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Where, when, and how to close dialysis access gaps: incorporation of geographic information system into data-driven planning: A commentary
Journal article   Open access   Peer reviewed

Where, when, and how to close dialysis access gaps: incorporation of geographic information system into data-driven planning: A commentary

Gina S. Lovasi and Richard Remigio
Israel journal of health policy research, v 14(1), 69
26 Nov 2025
DOI: https://doi.org/10.1186/s13584-025-00724-1
PMID: 41291911
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1186/s13584-025-00724-1View
Published, Version of Record (VoR) Open

Abstract

Comment Health Administration Health Policy Health Promotion and Disease Prevention Health Services Research Medicine Medicine & Public Health Public Health
Barriers to timely and consistent dialysis care include characteristics at the patient, facility, and area levels. An article by Schroeder and colleagues uses national data spanning several thousand patients served by 67 dialysis centers across 6 districts of Israel, illustrating an approach that could be extended to other health care facilities within and beyond this national setting. The methods and findings demonstrate challenges and utility of incorporating geographic information systems (GIS) into data-driven planning to alleviate capacity constraints. Accurate estimation of distance and travel time from home to dialysis center rely on geocoding methods, road networks, time-varying transit and traffic congestion, and analytic treatment of statistical outliers. Analyses of where capacity gaps exist have potential to guide opening, relocation, or closure of health care facilities. Attention to identities and comorbidities within area-level resident populations can be used alongside data on whether dialysis centers are oversubscribed to inform scheduling. An example discussed was feasibility of offering a third Friday shift that extends into evening hours, which depends on religious observance patterns of patients and staff. Although not available in data used by Schroeder and colleagues, patient-level indication for supine treatment due to functional limitations could inform selection of equipment within dialysis centers, improving care quality. Our commentary highlights the potential of integrating GIS data to characterize where, when, and how dialysis care is available, which can likewise be used across other health care sites to ensure timely response to health emergencies and to accommodate the increasing chronic care needs of an aging population. Internationally, data needs and opportunities to improve population outcomes and equity will depend on the current state of care availability and on crises, whether collective (conflict, inclement weather) or personal (bereavement or other loss of social support, disruption of commuting modes).

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