Health science reports · 2025
Geospatial Visualization of Dialysis Accessibility in Shiraz: A Nonanalytical Geographic Information System Approach.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
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Ghahramani Peyman, Kiani Behzad, Norouzkhani Narges, Khoshkangin Atefeh, Kheirdoust Azam, Mazaheri Habibi Mohammad Reza
Аннотация
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.
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.