A New Hybrid Model for Mapping Spatial Accessibility to Healthcare Services Using Machine Learning Methods

Ali Khosravi Kazazi · Yaser Rahmani · Raheleh Samouei · Hamidreza Rabiei‐Dastjerdi

24 citations0/0 files storedSustainability

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Urban Transport and Accessibility Urban Green Space and Health Healthcare Quality and Satisfaction

Abstract

The unequal distribution of healthcare services is the main obstacle to achieving health equity and sustainable development goals. Spatial accessibility to healthcare services is an area of interest for health planners and policymakers. In this study, we focus on the spatial accessibility to four different types of healthcare services, including hospitals, pharmacies, clinics, and medical laboratories at Isfahan’s census blocks level, in a multivariate study. Regarding the nature of spatial accessibility, machine learning unsupervised clustering methods are utilized to analyze the spatial accessibility in the city. Initially, the study area was grouped into five clusters using three unsupervised clustering methods: K-Means, agglomerative, and bisecting K-Means. Then, the intersection of the results of the methods is considered to be conclusive evidence. Finally, using the conclusive evidence, a supervised clustering method, KNN, was applied to generate the map of the spatial accessibility situation in the study area. The findings of this study show that 47%, 22%, and 31% of city blocks in the study area have rich, medium, and poor spatial accessibility, respectively. Additionally, according to the study results, the healthcare services development is structured in a linear pattern along a historical avenue, Chaharbagh. Although the scope of this study was limited in terms of the supply and demand rates, this work gives more information and spatial insights for researchers, planners, and policymakers aiming to improve accessibility to healthcare and sustainable urban development. As a recommendation for further research work, it is suggested that other influencing factors, such as the demand and supply rates, should be integrated into the method.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 24 citations exist upstream.

References

2013Patient-centred access to health care: conceptualising access at the interface of health systems and populations 2003Measures of Spatial Accessibility to Health Care in a GIS Environment: Synthesis and a Case Study in the Chicago Region 2009An enhanced two-step floating catchment area (E2SFCA) method for measuring spatial accessibility to primary care physicians 2000Spatial Decompositions, Modeling and Mapping Service Regions to Predict Access to Social Programs 2012Spatial accessibility of primary health care utilising the two step floating catchment area method: an assessment of recent improvements 2013Spatial accessibility in suboptimally configured health care systems: A modified two-step floating catchment area (M2SFCA) metric 2019A comparative analysis of accessibility measures by the two-step floating catchment area (2SFCA) method 2014Recent advances and applications in accessibility modelling

Cited by

2024An examination and analysis of the clustering of healthcare centers and their spatial accessibility in Tehran metropolis: Insights from Google POI data 2024Reducing urban energy consumption and carbon emissions: a novel GIS-based model for sustainable spatial accessibility to local services and resources 2023A School of Thought on VGI Challenges: A Literature Review

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.