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Retrospective cohort analysis identified 116 potentially preventable medication-related readmissions, highlighting prescribing issues and non-adherence.
BACKGROUND: Medication-related readmissions are significant burdens on patients and healthcare systems and are particularly prevalent among older adults. We aimed to identify potentially preventable medication-related readmissions and to describe their causes. METHODS: We conducted a retrospective cohort study of 500 randomly selected patients, aged 65 or older, discharged from the general internal medicine department of a university hospital in Switzerland between January 2022 and October 2023 and readmitted within 30 days. Two pharmacists independently screened their electronic health records and analysed whether their readmission was medication-related using the AT-HARM10 tool. We assessed preventability using judgements similar to the Schumock statements. In cases of disagreement between the two pharmacists, readmissions were also screened by a senior physician. We analysed the causes of potentially preventable medication-related readmissions. RESULTS: We identified 116 (23.2%) potentially preventable medication-related readmissions among the 500 readmissions analysed. The most common diagnoses associated with readmission were heart failure (21.6%), worsening pain (12.1%) and infection (12.1%). The most common causes of readmission were underprescribing (29.3%), Other prescribing problems such as suboptimal medication selection or dosage issues (28.4%), and non-adherence (12.9%). Diuretics, analgesics and antibiotics were the most frequently involved medications. CONCLUSIONS: Nearly one-quarter of 30-day readmissions involving older adults were medication-related and potentially preventable. The primary contributing factors were prescribing and non-adherence issues. The study highlighted common causes of such readmissions and underlines the need for further research to determine which interventions – such as medication reviews or improved care transitions – are most effective in addressing them. Identifying high-risk patients will also be essential to optimise the use of healthcare resources.
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Schönenberger et al. (2025) studied this question.
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