Abstract
ABSTRACT
Background and Aims
Managing chronic kidney disease (CKD) care, particularly for patients requiring hemodialysis, presents significant challenges due to the uneven geographical distribution of cases, which complicates equitable resource allocation. Geographic Information Systems (GIS) can help identify spatial patterns and clusters, thereby supporting more efficient healthcare planning. This study aimed to investigate the spatial distribution of CKD cases requiring hemodialysis in West Azerbaijan Province, Iran.
Methods
This retrospective cross‐sectional descriptive study analyzed hemodialysis patient data collected during January–December 2021. Data from 1709 patients undergoing maintenance hemodialysis were obtained from all 19 governmental and 2 private hemodialysis centers operating at the provincial level. As all registered dialysis centers were included, the data set was considered representative of the provincial hemodialysis population. Records with incomplete key variables were excluded from analysis. Spatial prevalence patterns were assessed using spatial autocorrelation techniques, including the global Moran's
I
and local Moran's
I
indices, to identify nonrandom spatial distributions.
Results
The prevalence of hemodialysis in West Azerbaijan Province was 52.33 per 100,000 population. The global Moran's
I
index was 0.2706 (
Z
= 1.82,
p
I
analysis revealed no high–high clusters of hemodialysis prevalence. However, two significant low–low clusters (cold spots) were identified in the cities of Showt and Mako, while a high–low cluster was observed in Qarah Zia ol Din.
Conclusion
The findings highlight spatial inequalities in hemodialysis distribution and underscore the importance of geographically targeted resource allocation and public health strategies to improve CKD care delivery in the region.