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医疗保健中沟通错误分析框架

A Framework for the Analysis of Communication Errors in Health Care.

作者信息

Bender John A, Thiyagarajan Sreedevi, Morrish Wendy, Mims Maisha, Yackel Edward E

机构信息

Department of Veterans Affairs, VHA National Center for Patient Safety, Ann Arbor, Michigan.

出版信息

J Patient Saf. 2025 Mar 1;21(2):69-81. doi: 10.1097/PTS.0000000000001303. Epub 2024 Dec 23.

Abstract

OBJECTIVES

The goal of this study was to develop a systematic method to identify and classify different types of communication failures leading to patient safety events. We aimed to develop a taxonomy code sheet for identifying communication errors and provide a framework tool to classify the communication error types.

METHODS

This observational study used the Delphi method to develop a taxonomy code sheet for identifying communication errors reported in the Veterans Health Administration patient safety databases between April 2018 and March 2021. We also used Natural Language Processing to create a framework tool to classify the 9 types of communication errors using this taxonomy. Finally, analysis was done to identify affected clinical locations.

RESULTS

We identified 9 types of communication failures that impacted clinical outcomes using the taxonomy code sheet developed. The top 3 errors were related to nonadherence to facility standard operating procedures (993, 37.6%), followed by written errors (e.g., unclear documentation or not using plain language) (587, 22.3%) and no communication (347, 13.2%). The remaining categories of communication types are electronic (253, 9.6%), verbal (205, 7.8%), hand-off (124, 4.7%), visual (76, 2.9%), listening (41, 1.6%), and nonverbal (12, 0.5%). A cognitive aide was developed to demonstrate the step-by-step method for using the framework tool to classify the communication errors.

CONCLUSIONS

The cognitive aide and the framework tool developed in this study can be used in any healthcare setting to identify and classify communication failures and mitigate potential risks contributing to safety events.

摘要

目的

本研究的目的是开发一种系统方法,以识别和分类导致患者安全事件的不同类型的沟通失误。我们旨在开发一种分类编码表来识别沟通错误,并提供一个框架工具来对沟通错误类型进行分类。

方法

这项观察性研究使用德尔菲法开发了一种分类编码表,用于识别2018年4月至2021年3月期间退伍军人健康管理局患者安全数据库中报告的沟通错误。我们还使用自然语言处理创建了一个框架工具,使用该分类法对9种沟通错误类型进行分类。最后,进行分析以确定受影响的临床地点。

结果

我们使用开发的分类编码表确定了9种影响临床结果的沟通失误类型。前三大错误与不遵守机构标准操作程序有关(993例,37.6%),其次是书面错误(例如,文件不清楚或未使用通俗易懂的语言)(587例,22.3%)和无沟通(347例,13.2%)。其余沟通类型类别包括电子(253例,9.6%)、口头(205例,7.8%)、交接班(124例,4.7%)、视觉(76例,2.9%)、听力(41例,1.6%)和非语言(12例,0.5%)。开发了一种认知辅助工具,以演示使用框架工具对沟通错误进行分类的逐步方法。

结论

本研究中开发的认知辅助工具和框架工具可用于任何医疗环境,以识别和分类沟通失误,并减轻导致安全事件的潜在风险。

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