Polypharmacy is common among older adults with multiple chronic comorbidities and has been associated with adverse outcomes. This study aimed to investigate the clarify an efficient approach to eliminate polypharmacy. The primary endpoint was a multivariate logistic regression analysis that was performed to compare the effects of each factor in the polypharmacy and non-polypharmacy groups. The secondary endpoint was the relation between the period until the unscheduled visit within three months, measured by Cox proportional hazards model. In the multivariate analysis, the number of diseases (odds ratio = 1.01; P = 0.04) and more. Cox proportional hazards model was performed on the factors related to the unscheduled visit, and a significant difference was found in the relation with drug-drug interaction (hazard ratio = 1.51; P = 0.03) and more. The results of this study suggest the possibility of more efficiently leading to the correction of polypharmacy.
