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了解导致医院住院药房药品转移的社会网络:一项社会网络分析。

Understanding the social networks that contribute to diversion in hospital inpatient pharmacies: A social network analysis.

作者信息

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

机构信息

HumanEra, Research and Innovation, North York General Hospital, Toronto, Ontario, Canada.

Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, Canada.

出版信息

Explor Res Clin Soc Pharm. 2024 Oct 19;16:100530. doi: 10.1016/j.rcsop.2024.100530. eCollection 2024 Dec.

Abstract

BACKGROUND

Controlled substances (CS) are 'diverted' (stolen) from healthcare facilities via many integrated and diverse mechanisms due to a lack of safeguards. There remains a gap in understanding how healthcare workers (HCWs) leverage their social networks (e.g., their role/tasks and interactions with other roles/tasks) within the medication use process (MUP) that contribute to diversion. Social network analysis (SNA) is an analytic approach used to map and analyze social connections, which can help identify influential interdependence between HCWs and tasks susceptible to drug diversion.

OBJECTIVES

To map the social network structures of MUP tasks vulnerable to CS diversion in two Inpatient pharmacies and compare diversion risks by identifying influential tasks and HCWs.

METHODS

This was an exploratory sequential mixed methods study conducted in the Inpatient pharmacies at two large hospitals in Toronto, Canada. Initial analysis used previously collected clinical observation data to identify key pharmacy roles and tasks vulnerable to CS diversion. Subsequently, a cross-sectional survey was conducted to collect demographic information on HCWs and assess their engagement in the identified vulnerable tasks. Clinical observations and survey data were used to perform two-mode SNA to identify connections between HCWs and tasks susceptible to drug diversion.

RESULTS

The analysis identified different network structures across both sites but highlighted the importance of strategic Pharmacist or Technician Supervisor oversight to moderate-high vulnerability tasks. Pharmacy technicians were found to be the network's most central actors, while Pharmacists had a more supportive role on the network's periphery, providing oversight. Across both sites, there was strong connectivity between HCWs and tasks, indicating a higher level of security against potential undetected diversion.

CONCLUSION

By strategically involving Pharmacists or Technician Supervisors, diversion risk can be mitigated through cross-checking and quality control. Through identifying the network structure of each unit, hospitals can identify opportunities for future interventions to prevent diversion.

摘要

背景

由于缺乏安全保障措施,管制药品会通过多种综合且多样的机制从医疗机构“转移”(被盗)。在理解医护人员如何在用药过程(MUP)中利用其社交网络(例如,他们的角色/任务以及与其他角色/任务的互动)导致药品转移方面,仍然存在差距。社会网络分析(SNA)是一种用于绘制和分析社会联系的分析方法,它有助于识别医护人员与易发生药品转移的任务之间的有影响力的相互依存关系。

目的

绘制两家住院药房中易发生管制药品转移的用药过程任务的社会网络结构,并通过识别有影响力的任务和医护人员来比较转移风险。

方法

这是一项在加拿大多伦多两家大型医院的住院药房进行的探索性序贯混合方法研究。初始分析使用先前收集的临床观察数据来识别易发生管制药品转移的关键药房角色和任务。随后,进行了一项横断面调查,以收集医护人员的人口统计学信息,并评估他们在已识别的易发生转移任务中的参与情况。临床观察和调查数据用于进行双模式社会网络分析,以识别医护人员与易发生药品转移的任务之间的联系。

结果

分析确定了两个地点不同的网络结构,但强调了药剂师或技术主管进行战略监督对中度至高度易发生转移的任务的重要性。发现药房技术人员是网络中最核心的参与者,而药剂师在网络边缘发挥更具支持性的作用,进行监督。在两个地点,医护人员与任务之间都有很强的连通性,表明对潜在未被发现的转移有更高的安全保障水平。

结论

通过策略性地让药剂师或技术主管参与,可以通过交叉核对和质量控制来降低转移风险。通过识别每个单元的网络结构,医院可以确定未来预防转移干预的机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a865/11543554/549ca8e1cde8/gr1.jpg

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