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An Introduction to Software Tools, Data, and Services for Geospatial Analysis of Stroke Services
Mark Padgham1, Geoff Boeing2, David Cooley3
1Active Transport Futures, Muenster, Germany.
Frontiers in Neurology
|August 24, 2019
Summary
This study introduces using geospatial data and open-source software (R and Python) to map stroke cases and plan rehabilitation services. It provides code examples to help improve acute stroke care delivery and demand management.
Area of Science:
- Geographic Information Systems (GIS)
- Health Services Research
- Computational Health Informatics
Background:
- Timely access to acute reperfusion therapy is critical for acute stroke services.
- Geospatial data analysis offers potential for developing and optimizing these services.
- Open-source software (R and Python) provides accessible tools for such analyses.
Purpose of the Study:
- To introduce clinicians and citizen scientists to geospatial data analysis for stroke services.
- To demonstrate the application of R and Python in analyzing health-related geospatial data.
- To stimulate interest and generate ideas for improving stroke care delivery.
Main Methods:
- Providing installation instructions for R and Python libraries.
- Sharing source codes and census data links in a notebook format.
- Illustrating geospatial analysis techniques including choropleth mapping and service region definition.
Main Results:
- Generation of a choropleth map displaying estimated stroke cases by postcode.
- Creation of a service boundary map for post-stroke rehabilitation.
- Demonstration of practical applications of geospatial analysis in healthcare.
Conclusions:
- Geospatial analysis components are fundamental for understanding service delivery and demand.
- Accessible code examples empower clinicians and researchers to address clinically relevant questions.
- This approach can lead to data-driven improvements in stroke service planning and resource allocation.
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