To identify demographic and medication-related predictors of unplanned hospitalisation and combine them into a hospitalisation risk score.
Patients aged ≥65 years from an outpatient multimorbidity clinic were included. Hospitalisation predictors within a year of clinic discharge were identified using logistic regression. A risk score was developed. The area under the curve (AUC) was used to assess its predictive ability, compared to that of the medicines count (definition of polypharmacy).
A total of 598 patients were included (median age of 80.0 years). 58.0% (n = 347) were hospitalised within a year of clinic discharge. The AUC for the risk score incorporating age, medicines count, heart failure (HF), atherosclerotic disease and systemic steroids was 0.67 [95% CI 0.62-0.71], compared to 0.62 [95% CI 0.58-0.67] for the medicines count.
A hospitalisation risk score incorporating demographics, medicines, namely steroids, and diseases such as HF had increased predictive ability compared to the medicines count, providing guidance for developing future polypharmacy tools.

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