Transportation vulnerability as a barrier to service utilization for HIV-positive individuals

Abstract

Research suggests that transportation vulnerability can negatively impact adherence to HIV-related medical treatment. Moreover, transportation can be a barrier to accessing ancillary services which can increase positive health outcomes for HIV-positive individuals. This study examines transportation vulnerability and its impact on HIV-related health and ancillary service utilization in the Mid-South Region. Focus groups and interviews were conducted with service providers and HIV-positive individuals, and survey data were collected from HIV-positive individuals (N=309) using the five A's of access to frame transportation vulnerability: availability, accessibility, accommodation, affordability, and acceptability. Study results indicate that transportation vulnerability can present significant barriers to service utilization for HIV-positive individuals, including insufficient transportation infrastructure, incompatible fit between transportation and health systems, and insensitivity to privacy issues. One consequence of transportation vulnerability is reliance upon weaving together multiple modes of transport to access care and ancillary services, creating additional barriers to service utilization and medical adherence. The research team recommends more investment in public transit systems, expanded services, and innovative approaches to solving procedural problems.

Keywords:

• transportation
• medical adherence
• service utilization
• HIV/AIDS

Acknowledgements

This research was supported in part by Ryan White Part A funds, administered by the United Way of the Mid-South, and in collaboration with the Mid-South Coalition on HIV/AIDS and the Ryan White Part A Planning Council. The authors acknowledge the assistance of the Ryan White Program Office, Part A service providers; Planning Council members; and graduate students Meagan Brown, Nicole Gottier, Dustin James, Ace Madjlesi, Ginger McKay, and Janelle Williams for their assistance in data collection, analysis, and interpretation.

Notes

1. Differences by race, gender, education, income, and urbanicity were tested and only reported when significant.