Objectives: To explore travel burden in patients with multimorbidity and analyze patients with high travel burden, to stimulate actions towards adequate access and remote care coordination for these patients.
Design: A retrospective, cross-sectional, explorative proof of concept study. Setting and participants: Electronic health record data of all patients who visited our academic hospital in were used. Baseline variables were analyzed using univariate statistics. Patients were stratified into two groups by the median travel burden.
The contribution of travel time dichotomized and the number of outpatient clinic visits days dichotomized to the travel burden was examined with binary logistic regression by adding these variables consecutively to a crude model with age, sex and number of diagnosis.
National maps exploring the geographic variation of multimorbidity and travel burden were built. Results: A total of 14 patients were included Patients travelled an average of 0. Care consumption variables, such as higher number of diagnosis and treating specialties in the outpatient clinic were more frequent in patients with higher travel burden.
Conclusions and implications: The geographic representation of patients with multimorbidity and their travel burden varied but coincided locally with lower SES and older age in the general population. Future studies should aim on identifying patients with high travel burden and low SES, creating opportunity for adequate remote care coordination.
