急诊医疗服务提供者对在院前识别中风中使用人工智能的看法——挪威和瑞典的一项定性研究。

IF 2.3 3区 医学 Q1 EMERGENCY MEDICINE
Ann-Chatrin Linqvist Leonardsen, Camilla Hardeland, Andreas Dehre, Glenn Larsson
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引用次数: 0

摘要

背景:脑卒中是一个巨大且日益增加的健康挑战,导致获得性身体残疾和死亡。在中风急性期进行快速诊断评估是至关重要的,并且高度依赖于时间。研究表明,人工智能(AI)可以为院前急救中疑似脑卒中患者的预后、预测和资源优化做出贡献。本研究的目的是探讨急诊医疗服务提供者在院前评估疑似中风诊断患者时使用人工智能的观点。方法:采用基于人工智能诊断工具的脑卒中病例模拟定性研究设计。分别对来自挪威和瑞典三个救护站的24名参与者进行了一次焦点小组和10次二元访谈。数据分析遵循Braun和Clarke的主题分析步骤。结果:确定了三个主题,即(1)工具箱中的另一个工具,(2)信任是必不可少的,(3)细节决定成败。参与者强调,基于人工智能的工具只是他们常规评估的补充,包括症状、记忆、重要参数,以及他们自己的“临床眼睛”。此外,需要各方利益相关者的信任,才能使该工具在患者途径中发挥作用。最后,尺寸和重量,以及区分出血性和血栓性中风的能力是该工具可行的核心方面。结论:急诊医务人员在对疑似脑卒中患者进行评估时,主要依靠自己的临床眼,结合症状、记忆和生命参数测量。基于人工智能的工具可以用作决策过程中的支持,但这取决于EMS提供者、神经科医生和其他卫生专业人员对该工具的信任。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emergency medical services providers' perspectives on the use of artificial intelligence in prehospital identification of stroke- a qualitative study in Norway and Sweden.

Background: Stroke is a large and increasing health challenge, leading to acquired physical disability and mortality. A rapid diagnostic assessment in the acute phase of a stroke is crucial and highly time dependent. Studies suggest that artificial intelligence (AI) could contribute for prognostication, prediction and resource optimization in suspected stroke cases in prehospital emergency care. The objective of the current study was to explore Emergency Medical Services providers' perspectives on using AI in the prehospital assessment of patients with a suspected stroke diagnosis.

Methods: A qualitative study design following stroke case simulation with an AI-based diagnostic tool was used. One focus group and ten dyadic interviews were conducted comprising 24 participants from three ambulance stations in Norway and Sweden respectively. Data were analyzed following Braun and Clarke's steps for thematic analysis.

Results: Three themes were identified, namely (1) Another tool in the toolkit, (2) Trust is essential, and (3) The devil is in the details. The participants underlined that the AI-based tool was just an addition to their usual assessment, including symptoms, anamnesis, and vital parameters, as well as their own 'clinical eye'. Moreover, trust was needed from various stakeholders for the tool to have a function in the patient pathway. Finally, size and weight, as well as the ability to differentiate between hemorrhagic and thrombotic stroke were central aspects for the tool to be feasible.

Conclusion: Emergency Medical Services providers mainly rely on their own clinical eye, combining symptoms, anamnesis and measurement of vital parameters when assessing suspected stroke patients. AI-based tools may be used as support in the decision-making process, however this depends on the establishment of trust in the tool across EMS providers, neurologists and other health professionals.

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来源期刊
BMC Emergency Medicine
BMC Emergency Medicine Medicine-Emergency Medicine
CiteScore
3.50
自引率
8.00%
发文量
178
审稿时长
29 weeks
期刊介绍: BMC Emergency Medicine is an open access, peer-reviewed journal that considers articles on all urgent and emergency aspects of medicine, in both practice and basic research. In addition, the journal covers aspects of disaster medicine and medicine in special locations, such as conflict areas and military medicine, together with articles concerning healthcare services in the emergency departments.
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