Michelle S Wong1, David T Grande, Nandita Mitra, Archana Radhakrishnan, Charles C Branas, Katelyn R Ward, Craig E Pollack. 1. *Department of Health Policy and Management, Johns Hopkins School of Public Health, Baltimore, MD †Division of General Internal Medicine, University of Pennsylvania ‡Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA §Division of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, MD ∥Department of Epidemiology, Columbia University, New York, NY ¶Division of General Internal Medicine, University of Pennsylvania, Philadelphia, PA #Division of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, MD.
Abstract
BACKGROUND: Geographic access-the travel burden required to reach medical care-is an important aspect of care. Studies, which typically rely on geographic information system (GIS) calculated travel times, have found some evidence of racial disparities in spatial access to care. However, the validity of these studies depends on the accuracy of travel times by patient race. OBJECTIVES: To determine if there are racial differences when comparing patient-reported and GIS-calculated travel times. RESEARCH DESIGN: Data came from the Philadelphia Area Prostate Cancer Access Study (P Access), a cohort study of men diagnosed with localized prostate cancer. We conducted cross-sectional analysis of 2136 men using multivariable linear mixed-effects models to examine the effect of race on differences in patient-reported and GIS-calculated travel times to urology and radiation oncology cancer providers. RESULTS: Patient-reported travel times were, on an average, longer than GIS-calculated times. For urology practices, median patient-reported travel times were 12.7 minutes longer than GIS-calculated travel times for blacks versus 7.2 minutes longer for whites. After adjusting for potential confounders, including socioeconomic status and car access, the difference was significantly greater for black patients than white patients (2.0 min; 95% confidence interval, 0.58-3.44). CONCLUSIONS: GIS-calculated travel time may underestimate access to care, especially for black patients. Future studies that use GIS-calculated travel times to examine racial disparities in spatial access to care might consider including patient-reported travel times and controlling for factors that might affect the accuracy of GIS-calculated travel times.
BACKGROUND: Geographic access-the travel burden required to reach medical care-is an important aspect of care. Studies, which typically rely on geographic information system (GIS) calculated travel times, have found some evidence of racial disparities in spatial access to care. However, the validity of these studies depends on the accuracy of travel times by patient race. OBJECTIVES: To determine if there are racial differences when comparing patient-reported and GIS-calculated travel times. RESEARCH DESIGN: Data came from the Philadelphia Area Prostate Cancer Access Study (P Access), a cohort study of men diagnosed with localized prostate cancer. We conducted cross-sectional analysis of 2136 men using multivariable linear mixed-effects models to examine the effect of race on differences in patient-reported and GIS-calculated travel times to urology and radiation oncology cancer providers. RESULTS:Patient-reported travel times were, on an average, longer than GIS-calculated times. For urology practices, median patient-reported travel times were 12.7 minutes longer than GIS-calculated travel times for blacks versus 7.2 minutes longer for whites. After adjusting for potential confounders, including socioeconomic status and car access, the difference was significantly greater for black patients than white patients (2.0 min; 95% confidence interval, 0.58-3.44). CONCLUSIONS: GIS-calculated travel time may underestimate access to care, especially for black patients. Future studies that use GIS-calculated travel times to examine racial disparities in spatial access to care might consider including patient-reported travel times and controlling for factors that might affect the accuracy of GIS-calculated travel times.
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