Adventist Health White Memorial, Los Angeles, CA, USA.
University of California Los Angeles, USA.
J Transcult Nurs. 2023 Jan;34(1):32-39. doi: 10.1177/10436596221129226. Epub 2022 Oct 8.
Triage requires rapid determination of acuity and resources. Current modalities allow for individual judgment, with varied application of algorithmic rules. Although artificial intelligence can improve triage accuracy, gaps remain in understanding implementation facilitators and barriers, especially those related to the cultural understandings by nurses of emergency department presentations. The purpose of this study was to explore the cultural and technological elements of the implementation of an artificial intelligence clinical decision support aid (i.e., KATE) in an emergency nursing triage process in an urban community hospital on the West Coast of the United States.
An exploratory qualitative study using semi-structured small group and individual interviews and constant comparison analysis strategies. The sample comprised 13 emergency department triage nurses at one site. Campinha-Bacote's theory of cultural competence framed the study.
Responses yielded the overall theme of . Supporting categories included ; and . Participants reported reliance on clinical experience and cultural knowledge to assign acuity.
The implementation of an artificial intelligence program was initially received skeptically due to the acontextual nature of AI, but grew to be perceived as a safety net for triage decision making among emergency nurses.
分诊需要快速确定病情严重程度和资源。目前的方法允许进行个体判断,并应用不同的算法规则。尽管人工智能可以提高分诊准确性,但在理解实施促进因素和障碍方面仍存在差距,特别是与护士对急诊科就诊的文化理解有关的障碍。本研究的目的是探讨在美国西海岸的一家城市社区医院的急诊护理分诊过程中,人工智能临床决策支持辅助工具(即 KATE)实施的文化和技术要素。
采用半结构化小组和个人访谈以及恒比分析策略的探索性定性研究。样本包括一个地点的 13 名急诊分诊护士。坎皮尼亚-巴科特的文化能力理论为研究提供了框架。
回应产生了整体主题。支持类别包括;和。参与者报告说,他们依靠临床经验和文化知识来确定病情严重程度。
由于人工智能的非语境性质,人工智能计划的实施最初受到怀疑,但后来被认为是急诊护士分诊决策的安全网。