Exploring the social dimensions of AI integration in healthcare: a qualitative study of stakeholder views on challenges and opportunities.

IF 2.4 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Julia-Astrid Moldt, Teresa Festl-Wietek, Wolfgang Fuhl, Susanne Zabel, Manfred Claassen, Samuel Wagner, Kay Nieselt, Anne Herrmann-Werner
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Abstract

Objectives: This study aimed to investigate the opportunities and challenges associated with integrating artificial intelligence (AI) in healthcare by exploring the perspectives of various stakeholders. The objective was to provide a nuanced understanding of stakeholder views to address concerns and promote the acceptance and successful integration of AI technologies in medical practice.

Design: This exploratory qualitative study used semi-structured interviews. Data were analysed using a combination of deductive and inductive coding, followed by content analysis to identify and develop categories.

Setting: This study was conducted in Tübingen, Germany, within the framework of the TüKITZMed project (Tübingen AI Training Center for Medicine), between August 2022 and March 2023.

Participants: A total of 38 stakeholders participated, including 6 lecturers, 9 clinicians, 10 healthcare students, 6 AI experts and 7 institutional stakeholders. Inclusion criteria included professionals involved in or affected by AI in healthcare, while exclusion criteria comprised individuals without relevant experience.

Interventions: Not applicable.

Outcome measures: The main outcome was the identification of thematic categories capturing stakeholders' perceptions, expectations and concerns regarding the integration of AI in healthcare.

Results: The analysis identified two main thematic categories: two main categories encompassing a total of 14 subcategories: (1) perceived opportunities of AI in medicine, including aspects of increased efficiency, reduced workload and improved patient safety and (2) perceived challenges of AI in medicine, such as its impact on medical decision-making and concerns about dependence on technology. These themes reflect diverse perspectives and insights across stakeholder groups.

Conclusions: Diverse stakeholder perspectives offer valuable insights into the anticipated effects of AI in healthcare. Understanding these perspectives can support decision-makers in designing context-sensitive AI strategies and identifying areas for further professional and institutional development. Future research should monitor how these attitudes evolve in response to technological progress and real-world implementation.

探索人工智能在医疗保健领域整合的社会维度:利益相关者对挑战和机遇看法的定性研究。
目的:本研究旨在通过探讨不同利益相关者的观点,探讨将人工智能(AI)整合到医疗保健中的机遇和挑战。其目标是对利益攸关方的观点提供细致入微的理解,以解决关切,促进人工智能技术在医疗实践中的接受和成功整合。设计:本探索性质的研究采用半结构化访谈。数据分析使用演绎和归纳编码的组合,其次是内容分析,以确定和发展类别。背景:本研究于2022年8月至2023年3月在德国宾根市,在t kitzmed项目(t宾根医学人工智能培训中心)的框架内进行。参与者:共有38名利益攸关方参加,包括6名讲师、9名临床医生、10名保健专业学生、6名人工智能专家和7名机构利益攸关方。纳入标准包括在医疗保健领域参与人工智能或受其影响的专业人员,而排除标准包括没有相关经验的个人。干预措施:不适用。结果测量:主要结果是确定了主题类别,涵盖了利益攸关方对将人工智能纳入医疗保健的看法、期望和关切。结果:分析确定了两个主要的主题类别:两个主要类别共包含14个子类别:(1)人工智能在医学中的感知机会,包括提高效率、减少工作量和改善患者安全等方面;(2)人工智能在医学中的感知挑战,例如其对医疗决策的影响以及对技术依赖的担忧。这些主题反映了利益相关者群体的不同观点和见解。结论:不同利益相关者的观点为人工智能在医疗保健领域的预期影响提供了有价值的见解。理解这些观点可以帮助决策者设计情境敏感的人工智能战略,并确定进一步专业和机构发展的领域。未来的研究应该监测这些态度如何随着技术进步和现实世界的实施而演变。
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
BMJ Open
BMJ Open MEDICINE, GENERAL & INTERNAL-
CiteScore
4.40
自引率
3.40%
发文量
4510
审稿时长
2-3 weeks
期刊介绍: BMJ Open is an online, open access journal, dedicated to publishing medical research from all disciplines and therapeutic areas. The journal publishes all research study types, from study protocols to phase I trials to meta-analyses, including small or specialist studies. Publishing procedures are built around fully open peer review and continuous publication, publishing research online as soon as the article is ready.
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