Evidence map›Paper›PMID 40146397›Full record

ArticleInternational journal of clinical pharmacy2025

Streamlining the quality assessment in medication reviews: a biased random sampling approach using BRANT-MERQS criteria.

Eline Tobback, Maja Brumer, Anneleen Robberechts, Guido De Meyer, Hans De Loof

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Article in International journal of clinical pharmacy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Eline TobbackLaboratory of Physiopharmacology, University of Antwerp, Antwerp, Belgium.
Maja BrumerLaboratory of Physiopharmacology, University of Antwerp, Antwerp, Belgium.
Anneleen RobberechtsLaboratory of Physiopharmacology, University of Antwerp, Antwerp, Belgium.
Guido De MeyerLaboratory of Physiopharmacology, University of Antwerp, Antwerp, Belgium.
Hans De LoofLaboratory of Physiopharmacology, University of Antwerp, Antwerp, Belgium. hans.deloof@uantwerpen.be.ORCID http://orcid.org/0000-0003-4488-551X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedication review type 3 (MR3) is a comprehensive and collaborative clinical service designed to optimize patient treatment. The BRussels ANTwerp Medication Review Quality score (BRANT-MERQS) assesses MR3 quality, incorporating 45 general and 4 project-specific criteria. Using all BRANT-MERQS criteria is laborious and time-intensive, necessitating the development of a more efficient, streamlined version that preserves reliability.

aimThe aim of this study was to create a reliable and more efficient scoring system to evaluate the quality of MR3.

methodA random but weighted subset of the BRANT-MERQS quality criteria was employed in repeated tests. This technique helped determine the required subsample size for accurate quality scores. The weighting was based on previously assessed importance of each criterion.

resultsRepeated sampling showed that a 10-criteria random subsample yielded dependable quality scores. The biased sampling approach (5-3-1 ratio, 5 for highly important criteria, 3 for moderately important criteria and 1 for less important criteria) offered improvements compared to an unbiased one.

conclusionA more efficient MR3 quality evaluation was developed using the BRANT-MERQS scoring table. A 10 criteria biased subsample, representing one-third of the full assessment, ensures both time efficiency and consistency in quality assessment.

Indexed as

Drug Utilization ReviewQuality Assurance, Health CareHumansReproducibility of ResultsBRANT-MERQSCriteria weightingMedication reviewMedication review toolsQuality assessmentTime-efficient

Identifiers

PMID40146397

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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 Socratic graph.