Optimizing Hospital Locations in Manchester: A GIS-Based Approach to Enhancing Healthcare Accessibility

dc.contributor.advisorMacdonald, Jacob
dc.contributor.authorAlqadi, Abdulaziz
dc.date.accessioned2024-12-15T09:16:10Z
dc.date.issued2024-08
dc.description.abstractThis study explores the optimisation of healthcare accessibility in Manchester through the strategic identification of locations for new hospitals using Geographic Information Systems (GIS). The research focuses on improving healthcare delivery across the city by analysing spatial disparities and using a strong spatial analysis framework. A Multi-criteria Decision Analysis (MCDA) approach was utilised, integrating key factors such as population density, transportation networks, and environmental constraints through Weighted Overlay techniques. The methodology used to establish spatial planning theories strategically placed healthcare facilities for improved accessibility and equitable service, incorporating theories such as Tobler’s First Law of Geography and central place theory. Key findings revealed high-demand areas in Manchester where new hospitals could significantly improve accessibility. The analysis emphasised the importance of carefully balancing various criteria to identify optimal sites that meet the needs of the city’s population, particularly in underserved areas. However, the study also identified several limitations. The reliance on 2021 population data may result in outdated assessments, given recent demographic changes. Furthermore, the analysis was limited in fully addressing healthcare disparities due to the exclusion of socio-economic and demographic factors like income levels and age distribution. Despite these limitations, the research offers valuable insights for policymakers and urban planners, providing a data-driven approach to healthcare facility planning that aims to improve access and equity in urban environments. The study concludes with recommendations for future research, including the incorporation of up-to-date population data and dynamic travel metrics to further refine site suitability models.
dc.format.extent44
dc.identifier.urihttps://hdl.handle.net/20.500.14154/74179
dc.language.isoen
dc.publisherUniversity of Sheffield
dc.subjectOptimizing Hospital Locations in Manchester: A GIS-Based Approach to Enhancing Healthcare Accessibility
dc.titleOptimizing Hospital Locations in Manchester: A GIS-Based Approach to Enhancing Healthcare Accessibility
dc.typeThesis
sdl.degree.departmentSchool of Geography and Planning, Faculty of Social Sciences
sdl.degree.disciplineGeographical Information Systems (GIS)
sdl.degree.grantorUniversity of Sheffield
sdl.degree.nameGeographical Information Systems

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
SACM-Dissertation.pdf
Size:
2.51 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.61 KB
Format:
Item-specific license agreed to upon submission
Description:

Copyright owned by the Saudi Digital Library (SDL) © 2025