Age-related risk factors for leftover drugs: a lifespan analysis in community pharmacies

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Introduction Medication adherence is a critical global challenge because suboptimal adherence reduces therapeutic efficacy and increases healthcare costs. While leftover drugs are vital indicators of potential adherence-related challenges, age-specific factors contributing to their occurrence, particularly across the lifespan, remain insufficiently understood. This study was aimed at clarifying age-stratified factors associated with leftover drugs using large-scale objective data from protocol-based pharmacotherapy management (PBPM) in community pharmacies. Methods This was a single-center, retrospective, observational cohort study of 36,340 outpatients. Objective reporting of data based on the PBPM in community pharmacies between 2016 and 2021 was analyzed. Multivariate logistic regression and predicted probability models were used to evaluate the interactions between age (decade-stratified) and four primary clinical factors: drug count, prescription duration, prescribing department count, and sex. Results The overall proportion of leftover drugs was 9.6% ( n = 3,472). In the overall population comparison, no significant differences were observed in terms of sex, but the patients in the leftover group were significantly older and had higher medication counts, longer prescription durations, and more prescribing departments. Multivariate analysis revealed significant interactions between age and each of the three primary prescription-related factors. The impact of clinical characteristics on the proportion of leftover drugs varied distinctly across life stages. Specifically, long-term prescription was the most potent risk factor for younger adults (20s–40s), whereas polypharmacy and multidepartment visits were the primary factors associated with leftover drugs for older patients. Predicted probability models indicated that having fewer than five prescribed medications was consistently associated with a lower likelihood of leftover drugs across all age groups. Conclusion This study highlights the influence of clinical characteristics on leftover drug shifting substantially with age. Consequently, effective management requires age-specific interventions centered on minimizing drug counts, with an emphasis on optimizing prescription duration in younger adults and promoting medication simplification and inter-institutional coordination in older adults.

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