Shah Sparsh, McGowan Melissa, Petrosoniak Andrew
Department of Medicine, University of Toronto Faculty of Medicine, Toronto, Canada.
Department of Emergency Medicine, St. Michael's Hospital, Toronto, Canada.
BMJ Simul Technol Enhanc Learn. 2020 Aug 6;7(4):194-198. doi: 10.1136/bmjstel-2020-000650. eCollection 2021.
Latent safety threats (LSTs) in healthcare are hazards or conditions that risk patient safety but are not readily apparent without system stress. In situ simulation (ISS), followed by post-scenario debriefing is a common method to identify LSTs within the clinical environment. The function of post-ISS debriefing for LST identification is not well understood.
This study aims to qualitatively characterise the types of LSTs identified during ISS debriefing.
We conducted 12 ISS trauma scenarios followed by debriefing at a Canadian, Level 1 trauma centre. We designed the scenarios and debriefing for 15 and 20 min, respectively. Debriefings focused on LST identification, and each session was audio recorded and transcribed. We used an inductive approach with qualitative content analysis to code text data into an initial coding tree. We generated refined topics from the coded text data.
We identified five major topics: (1) communication and teamwork challenges, (2) system-level issues, (3) resource constraints, (4) positive team performance and (5) potential improvements to the current systems and processes.
During simulation debriefing sessions for LST identification, participants discussed threats related to communication and interpersonal issues. Safety issues relating to equipment, processes and the physical space received less emphasis. These findings may guide health system leaders and simulation experts better understanding of the strengths and limitations of simulation debriefing for LST identification. Further studies are required to compare ISS-based LST identification techniques.
医疗保健中的潜在安全威胁(LSTs)是指那些对患者安全构成风险,但在系统未承受压力时不易显现的危害或状况。情景模拟(ISS),随后进行情景后总结汇报是在临床环境中识别LSTs的常用方法。情景模拟后总结汇报在识别LSTs方面的作用尚未得到充分理解。
本研究旨在定性描述情景模拟总结汇报期间识别出的LSTs类型。
我们在加拿大一家一级创伤中心进行了12次情景模拟创伤情景演练,随后进行总结汇报。我们分别为情景设计和总结汇报设定了15分钟和20分钟的时间。总结汇报聚焦于LSTs的识别,每次会议都进行了音频录制和转录。我们采用归纳法和定性内容分析法将文本数据编码到一个初始编码树中。我们从编码后的文本数据中生成了细化的主题。
我们识别出五个主要主题:(1)沟通与团队协作挑战,(2)系统层面问题,(3)资源限制,(4)团队积极表现,以及(5)对当前系统和流程的潜在改进。
在用于识别LSTs的模拟总结汇报会议期间,参与者讨论了与沟通和人际问题相关的威胁。与设备、流程和物理空间相关的安全问题受到的关注较少。这些发现可能有助于卫生系统领导者和模拟专家更好地理解模拟总结汇报在识别LSTs方面的优势和局限性。需要进一步的研究来比较基于情景模拟的LSTs识别技术。