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检查清单以减少诊断错误:使用人为因素框架对文献进行的系统回顾。

Checklists to reduce diagnostic error: a systematic review of the literature using a human factors framework.

机构信息

Department of Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA

Department of Medicine, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.

出版信息

BMJ Open. 2022 Apr 29;12(4):e058219. doi: 10.1136/bmjopen-2021-058219.

Abstract

OBJECTIVES

To apply a human factors framework to understand whether checklists reduce clinical diagnostic error have (1) gaps in composition; and (2) components that may be more likely to reduce errors.

DESIGN

Systematic review.

DATA SOURCES

PubMed, EMBASE, Scopus and Web of Science were searched through 15 February 2022.

ELIGIBILITY CRITERIA

Any article that included a clinical checklist aimed at improving the diagnostic process. Checklists were defined as any structured guide intended to elicit additional thinking regarding diagnosis.

DATA EXTRACTION AND SYNTHESIS

Two authors independently reviewed and selected articles based on eligibility criteria. Each extracted unique checklist was independently characterised according to the well-established human factors framework: Systems Engineering Initiative for Patient Safety 2.0 (SEIPS 2.0). If reported, checklist efficacy in reducing diagnostic error (eg, diagnostic accuracy, number of errors or any patient-related outcomes) was outlined. Risk of study bias was independently evaluated using standardised quality assessment tools in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

RESULTS

A total of 30 articles containing 25 unique checklists were included. Checklists were characterised within the SEIPS 2.0 framework as follows: Work Systems subcomponents of Tasks (n=13), Persons (n=2) and Internal Environment (n=3); Processes subcomponents of Cognitive (n=20) and Social and Behavioural (n=2); and Outcomes subcomponents of Professional (n=2). Other subcomponents, such as External Environment or Patient outcomes, were not addressed. Fourteen checklists examined effect on diagnostic outcomes: seven demonstrated improvement, six were without improvement and one demonstrated mixed results. Importantly, Tasks-oriented studies more often demonstrated error reduction (n=5/7) than those addressing the Cognitive process (n=4/10).

CONCLUSIONS

Most diagnostic checklists incorporated few human factors components. Checklists addressing the SEIPS 2.0 Tasks subcomponent were more often associated with a reduction in diagnostic errors. Studies examining less explored subcomponents and emphasis on Tasks, rather than the Cognitive subcomponents, may be warranted to prevent diagnostic errors.

摘要

目的

应用人为因素框架来理解清单是否减少临床诊断错误,(1)在组成上存在差距;(2)可能更能减少错误的组成部分。

设计

系统评价。

资料来源

通过 2022 年 2 月 15 日在 PubMed、EMBASE、Scopus 和 Web of Science 上搜索。

入选标准

任何包含旨在改善诊断过程的临床清单的文章。清单被定义为任何旨在引出更多关于诊断思考的结构化指南。

资料提取与综合

两位作者根据入选标准独立审查和选择文章。每位作者独立提取独特的清单,并根据成熟的人为因素框架进行特征描述:患者安全系统工程倡议 2.0(SEIPS 2.0)。如果有报道,清单在减少诊断错误方面的功效(例如,诊断准确性、错误数量或任何与患者相关的结果)将被概述。使用符合系统评价和荟萃分析的首选报告项目的标准化质量评估工具,独立评估研究偏倚风险。

结果

共纳入 30 篇文章,包含 25 个独特的清单。清单在 SEIPS 2.0 框架内的特征如下:任务的工作系统子组件(n=13)、人员(n=2)和内部环境(n=3);认知过程(n=20)和社会和行为过程(n=2)的过程子组件;专业(n=2)的结果子组件。没有涉及其他子组件,如外部环境或患者结果。有 14 个清单检查了诊断结果的影响:7 个显示改善,6 个没有改善,1 个显示混合结果。重要的是,面向任务的研究更经常显示出错误减少(n=5/7),而不是针对认知过程的研究(n=4/10)。

结论

大多数诊断清单仅纳入了少数人为因素组成部分。针对 SEIPS 2.0 任务子组件的清单更常与诊断错误的减少相关。研究探索较少涉及的子组件并强调任务,而不是认知子组件,可能有助于防止诊断错误。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/431e/9058772/b54cb7b123cd/bmjopen-2021-058219f01.jpg

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