ArticleHealth science reports2025
Geospatial Visualization of Dialysis Accessibility in Shiraz: A Nonanalytical Geographic Information System Approach.
Article in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: 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. Methods: 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. Results: 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. Conclusion: 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.
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Registered trials
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