we could add pharmacy locations, for example, to the population-level data to show how the relationships between patient need and service availability. This helps anyone to explore the complexities of demand and supply sides of the aged care equation.

Creating dashboards

Our second approach involves data visualisation using dashboard technologies which are becoming increasingly popular in health care environments.

Data dashboards permit tracking of key performance data in a highly accessible format that can then be investigated by users if they notice something unusual or need to ask more detailed questions about a service problem.

Normally dashboards include the typical graphs and charts we are all familiar with, but also add maps and more innovative visual methods to enhance the value of that information. These approaches help make the data both analytical and informative.

This dashboard for northern Sydney shows different types of data using spatial and conventional methods in the same visual environment.

The dashboard image above was produced in Tableau and shows how different types of data can be visualised using spatial and conventional methods within the same visual environment.

The idea here is that users can explore their own situations and examine the data more broadly or narrowly depending on their needs. Organisational data such as costs, service locations and so on can also be added to the dashboard.

The advantage of this type of visual strategy is that data can be added or hidden as required and users can view data at the level of the whole state or zoom in on a group of SA2s or even a single SA2. Different geographies can also be added to fit organisational needs.

New approaches being developed

In our work, we have trialled a spatially integrated approach to population ageing that includes demography, epidemiology, disease severity, cost of formal care estimation and overlain that with major service provider types.

Originally produced for academic purposes, and focusing specifically on New South Wales, we are now adding 2016 Census data and recent service provider data to create a visually informative model of population ageing in Australia.

Population ageing is a challenge not because ageing is a tsunami but because it involves some new issues and the need to redirect a somewhat slow and complicated health and aged care system.

One the most sustainable ways forward is to see population ageing as a dynamic process which needs to be monitored and engaged with from the ground up. All of the aggregate data starts with individual older people living in their local situations.

This makes the ‘who’ and the ‘where’ of ageing intimately connected. People are embedded in places and not in databases or spreadsheets. The ‘when’ is harder to predict but much more is being done on this issue.

In addition, we can reasonably predict how many new people enter the dementia space each year, where they are likely to be and how severe their situations might be.

Of course, this is just one aspect of what can be mapped. You might want to include income data, social support information or access to transport, for example, to help improve service design and delivery.

We suggest that the future of ageing in Australia is not simply going to be a repeat of past experiences. That is, the same problems and patterns writ larger because of rising numbers.

Ageing itself is dynamic. Older people are a diversifying group and our understanding of ageing is growing rapidly. Change is guaranteed in the aged care industry and not just because of legislation or funding dynamics.

To respond effectively, we need to be better informed, tracking and managing information more effectively. This also means the big picture can’t be allowed to swamp local problems and responses.

We suggest that part of the solution will be to focus more closely on location as an important factor in the overall aged care equation.

Hamish Robertson is a research fellow at the Centre for Health Services Management, University of Technology Sydney, and Nick Nicholas is managing director of the Demographer’s Workshop in Sydney.



, ,

, , ,

No comments yet.

Leave a Reply