Evidence map›Paper›PMID 23306005›Full record

ArticleBMJ open2013

Cross-sectional study of prescribing errors in patients admitted to nine hospitals across North West England.

Kay Seden, Jamie J Kirkham, Tom Kennedy, Michael Lloyd, Sally James, Aine McManus, Andrew Ritchings, Jennifer Simpson, Dave Thornton, Andrea Gill and 3 more

Abstract read
In one paragraph

Article in BMJ open, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
–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

33 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Associations of physicians' prescribing experience, work hours, and workload with prescription errors.Journal of the American Medical Informatics Association : JAMIA · 2021
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  11. Observational
  12. Comparison of pharmacy technicians' and doctors' medication transcribing errors at hospital discharge.European journal of hospital pharmacy : science and practice · 2020
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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

13 authors.

Kay SedenNIHR Biomedical Research Centre, Royal Liverpool and Broadgreen University Hospitals NHS Trust, Liverpool, UK.
Jamie J Kirkham
Tom Kennedy
Michael Lloyd
Sally James
Aine McManus
Andrew Ritchings
Jennifer Simpson
Dave Thornton
Andrea Gill
Carolyn Coleman
Bethan Thorpe
Saye H Khoo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the prevalence, type and severity of prescribing errors observed between grades of prescriber, ward area, admission or discharge and type of medication prescribed.

designWard-based clinical pharmacists prospectively documented prescribing errors at the point of clinically checking admission or discharge prescriptions. Error categories and severities were assigned at the point of data collection, and verified independently by the study team.

settingProspective study of nine diverse National Health Service hospitals in North West England, including teaching hospitals, district hospitals and specialist services for paediatrics, women and mental health.

resultsOf 4238 prescriptions evaluated, one or more error was observed in 1857 (43.8%) prescriptions, with a total of 3011 errors observed. Of these, 1264 (41.9%) were minor, 1629 (54.1%) were significant, 109 (3.6%) were serious and 9 (0.30%) were potentially life threatening. The majority of errors considered to be potentially lethal (n=9) were dosing errors (n=8), mostly relating to overdose (n=7). The rate of error was not significantly different between newly qualified doctors compared with junior, middle grade or senior doctors. Multivariable analyses revealed the strongest predictor of error was the number of items on a prescription (risk of error increased 14% for each additional item). We observed a high rate of error from medication omission, particularly among patients admitted acutely into hospital. Electronic prescribing systems could potentially have prevented up to a quarter of (but not all) errors.

conclusionsIn contrast to other studies, prescriber experience did not impact on overall error rate (although there were qualitative differences in error category). Given that multiple drug therapies are now the norm for many medical conditions, health systems should introduce and retain safeguards which detect and prevent error, in addition to continuing training and education, and migration to electronic prescribing systems.

Identifiers

PMID23306005
PMCPMC3553389

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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.