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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 epidemiology of cardiovascular disease (CVD) in addition to 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). The distribution of services will be illustrated across the region using socio-demographic and spatial factors.
How did you come across InstantAtlas?
I’d seen how InstantAtlas was used to develop the NHS Atlas in the UK, but realised its potential to create a visual atlas of cardiovascular disease treatment and outcomes when we were commissioned by the Health Quality and Safety Commission to develop a national CVD atlas of variation.
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 and is over 35GB. 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 easily map the complex patterns hidden in large amounts of data.
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. We have also received very positive feedback from users regarding the PDF documents and YouTube clips we developed for the Auckland Region Vascular Atlas project to demonstrate the potential analyses that users can do using particular InstantAtlas templates.
How are you going to develop the interactive maps?
At the moment we are providing health planners and clinicians on the front line with a real snapshot of the pattern of variation. I would like to take this further so we can start to see variation between different district health boards and even analysis at electoral ward level – which is far less common here than in other countries. I am also keen to update our templates to the HTML versions to be more accessible for the end-users.
What are the benefits of using this mapping software?