Using smartphone user mobility to unveil actual travel time to healthcare: An example of mental health facilities

Abstract

Travel time to health facilities is one of the most important factors in evaluating health disparity. Previous extensive research has primarily leveraged the driving time to the nearest health facility to gauge travel time. However, such ideal travel time (ITT) may not accurately represent real individual travel time to health services and is often underestimated. This study aims to systematically understand such gaps by comparing ITT to actual travel time (ATT) derived from smartphone-based human mobility data and further identifying how various population groups across regions are most likely to be affected. This study takes mental health as an example and compares ATT with ITT to mental health facilities. Results indicate that ITT and ATT demonstrate significant disparities between urban and rural areas. ITT is consistently underestimated across the contiguous US. We compare travel times among diverse sociodemographic groups across eight geographical regions. The findings suggest that different age groups have similar travel times to mental health facilities. However, racial groups exhibit varied travel times. Hispanics have a larger percentage of the population experiencing longer ATT than ITT. We also employed spatial and non-spatial regression models, such as Ordinary Least Squares, Spatial Lag Model, and Spatial Error Model, to quantify the correlation between travel times and socioeconomic status. The results revealed that the proportion of older adults and high school dropouts positively correlates with travel times in most regions. Areas with more non-Hispanics show positive correlations with both travel times. Overall, this study reveals pronounced discrepancies between ITT and ATT, underscoring the importance of using smartphone-derived ATT to measure health accessibility.