Mapping the Dementias in NSW: A GIScience Approach
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Transcript Mapping the Dementias in NSW: A GIScience Approach
Mapping the Dementias in NSW:
A GIScience Approach
Authors: H. Robertson, GA (Tony) Broe and N. Nicholas
Ageing Research Centre
Prince of Wales Hospital
Email: [email protected]
Ph: 02-93824594
Contents
• The dementias and issues of scale
• Practical implications for monitoring and
service delivery
• Using GI Science and GIS in particular
• Adding value to past and present clinical
research
• Applying new methods to existing data
Objectives in Using GIScience
• Translating clinical research to population
outcomes and
• Sharpening the focus of questions and research for
the future
• Adding value to clinical data for researchers,
planners and the community
• Linking multiple data sets and research outcomes
to look at problems afresh
• Empowering communities and communities of
interest to plan and advocate more successfully
GIS Applications
•
•
•
•
•
•
Infectious disease mapping eg. Snow
Public health mapping eg. 9/11 toxic plume
Health service access – spatial access
Theorising disease aetiology eg. MND/Sabel
Investigating gene-environment interactions
Poorly utilised in ageing research - Hirschorn
GIS and MND/ALS
Actual and Projected Population 85+
2001-2050
Source: The Demographer’s Workshop
3000000
2500000
2000000
1500000
1000000
500000
0
Jun.2002 Jun.2007 Jun.2012 Jun.2017 Jun.2022 Jun.2027 Jun.2032 Jun.2037 Jun.2042 Jun.2047
Jun
.20
Jun 02
.20
Jun 05
.20
Jun 08
.20
Jun 11
.20
Jun 14
.20
Jun 17
.20
Jun 20
.20
Jun 23
.20
Jun 26
.20
Jun 29
.20
Jun 32
.20
Jun 35
.20
Jun 38
.2
Jun 041
.20
Jun 44
.20
Jun 47
.20
50
Australia’s 85+
3000000
2500000
2000000
1500000
1000000
500000
0
Projected Milestones for
the “Old Old”
•
•
•
•
•
2014
2031
2037
2043
2049
0.5 million people 85+
1 million
1.5 million
2.0 million
2.5 million
Some Reasons to Map Dementia
• Variations occur across space in terms of
population and infrastructure
• Importance of location for services eg.
MOW
• Importance for modelling patient and carer
needs eg. respite care demand
• Add a spatial dimension to the issue eg.
remoteness/distance etc
• Localise the issues faced in different places
Formal Service Utilisation in SOPS 1
Day Care Attended
Financial Support
Home Help
Home Maintenance
Home Modifications
Home Nursing
Laundry Service
Lawn Mowing/Gardening
Legal Management
Meals on Wheels
Medical Supply Service
Optical Service)
Other Services (check)
Podiatrist/chiropodist
Shopping Service
Transport Service
0
5
10
15
20
25
30
35
40
45
50
WARNING
Most data used in the following
maps and tables are provisional
results only and we suggest you
make contact with the authors prior
to any use of these maps and tables.
Informal Services Utilised SOPS 1 (Selected)
Private transport
Shopping/errands
Meal preparation
Heavy housework
Light housework
Laundry
Gardening/lawn mowing
Home repairs
Financial management
0
5
10
15
20
25
30
Disability Aids Owned SOPS 1
Brace
Crutches
Dentures
Glasses
Hearing aid
Nebuliser
Oxygen
Ramps
Shower or bath seat
Shower rails
Stair rails
Toilet rail
Toilet seat
Walking frame
Walking stick
Wheelchair
Other Aids
0
10
20
30
40
50
60
70
80
90
100
Rough Dementia Estimate and Projections
2000000.00
1800000.00
1600000.00
1400000.00
1200000.00
1000000.00
Legend
Total 75+
Dementia Estimate
800000.00
600000.00
400000.00
200000.00
0.00
1947 1954 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011 2016 2021
Current 85+ in Metropolitan Sydney
Eastern Suburbs, Sydney
Sydney Metro Model
Aged 85+ projected from 2001 out to 2031
using SLAs and SOPS Data
New South Wales Model
Conclusion
• GIS lends itself to better understanding of
and planning for long term health issues
• Mapping lends flexibility to planning eg.
model at various scales from nation down to
neighbourhood
• Simplifies/clarifies the numbers approach
for a broader audience
Where to Next?
• Plenty left to do to ensure model is relevant and
accurate for users
• Complete conversion and analysis of all five
waves of data (have Wave 1)
• Finalise our model of progression of
neurodegenerative diseases over the ageing
process
• Add service demands and met/unmet needs to
model
• Make internet friendly for a wider audience