ArticleDrugs & aging2024
Development of a Frailty Screening Tool Using Electronic Community Pharmacy Records.
Article in Drugs & aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFrailty is associated with increased susceptibility to medication-related harm, highlighting the importance of medication review for frail older adults. Community pharmacists are increasingly involved in the initiation of medication reviews. Yet, current frailty measurement methods are impractical in this setting. Alternative approaches, leveraging routinely collected data, are needed.
objectiveTo develop a frailty screening tool utilising routine electronic pharmacy records.
methodsCommunity-dwelling older adults (≥ 70 years) using ≥ 5 chronic medications were recruited in 196 Belgian community pharmacies. Frailty was assessed using SHARE-FI75+ (based on Fried's frailty phenotype). Model development was on the basis of a two-stage approach using multivariable logistic regression with split-sample internal validation. Stage 1 considered only electronic pharmacy record variables, while stage 2 also included other variables that can easily be collected in the community pharmacy. Model performance was evaluated for discrimination, calibration and predictive accuracy.
resultsWe recruited 875 participants [mean ± standard deviation (SD) age 79.3 ± 5.9 years], with 14.8% identified as frail. At stage 1, the frailty screening model included age, sex, reimbursement level of medical expenses, number of chronic medications and medication-derived comorbidities (anxiety, congestive heart failure, hypertension) [area under the receiver operating characteristic curve (AUC) 0.77, 95% confidence interval (CI) 0.69-0.85; sensitivity 78.0%; specificity 60.1%]. At stage 2, additional information on difficulties with basic activities of daily living or pharmacist's intuitive frailty assessment further improved the model (AUC 0.81, 95% CI 0.74-0.88 and AUC 0.82, 95% CI 0.75-0.89, respectively).
conclusionsWe developed a screening tool for frailty using data from electronic pharmacy records. This tool offers the opportunity for frailty screening in community pharmacy and to identify individuals that may benefit the most from medication review. External validation is warranted.
Indexed as
Identifiers
39579275What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.