BACKGROUND AND PURPOSE: Vital to maintaining an efficient delivery of services is an understanding of patient travel patterns during an acute ischemic stroke. Socioeconomic status may influence access to stroke care, including transportation and admission to different facility types. METHODS: We analyzed all acute ischemic stroke admissions between 2003 and 2007 through the Discharge Abstract Database, a national database containing patient-level sociodemographic, diagnostic, procedural, and administrative information across Canada. Socioeconomic status was defined in neighborhood quintiles according to Statistics Canada. Distances between patients and facilities were derived from postal codes. A principal diagnosis of ischemic stroke was identified using the International Classification of Diseases (versions 9 and 10). Analysis of variance and regression analyses were performed with adjustment for demographic characteristics. RESULTS: Admitted to acute care institutions were 243 410 patients with ischemic stroke. Mean patient age was 72.8 and 49.5% were male; 44.2% traveled beyond their closest center, amounting to an average 7.2 km additional distance traveled. Socioeconomic status quintile had minimal effect on travel patterns, with the lowest socioeconomic status accessing the closest center most frequently (odds ratio, 1.19; 95% confidence interval [CI], 1.13-1.16). Increased utilization of the closest hospital occurred with academic (odds ratio, 6.90; 95% CI, 6.69-7.11) or high-volume (odds ratio, 1.93; 95% CI, 1.88-1.98) facilities. Older patients (β=0.28; 95% CI, 0.27-0.28), expert destination facility (β=0.13; 95% CI, 0.12-0.14), and ambulance use increased travel beyond the closest center. CONCLUSIONS: Patients tend to choose care facilities based on hospital expertise; investment promoting improved regional facilities may be of greatest benefit to patients. Socioeconomic status has little bearing on travel patterns associated with stroke in Canada. These findings may assist in allocating funding to centers and improving patient care.
BACKGROUND AND PURPOSE: Vital to maintaining an efficient delivery of services is an understanding of patient travel patterns during an acute ischemic stroke. Socioeconomic status may influence access to stroke care, including transportation and admission to different facility types. METHODS: We analyzed all acute ischemic stroke admissions between 2003 and 2007 through the Discharge Abstract Database, a national database containing patient-level sociodemographic, diagnostic, procedural, and administrative information across Canada. Socioeconomic status was defined in neighborhood quintiles according to Statistics Canada. Distances between patients and facilities were derived from postal codes. A principal diagnosis of ischemic stroke was identified using the International Classification of Diseases (versions 9 and 10). Analysis of variance and regression analyses were performed with adjustment for demographic characteristics. RESULTS: Admitted to acute care institutions were 243 410 patients with ischemic stroke. Mean patient age was 72.8 and 49.5% were male; 44.2% traveled beyond their closest center, amounting to an average 7.2 km additional distance traveled. Socioeconomic status quintile had minimal effect on travel patterns, with the lowest socioeconomic status accessing the closest center most frequently (odds ratio, 1.19; 95% confidence interval [CI], 1.13-1.16). Increased utilization of the closest hospital occurred with academic (odds ratio, 6.90; 95% CI, 6.69-7.11) or high-volume (odds ratio, 1.93; 95% CI, 1.88-1.98) facilities. Older patients (β=0.28; 95% CI, 0.27-0.28), expert destination facility (β=0.13; 95% CI, 0.12-0.14), and ambulance use increased travel beyond the closest center. CONCLUSIONS:Patients tend to choose care facilities based on hospital expertise; investment promoting improved regional facilities may be of greatest benefit to patients. Socioeconomic status has little bearing on travel patterns associated with stroke in Canada. These findings may assist in allocating funding to centers and improving patient care.
Authors: Michael T Mullen; Douglas J Wiebe; Ariel Bowman; Catherine S Wolff; Karen C Albright; Jason Roy; Laura J Balcer; Charles C Branas; Brendan G Carr Journal: Stroke Date: 2014-10-09 Impact factor: 7.914