Evidence map›Paper›PMID 39893447›Full record

ArticleBMC health services research2025

Confronting needlestick and sharp injuries in healthcare: a decade of struggle and progress in a university teaching hospital.

Shuk-Ching Wong, Lithia Lai-Ha Yuen, Germaine Kit-Ming Lam, Monica Oi-Tung Kwok, Crystal Yuen-Ki Siu, Bella Hong-Yan Li, Jonathan Hon-Kwan Chen, Simon Yung-Chun So, Kelvin Hei-Yeung Chiu, Vincent Chi-Chung Cheng

Abstract read
In one paragraph

Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

10 authors.

Shuk-Ching WongInfection Control Team, Queen Mary Hospital, Hong Kong West Cluster, Pokfulam, Hong Kong Special Administrative Region, China. shchwong@hku.hk.
Lithia Lai-Ha YuenInfection Control Team, Queen Mary Hospital, Hong Kong West Cluster, Pokfulam, Hong Kong Special Administrative Region, China.
Germaine Kit-Ming LamInfection Control Team, Queen Mary Hospital, Hong Kong West Cluster, Pokfulam, Hong Kong Special Administrative Region, China.
Monica Oi-Tung KwokInfection Control Team, Queen Mary Hospital, Hong Kong West Cluster, Pokfulam, Hong Kong Special Administrative Region, China.
Crystal Yuen-Ki SiuInfection Control Team, Queen Mary Hospital, Hong Kong West Cluster, Pokfulam, Hong Kong Special Administrative Region, China.
Bella Hong-Yan LiInfection Control Team, Queen Mary Hospital, Hong Kong West Cluster, Pokfulam, Hong Kong Special Administrative Region, China.
Jonathan Hon-Kwan ChenDepartment of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Simon Yung-Chun SoDepartment of Microbiology, Queen Mary Hospital, Pokfulam, Hong Kong Special Administrative Region, China.
Kelvin Hei-Yeung ChiuDepartment of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Vincent Chi-Chung ChengInfection Control Team, Queen Mary Hospital, Hong Kong West Cluster, Pokfulam, Hong Kong Special Administrative Region, China. vcccheng@hku.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeedlestick and sharp injuries (NSIs) among healthcare workers (HCWs) are a significant concern in infection prevention. This study analyzes the incidence and characteristics of NSIs at Queen Mary Hospital and assesses the effectiveness of targeted training programs for interns.

methodsA retrospective analysis was conducted on NSI reports from 2014 to 2023, focusing on episodes involving medical, nursing, allied health, and other staff. Personal coaching training programs for newly recruited interns were implemented in 2019 to enhance safety practices. NSI episodes were analyzed in relation to patient days and full-time equivalents (FTE).

resultsDuring the study period, there was a mean of 464,118 patient days per year, with an average of 5,928 HCWs per year. A total of 1,076 NSI episodes were reported, resulting in a mean of 2.31 episodes per 10,000 patient days and 1.82 episodes per 100 FTE. Medical staff accounted for 502 episodes (47%), while nursing staff had 339 episodes (32%). The mean NSI episodes among medical staff were significantly higher than nursing staff per year, measured per 10,000 patient days (1.08 ± 0.21 vs. 0.73 ± 0.16, p = 0.001) and per 100 FTE (8.46 ± 1.95 vs. 1.62 ± 0.40, p < 0.001). Of the 1,076 episodes, 430 (40%) occurred in HCWs with less than 1 year of experience, with 278 (65%) attributed to interns, contributing to 26% of the overall NSI burden. Most incidents among interns occurred in wards (95%, 264/278), with 95% (252/264) involving hollow needles. Notably, 54% (149/278) involved safety-equipped devices, yet 94% (140/149) of these were not activated properly. Following targeted training, NSI rates among interns significantly decreased from 0.82 to 0.46 per 10,000 patient days (R

conclusionsThe study highlights the ongoing issue of NSIs among HCWs, especially inexperienced interns. While training programs have shown promise in reducing NSI rates, the high incidence of safety devices not being effectively utilized underscores the need for continuous education and hands-on training to enhance safety practices and prevent NSIs in healthcare settings.

Indexed as

Health PersonnelHospitals, TeachingNeedlestick InjuriesAdultFemaleHospitals, UniversityHumansIncidenceInternship and ResidencyMaleRetrospective StudiesInjuriesNeedlestickSharp

Identifiers

PMID39893447
PMCPMC11787756

What OpenQuestion holds

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LicenceCC BY
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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.