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An Introduction to Software Tools, Data, and Services for Geospatial Analysis of Stroke Services


Background: There is interest in the use of geospatial data for development of acute stroke services given the importance of timely access to acute reperfusion therapy. This paper aims to introduce clinicians and citizen scientists to the possibilities offered by open source software (R and Python) for analyzing geospatial data. It is hoped that this introduction would stimulate interest in the field as well as generate ideas for improving stroke services. Method: Instructions on installation of libraries for R and Python, source code, and links to census data are provided in a notebook format to enhance experience with running this software. This code illustrates different aspects of using geospatial analysis: 1) creation of choropleth (thematic) map which depicts estimate of stroke cases per post code; 2) use of map to help define service regions for rehabilitation after stroke. Results: choropleth map showing estimate of stroke per post codes and service boundary map for rehabilitation after stroke. Conclusions: the examples in this article illustrate the use of a range of components that underpin geospatial analysis. By providing an accessible introduction to these areas, clinicians and researchers can write code to answer clinically relevant questions on topics such as service delivery and service demand.

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