Prevalence of Potentially Inappropriate Medication Use in Older Drivers: AAA LongROAD Study
archive: archived pipeline: cataloged verified
Get this paper ↗ (full text — opens at the source; we link to it, we don't host it)
Summary
This study examines the prevalence and correlates of potentially inappropriate medication (PIM) use among older drivers, addressing the significant traffic safety risks associated with medications that impair driving ability. Motivated by the high morbidity, mortality, and crash risk linked to PIMs in older adults, the research utilized baseline data from the Longitudinal Research on Aging Drivers (LongROAD) study. The authors aimed to identify specific demographic and clinical factors associated with PIM use to inform interventions for improving traffic safety. The analysis drew from a multisite prospective cohort of 2,990 active drivers aged 65–79 recruited from primary care clinics in five U.S. locations. Medication data were collected via a "brown-bag" review, where participants brought all prescribed and over-the-counter medications. These medications were coded using the American Hospital Formulary Service classification system, and the 2015 American Geriatrics Society Beers Criteria were applied to identify PIMs that should generally be avoided. Statistical analyses included chi-square tests and multivariable logistic regression to assess associations between PIM use and demographic variables, frailty status, and residence location. The results indicated that 18.5% of the 2,949 participants with available medication data used at least one PIM. The most common therapeutic categories were benzodiazepines (16.6% of identified PIMs), nonbenzodiazepine hypnotics (16.4%), antidepressants (15.2%), and first-generation antihistamines (10.5%). Multivariable analysis revealed that the total number of medications taken was the strongest predictor of PIM use; drivers taking 12 or more medications were eight times more likely to use PIMs than those taking four or fewer. Significant demographic correlates included being female (23.8% prevalence vs. 12.4% for males), white, and residing in urban areas (20.1% prevalence vs. 13.6–14.7% in suburban/rural areas). PIM use was not significantly associated with education, income, or frailty status in this sample. The findings highlight that PIM use is common among older drivers and involves medications known to increase crash risk, such as sedatives and antihistamines. The study concludes that the odds of PIM use rise sharply with polypharmacy and are particularly elevated among white, female drivers in urban settings. The authors suggest that implementing evidence-based interventions, such as computer-based alerts and restrictive prescription rules, could reduce PIM use. They also note that the reported prevalence is likely a conservative estimate, as the analysis excluded certain medications like proton-pump inhibitors. Future research should incorporate longitudinal data to better understand the trajectory of PIM use and its direct impact on driving outcomes.
Key finding
18.5% of older LongROAD drivers used at least one Beers Criteria PIM, with prevalence rising to 34.3% among those taking 12 or more medications.
Methodology
survey
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_aaa_foundation on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 3 | 2026-05-28 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
Information type
What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).
- Empirical Findings: observational prevalence