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

TL;DR

This commentary discusses how GIS can help plan dialysis care by identifying where, when, and how to address access gaps, improving care for aging populations.

Contribution

The paper introduces the integration of GIS into data-driven planning for dialysis access, emphasizing spatial and temporal factors.

Findings

GIS can identify capacity gaps in dialysis centers, guiding facility adjustments.

Travel time and distance estimates depend on geocoding and traffic data.

Scheduling shifts, like evening Friday sessions, must consider religious observance patterns.

Abstract

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).