Mapping health inequalities in cardiovascular disease using mapping software at the Faculty of Medical and Health Sciences, Auckland
InstantAtlas in action
InstantAtlas is being used by Dr Dan Exeter at the Faculty of Medical and Health Sciences at the University of Auckland to map health inequalities. Dan is a senior lecturer in the School of Population Health and his current research focuses on the development of deprivation indices using routine administrative data sources. He explains how InstantAtlas is helping him to create interactive online atlases of cardiovascular disease treatment and outcomes.
What is your project?
I have a background in quantitative health geography and my current research is focussed on geographical variations in health outcomes. I tend to use Geographical Information Systems (GIS) and combine this with the secondary analysis of large datasets such as population censuses and registers of public hospitalisations, pharmaceutical dispensing, immunisation coverage and/or mortality. I am particularly interested health disparities and links with socio-economic deprivation or ethnicity.
The Auckland Region Vascular Atlas project integrates methods from epidemiology and geography to investigate and visualise the provision of vascular disease services (community laboratory tests, pharmaceutical management and hospital procedures) for the Auckland Region. The distribution of services will be illustrated across the region using socio-demographic and spatial factors.
How did you come across InstantAtlas?
I saw how InstantAtlas was used by the Centre for Public Health on its website CPHROnline and realised that it could be used to create a visual atlas of cardiovascular disease treatment and outcomes.
How did you get started?
Our research team has been collecting routine data sets for patients with heart disease. This includes information from GP registers, prescription data and secondary care (hospital) data. Since each patient has a unique identifier, it is possible to link this information with socio-economic data and identify inequalities in health outcomes. Learning how to use InstantAtlas was straightforward and we were able to map large amounts of data, roughly 35GB.
What sort of feedback have you had on the interactive maps?
We haven't published the maps widely yet, but the feedback we've had from colleagues has been fantastic. The ability to interact with the data so you can look at different age groups has been welcomed because it gives you a good idea of what is happing within each community.
How are you going to develop the interactive maps?
At the moment we are providing health planners with a real snapshot of the pattern of variation. I would like to take this further so we can start to see variation between health boards, healthcare regions and even analysis at electoral ward level - which is far less common here than in other countries.
What are the benefits of using this mapping software?
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