Too Many Medicines, Too Many Hospital Visits: Study Highlights Hidden Risk for Older Adults

Published in the Age and Ageing journal, this study is said to be the first to use data-driven techniques to show how complex drug regimens can quickly lead to short-term hospitalizations. With the number of older adults steadily increasing worldwide, the findings underscore the need to find ways to prevent avoidable hospital visits.

The study explains how older adults often get caught in “prescribing cascades,” where the side effects from one drug lead to additional prescriptions, creating a risky web of interactions. Using a large UK dataset, researchers built machine learning models that could predict the risk of emergency hospitalization within 30 days with about 75 percent accuracy. Key risk factors included a high Drug Burden Index (DBI) alongside lifestyle factors such as smoking and alcohol use, as well as issues like impaired mobility and a history of falls.

To tackle the problem, the researchers are working on developing a simple digital tool – potentially an app – that could help doctors and pharmacists identify at-risk patients. By answering questions about an individual’s current medications, chronic conditions, and lifestyle habits, clinicians could get a risk score that would help them adjust prescriptions and reduce hospital visits.

To learn more about the dangers of polypharmacy, see this article on our website.