Abstract
Objective: To identify demographic and medication-related predictors of unplanned hospitalisation and combine them into a hospitalisation risk score. Methods: 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). Results: 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. Conclusion: 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.
| Original language | English |
|---|---|
| Pages (from-to) | e436-e446 |
| Journal | Australasian Journal on Ageing |
| Volume | 39 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published or Issued - 1 Sept 2020 |
Keywords
- geriatrics
- hospitalisation
- pharmacy research
- polypharmacy
ASJC Scopus subject areas
- Community and Home Care
- Geriatrics and Gerontology