Drug prescriptions increase in the 20 years before a patient’s dementia diagnosis, and prescribing patterns begin to hone in on particular medical conditions, a new study finds.
Investigators explored the association of polypharmacy and dementia. They found that the proportion of people taking three or more medications rose from 5.5% to 82% during the 20 years before a diagnosis. And within the five years of a diagnosis, people with dementia were likely to have taken more than three medications for non-dementia conditions.
As the pre-dementia period progresses, the types of drugs being prescribed change, the researchers also found. Initially, patients took drugs to treat a range of unrelated health conditions. But as the dementia diagnosis neared, the prescriptions were more likely to target specific conditions. Among patients closest to their diagnosis, for example, two-thirds were taking multiple medicines for respiratory or urinary infections, arthropathies and rheumatism, and cardiovascular disease. Another 22% took medicines for infections, arthropathies and rheumatism, cardio-metabolic disease and depression, reported Shangming Zhou, professor of e-Health at the University of Plymouth, in the United Kingdom.
Polypharmacy — when patients are prescribed more than one drug at a time — is known to increase potential drug harms, reduce the effectiveness of the drugs being prescribed and raise the possibility of hospital readmissions, the authors noted.
“Given the rise in dementia cases internationally, the need to understand how patterns of polypharmacy evolve before and after a dementia diagnosis are important for devising a safe treatment program for each patient,” Zhou said. “Our aim in this study was to help doctors find ways to prescribe multiple items of dementia medication safely and without reducing their effectiveness.”
The study was published in the journal Aging and Disease, under the title “Identifying Dynamic Patterns of Polypharmacy for Patients with Dementia from Primary Care Electronic Health Records: A Machine Learning Driven Longitudinal Study.”