Evidence map›Paper›PMID 39873416›Full record

ArticleAustralian veterinary journal2025

Categorising reported errors and incidents from morbidity and mortality meetings (M&Ms) in a small animal multi-specialty veterinary teaching hospital.

G Giles, L A Boland, N Kirkwood, M P Ward, A Quain

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Article in Australian veterinary journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

G GilesSydney School of Veterinary Science, University of Sydney, Camperdown, Australia.
L A BolandSydney School of Veterinary Science, University of Sydney, Camperdown, Australia.
N KirkwoodSydney School of Veterinary Science, University of Sydney, Camperdown, Australia.
M P WardSydney School of Veterinary Science, University of Sydney, Camperdown, Australia.
A QuainSydney School of Veterinary Science, University of Sydney, Camperdown, Australia.ORCID https://orcid.org/0000-0001-9159-4569

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundErrors in veterinary clinical settings can lead to patient harm. Morbidity and mortality meetings (M&Ms) are forums to discuss errors and incidents that can lead or have led to adverse outcomes, potential harm or unsafe conditions, with the purpose of improving patient safety in future. Despite growing implementation of M&Ms in veterinary medicine, their effectiveness in improving future patient safety may be constrained by the need for absolute confidentiality during meetings.

objectiveTo pilot the use of a simple framework to categorise errors and incidents triggering M&Ms in a multi-specialty Australian veterinary teaching hospital. METHODOLOGY: A retrospective analysis of deidentified M&M summaries over 5 years (2018-2023) from a small animal multi-specialty veterinary teaching hospital. Animal demographic and incident information were extracted, classified by incident type and severity of harm adapted from Wallis and colleagues (2019). Descriptive statistics were produced for error category, severity, incident type and quarter of the year they occurred in. Recommendations were analysed using codebook thematic analysis.

resultsThere were 68 cases in total. The most common overall errors were oversight (n = 26/25.0%), drug (n = 20/19.2%), iatrogenic (n = 17, 16.3%) and staff (n = 17, 16.3%). Most cases resulted in temporary harm (n = 36, 52.9%), though 20.6% (n = 14) resulted in death, euthanasia or permanent harm. The most frequent recommendations were 'improving communications and record keeping', improving staff training' and 'ensuring appropriate equipment is available'.

conclusionCategorisation of errors using this simple framework can facilitate sharing of information which can be used to refine practices and improve animal safety, without compromising confidentiality of M&M meetings.

Indexed as

Hospitals, AnimalMedical ErrorsAnimalsAustraliaHospitals, TeachingHumansRetrospective Studiesadverse eventsmedical errorsmedication errorsmorbidity and mortality meetingspatient safetyroot cause analysis

Identifiers

PMID39873416
PMCPMC12050145

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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.