Evidence map›Paper›PMID 40892868›Full record

ArticlePloS one2025

Unveiling hidden connections: How social networks impact diversion in hospital emergency departments: An exploratory social network analysis.

Troy Francis, Maaike de Vries, Mark Fan, Reza Yousefi-Nooraie, Mathieu Ouimet, Valeria E Rac, Patricia Trbovich

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Troy FrancisHumanEra, Research and Innovation, North York General Hospital, Toronto, Ontario, Canada.ORCID https://orcid.org/0000-0002-7259-0922
Maaike de VriesHumanEra, Research and Innovation, North York General Hospital, Toronto, Ontario, Canada.
Mark FanHumanEra, Research and Innovation, North York General Hospital, Toronto, Ontario, Canada.
Reza Yousefi-NooraieDepartment of Public Health Sciences, University of Rochester, New York, United States of America.
Mathieu OuimetDepartment of Political Science, Université Laval, Quebec, Canada.
Valeria E RacInstitute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, Canada.ORCID https://orcid.org/0000-0002-0426-4594
Patricia TrbovichHumanEra, Research and Innovation, North York General Hospital, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to a lack of safeguards, controlled substances (CS) can be diverted (stolen) from healthcare facilities. While it is known that healthcare workers (HCWs) can use their social networks within the medication use process (MUP) to facilitate diversion, the specific connections between HCWs and the MUP tasks most vulnerable to diversion remain poorly understood. Social network analysis (SNA) was used to analyze social connections to identify influential relationships between HCWs and tasks susceptible to diversion.To map the social network structures of MUP tasks vulnerable to CS diversion in two Emergency Departments (EDs), identify influential tasks and HCWs, and report HCW perceptions of in-hospital diversion.This study used a mixed methods approach in the ED of two large hospitals in Toronto, Canada. Previously collected clinical observation data was used to identify tasks at risk of diversion, and cross-sectional surveys were conducted to assess HCW's involvement in the identified vulnerable tasks. A two-mode SNA was conducted to identify connections between HCWs and tasks susceptible to drug diversion.SNA identified a circular structure across both sites, highlighting the network's redundancy and capacity to efficiently disseminate information. Nurses were central to tasks with a higher risk of diversion. Physicians and Pharmacists had limited direct involvement in these tasks. Tasks with frequent interprofessional interactions, such as creating, following, or reviewing orders for non-admitted patients, are vulnerable to diversion due to HCWs acting on decisions made by other professionals without closely scrutinizing the details. No significant differences were observed between sites, suggesting a shared perception of diversion. The SNA results highlight the critical role of network structure in shaping vulnerability to diversion. The similarities across both sites suggest a systemic challenge across ED settings that require targeted interventions. By uncovering critical points of influence, we can better understand how diversion occurs and develop targeted interventions to prevent it.

Indexed as

Emergency Service, HospitalSocial Network AnalysisSocial NetworkingCanadaCross-Sectional StudiesFemaleHealth PersonnelHumansMaleOntario

Identifiers

PMID40892868
PMCPMC12404548

What OpenQuestion holds

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LicenceCC BY
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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.