ArticleBritish journal of clinical pharmacology2021
Using pharmacy dispensing data to predict falls in older individuals.
Article in British journal of clinical pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Dynamic changes in medication burden leading to fall and hospital readmissions in older adults: Toward a strategy for improving risk and managing costs.Journal of managed care & specialty pharmacy · 2025Review
- Development of the ADFICE_IT Models for Predicting Falls and Recurrent Falls in Community-Dwelling Older Adults: Pooled Analyses of European Cohorts With Special Attention to Medication.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022Article
- Using pharmacy dispensing data to predict falls in older individuals.British journal of clinical pharmacology · 2021Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
aimsAssociations between individual medication use and falling in older individuals are well-documented. However, a comprehensive risk score that takes into account overall medication use and that can be used in daily pharmacy practice is lacking. We, therefore, aimed to determine whether pharmacy dispensing records can be used to predict falls.
methodsA retrospective cohort study was conducted using pharmacy dispensing data and self-reported falls among 3454 Dutch individuals aged ≥65 years. Two different methods were used to classify medication exposure for each person: the drug burden index (DBI) for cumulative anticholinergic and sedative medication exposure as well as exposure to fall risk-increasing drugs (FRIDs). Multinomial regression analyses, adjusted for age and sex, were conducted to investigate the association between medication exposure and falling classified as nonfalling, single falling and recurrent falling. The predictive performances of the DBI and FRIDs exposure were estimated by the polytomous discrimination index (PDI).
resultsThere were 521 single fallers (15%) and 485 recurrent fallers (14%). We found significant associations between a DBI ≥1 and single falling (adjusted odds ratio: 1.30 [95% confidence interval {CI}: 1.02-1.66]) and recurrent falling (adjusted odds ratio: 1.60 [95%CI: 1.25-2.04]). The PDI of the DBI model was 0.41 (95%CI: 0.39-0.42) and the PDI of the FRIDs model was 0.45 (95%CI: 0.43-0.47), indicating poor discrimination between fallers and nonfallers.
conclusionThe study shows significant associations between medication use and falling. However, the medication-based models were insufficient and other factors should be included to develop a risk score for pharmacy practice.
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Registered trials
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