Related Experiment Video
Updated: Mar 10, 2026

Training Persons with Spinal Cord Injury to Ambulate Using a Powered Exoskeleton
Published on: June 16, 2016
Geographic Variation in Outpatient Health Care Service Utilization After Spinal Cord Injury
Nathaniel Bell1, Tsion Kidanie2, Bo Cai2
1College of Nursing, University of South Carolina, Columbia, SC.
Objective:
To assess whether travel distances between patients and providers predict the frequency in which outpatient health care services are accessed after spinal cord injury (SCI).
Design:
A retrospective cohort study was carried out in South Carolina among employee health plan and Medicaid insurance recipients.
Setting:
Research center.
Participants:
Two years of outpatient claimant data were evaluated from patients (N=243) aged ≥18 years who were hospitalized between 2010 and 2012.
Interventions:
Travel distances were estimated by geocoding provider and patient address information onto street network files.
Main Outcome Measures:
Variation in service utilization use was assessed using negative binomial regression. Outpatient visits for physical medicine and rehabilitation, physician and specialty clinic, radiology, internal medicine, behavioral mental health, and "other" were evaluated.
Results:
Longer travel distances were statistically significant predictors of decreased physician/specialty clinic (relative risk [RR]=.87; 95% confidence interval [CI], .79-.96) and physiotherapy (RR=.57; 95% CI, .46-.71) utilization, with mixed findings for other providers. Secondary analyses in which differences in service use were analyzed using census-defined classifications of urban and rural status did not demonstrate any geographic pattern.
Conclusions:
There are significant geographic variations in the use of select outpatient services among SCI populations across the state that are related to longer travel distances. That these patterns were only visible when using travel distance models as opposed to census-based classifications of urban and rural status adds support to augmenting routine data collection and surveillance with spatial analytical models.

