Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK

IF 1.3 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Nikolaos Stogiannos , Tracy O'Regan , Erica Scurr , Lia Litosseliti , Michael Pogose , Hugh Harvey , Amrita Kumar , Rizwan Malik , Anna Barnes , Mark F McEntee , Christina Malamateniou
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引用次数: 0

Abstract

Introduction

Artificial Intelligence (AI) has the potential to transform medical imaging and radiotherapy; both fields where radiographers’ use of AI tools is increasing. This study aimed to explore the views of those professionals who are now using AI tools.

Methods

A small-scale exploratory research process was employed, where qualitative data was obtained from five UK-based participants; all professionals working in medical imaging and radiotherapy who use AI in clinical practice. Five semi-structured interviews were conducted online. Verbatim transcription was performed using an open-source automatic speech recognition model. Conceptual content analysis was performed to analyse the data and identify common themes.

Results

Participants spoke about the possibility of AI deskilling staff and changing their roles, they discussed issues around data protection and data sharing strategies, the important role of effective leadership of AI teams, and the seamless integration into workflows. Participants thought that the benefits of adopting AI were smoother clinical workflows, support for the workforce in decision-making, and enhanced patient safety/care. They also highlighted the need for tailored AI education/training, multidisciplinary teamwork and support.

Conclusion

Participants who are now using AI tools felt that clinical staff should be empowered to support AI implementation by adopting new and clearly defined roles and responsibilities. They suggest that attention to patient care and safety is a key to successful AI adoption. Despite the increasing adoption of AI, participants in the UK described a gap in knowledge with professionals still needing clear guidance, education and training regarding AI in preparation for more widespread adoption.
资深临床从业人员在实施人工智能方面的经验教训:英国医学影像和放射治疗领域的探索性定性研究。
导言:人工智能(AI)有可能改变医学影像和放射治疗;在这两个领域,放射技师对人工智能工具的使用都在增加。本研究旨在探讨目前正在使用人工智能工具的专业人员的观点:本研究采用了小规模探索性研究过程,从五位英国参与者那里获得了定性数据,他们都是在临床实践中使用人工智能的医学影像和放射治疗领域的专业人士。研究人员在网上进行了五次半结构化访谈。使用开源自动语音识别模型进行逐字转录。对数据进行了概念内容分析,以确定共同的主题:结果:参与者谈到了人工智能使员工离职并改变其角色的可能性,他们讨论了与数据保护和数据共享策略有关的问题、有效领导人工智能团队的重要作用以及与工作流程的无缝集成。与会者认为,采用人工智能的好处是临床工作流程更加顺畅,为员工决策提供支持,以及加强患者安全/护理。他们还强调需要有针对性的人工智能教育/培训、多学科团队合作和支持:结论:目前正在使用人工智能工具的与会者认为,临床工作人员应通过采用新的、明确界定的角色和职责来支持人工智能的实施。他们认为,关注患者护理和安全是成功采用人工智能的关键。尽管人工智能的应用日益广泛,但英国的参与者认为,专业人员在人工智能方面仍然需要明确的指导、教育和培训,为更广泛地应用人工智能做好准备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Medical Imaging and Radiation Sciences
Journal of Medical Imaging and Radiation Sciences RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
2.30
自引率
11.10%
发文量
231
审稿时长
53 days
期刊介绍: Journal of Medical Imaging and Radiation Sciences is the official peer-reviewed journal of the Canadian Association of Medical Radiation Technologists. This journal is published four times a year and is circulated to approximately 11,000 medical radiation technologists, libraries and radiology departments throughout Canada, the United States and overseas. The Journal publishes articles on recent research, new technology and techniques, professional practices, technologists viewpoints as well as relevant book reviews.
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