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Chronic kidney disease is growing and the current estimated global prevalence exceeds 13%. As the use of haemodialysis machines for patients with end stage renal disease increases survival considerably, it is critical to plan correctly for the allocation of these machines. This study aimed to develop a geographical information systems (GIS)-based approach to predict the need for this service in the northeastern region of Iran taking into account where patients live and where haemodialysis is the most needed and identifying areas with poor access to haemodialysis centres. Patients were interviewed to obtain self-reported actual travel time and the inverse distance-weighting algorithm was used to determine access in each area. The prediction is based on the domestic growth rate for haemodialysis services and the estimated active hours of machine use for the next five years. We estimate that six new haemodialysis machines are required in northeastern Iran at the present time with 50 machines required over the next five years. Ashkhane City was identified to have the least access to haemodialysis centres in the study area. Our GIS-based model can be used to investigate not only the need for new haemodialysis machines but also to examine geographic disparities in the allocation of haemodialysis centres and to identify areas most in need of this service. It is important that policymakers consider both spatial and non-spatial dimensions of access to enable better allocation of haemodialysis services ensuring they are targeted to reach those in need.
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