# Geospatial Visualization of Dialysis Accessibility in Shiraz: A Nonanalytical Geographic Information System Approach

## TL;DR

This study uses GIS to map dialysis accessibility in Shiraz, revealing how geography and socioeconomic factors affect patient access to treatment.

## Contribution

The paper introduces a nonanalytical GIS approach to visualize dialysis accessibility and identify underserved areas in Shiraz.

## Key findings

- Spatial disparities in dialysis accessibility were found, with disadvantaged neighborhoods facing longer travel times and higher costs.
- GIS modeling identified priority zones for expanding dialysis services to improve equitable access.
- Socioeconomic factors were shown to concentrate patients in areas with poor access to dialysis facilities.

## Abstract

Chronic kidney disease (CKD) poses a substantial global health challenge, contributing to increased morbidity and mortality, diminished quality of life, and escalating healthcare expenditures. Despite advancements in nephrology and dialysis technologies, disparities in hemodialysis (HD) accessibility remain prevalent, leading to suboptimal patient outcomes and increased healthcare burdens. Geographic Information Systems (GIS) facilitate the spatial analysis of healthcare service distribution, identifying inequities in access. This study employs GIS to evaluate the spatial distribution of dialysis facilities in Shiraz, highlight underserved areas, and assess geographic barriers impacting patient access.

A GIS‐based spatial analysis was performed utilizing deidentified patient demographics, dialysis facility locations, transportation network data, and urban zoning characteristics to assess accessibility and service distribution. Sophisticated geospatial methodologies, including Network Analysis and Kernel Density Estimation (KDE), were employed to model travel time variations and evaluate spatial equity in‐service distribution. The study adhered to SAMPL and CONSORT reporting guidelines.

Among 605 patients (mean age: 60.9 ± 15.4 years; 64.6% male), substantial spatial disparities in dialysis service accessibility were identified, with notable variations in travel burden and facility distribution. Patients from socioeconomically disadvantaged neighborhoods experienced prolonged travel times and increased transportation expenses, further intensifying healthcare access disparities. GIS‐based spatial modeling identified priority zones for service expansion, proposing targeted interventions to optimize resource allocation.

Socioeconomic inequities substantially impact dialysis accessibility, concentrating patients in cost‐effective residential areas with heightened travel burdens and delayed treatment initiation. GIS‐driven spatial planning provides a data‐driven framework for equitable dialysis resource allocation, facilitating evidence‐based healthcare policy decisions.