Mamykina Lena, Jiang Silis, Collins Sarah A, Twohig Bridget, Hirsh Jamie, Hripcsak George, Stanley Hum R, Kaufman David R
Department of Biomedical Informatics, Columbia University, United States.
Department of Biomedical Informatics, Columbia University, United States.
J Biomed Inform. 2016 Aug;62:117-24. doi: 10.1016/j.jbi.2016.03.025. Epub 2016 Apr 7.
To examine a novel mixed-methods approach for studying patterns of clinical communication that could inform future informatics solutions, with a specific focus on handoff within interdisciplinary teams.
Researchers observed, recorded, and transcribed verbal handoff discussions of different members of critical care teams. The transcripts were coded qualitatively, and then analyzed quantitatively for emerging structural patterns using categorical cluster analysis, and for degree of shared mental models (SMM) using the modified Pyramid method.
An empirical study using the proposed mixed-methods approach suggested emerging patterns of communication among clinicians. For example, the temporal focus of handoff was often determined by the role of the clinician giving the handoff; the clinical content of handoff was consistent between clinicians, but varied between patients. The SMM index ranged from 0.065 (with the maximum possible overlap score of 1) to 0.007 with a median of 0.026; the overlap was higher in statements concerned with patient presentation (23.6% of these had overlap) and referring to the past (24% overlapped). This calculated SMM index was correlated with the assessment of coherence within the participating teams by independent physicians (r=0.63, p=0.038).
The proposed novel mixed-methods approach helped to reveal emerging patterns in content and structure of handoff communication and highlight differences due to the clinical context, and to the different priorities of clinicians on interdisciplinary patient care teams. The approach for calculating SMM is more ecologically sensitive as it relies on naturally occurring discourse and less intrusive than traditional ways of assessing SMM, and takes initial steps toward establishing empirical foundation for the design of electronic tools to support handoff in interdisciplinary teams.
研究一种用于探究临床沟通模式的新型混合方法，该方法可为未来的信息学解决方案提供参考，尤其关注跨学科团队内部的交接班情况。
研究人员观察、记录并转录了重症监护团队不同成员之间的口头交接班讨论。对转录文本进行定性编码，然后使用分类聚类分析对出现的结构模式进行定量分析，并使用改良的金字塔方法对共享心智模型（SMM）的程度进行定量分析。
一项使用所提出的混合方法的实证研究表明临床医生之间出现了沟通模式。例如，交接班的时间重点通常由进行交接班的临床医生的角色决定；临床医生之间交接班的临床内容是一致的，但不同患者之间存在差异。SMM指数范围从0.065（最大可能重叠分数为1）到0.007，中位数为0.026；在与患者表现相关的陈述中重叠率更高（其中23.6%有重叠），以及涉及过去情况的陈述中重叠率更高（24%重叠）。计算得出的SMM指数与独立医生对参与团队内连贯性的评估相关（r = 0.63，p = 0.038）。
所提出的新型混合方法有助于揭示交接班沟通在内容和结构方面出现的模式，并突出因临床背景以及跨学科患者护理团队中临床医生不同优先级而产生的差异。计算SMM的方法对生态环境更敏感，因为它依赖于自然发生的话语，比传统评估SMM的方法侵入性更小，并朝着为跨学科团队中支持交接班的电子工具设计建立实证基础迈出了初步步伐。
