Evidence map›Paper›PMID 38308152›Full record

ArticleDrug safety2024

Exploring the Role of Guidelines in Contributing to Medication Errors: A Descriptive Analysis of National Patient Safety Incident Data.

Matthew D Jones, Shaojun Liu, Freyja Powell, Asma Samsor, Felicity Chao Ru Ting, Nikolaos Veliotis, Yin Mei Wong, Bryony Dean Franklin, Sara Garfield

Open access · hybridAbstract read
In one paragraph

Article in Drug safety, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
6.0field-weighted citation impact, top 4% of its field
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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
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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

9 authors at 3 institutions in 1 country.

Matthew D JonesDepartment of Life Sciences, University of Bath, Bath, BA2 7AY, UK. M.D.Jones@bath.ac.uk.ORCID http://orcid.org/0000-0002-2617-4098
Shaojun LiuUCL School of Pharmacy, London, UK.
Freyja PowellDepartment of Life Sciences, University of Bath, Bath, BA2 7AY, UK.
Asma SamsorDepartment of Life Sciences, University of Bath, Bath, BA2 7AY, UK.
Felicity Chao Ru TingDepartment of Life Sciences, University of Bath, Bath, BA2 7AY, UK.
Nikolaos VeliotisDepartment of Life Sciences, University of Bath, Bath, BA2 7AY, UK.
Yin Mei WongDepartment of Life Sciences, University of Bath, Bath, BA2 7AY, UK.
Bryony Dean FranklinUCL School of Pharmacy, London, UK.ORCID http://orcid.org/0000-0002-2892-1245
Sara GarfieldUCL School of Pharmacy, London, UK.ORCID http://orcid.org/0000-0002-9980-0520
University of Bath · GBThe London College · GBImperial College Healthcare NHS Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionClinical guidelines can contribute to medication errors but there is no overall understanding of how and where these occur.

objectivesWe aimed to identify guideline-related medication errors reported via a national incident reporting system, and describe types of error, stages of medication use, guidelines, drugs, specialties and clinical locations most commonly associated with such errors.

methodsRetrospective analysis of reports to the National Reporting and Learning System for England and Wales. A hierarchical task analysis (HTA) was developed, describing expected practice when using guidelines. A free-text search was conducted of medication incident reports (2016-2021) using search terms related to common guidelines. All identified reports linked to moderate-severe harm or death, and a random sample of 5100 no/low-harm reports were coded to describe deviations from the HTA. A random sample of 500 cases were independently double-coded.

resultsIn total, 28,217 reports were identified, with 608 relating to moderate-severe harm or death. Fleiss' kappa for interrater reliability was 0.46. Of the 5708 reports coded, 642 described an HTA step discrepancy (including four linked to a death), suggesting over 3200 discrepancies in the entire dataset of 28,217 reports. Discrepancies related to finding guidelines (n = 300 reports), finding information within guidelines (n = 166) and using information (n = 176). Discrepancies were most frequently identified for guidelines produced by a local organisation (n = 405), and most occurred during prescribing (n = 277) or medication administration (n = 241).

conclusionDifficulties finding and using information from clinical guidelines contribute to thousands of prescribing and medication administration incidents, some of which are associated with substantial patient harm.

Indexed as

Medication ErrorsPatient SafetyHumansReproducibility of ResultsRetrospective StudiesRisk Management

Identifiers

PMID38308152
PMCPMC10954937
OpenAlexW4391469827

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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 OpenQuestion graph.