Learning to Teach AI: Understanding the Needs of Healthcare Professionals.

Tharshini Jeyakumar, Sarmini Balakumar, Sarah Younus, Megan Clare, Rebecca Charow, Dalia Al-Mouaswas, Azra Dhalla, Caitlin Gillan, Jessica Jardine, Sedef Akinli Kocak, Jane Mattson, Mohammad Salhia, Walter Tavares, Melody Zhang, David Wiljer
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Abstract

As Artificial Intelligence (AI) technologies become more integrated into clinical settings to optimize care, healthcare professionals (HCPs) will need to become more adept in responsibly using these novel technologies to augment patient care. A qualitative study, consisting of semi-structured interviews was conducted to explore the informational needs of HCPs and gaps in current AI education. Participants, consisting of educators and learners, were recruited from AI programs. The interview data were analyzed using inductive thematic analysis. Three themes were identified, addressing the need for (1) developing a longitudinal AI curriculum to transform the mindset, skillset, and toolset of providers, (2) cultivating an active learning approach to foster knowledge mobilization and optimize the use of AI tools in the provision of care, and (3) fostering a multidisciplinary approach to AI curriculum design is essential to promote collaborative efforts among HCPs in implementing AI tools. This study identified five key recommendations to prepare HCPs with the knowledge and skills necessary for an AI-driven future.

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学习教授人工智能:了解医疗保健专业人员的需求。
随着人工智能(AI)技术越来越多地集成到临床环境中以优化护理,医疗保健专业人员(HCPs)将需要更加熟练地负责任地使用这些新技术来增强患者护理。一项由半结构化访谈组成的定性研究旨在探讨医护人员的信息需求和当前人工智能教育的差距。参与者包括教育工作者和学习者,他们是从人工智能项目中招募的。访谈数据采用归纳主题分析法进行分析。确定了三个主题,以满足以下需求:(1)开发纵向人工智能课程,以转变提供者的思维方式、技能和工具集;(2)培养主动学习方法,以促进知识动员和优化人工智能工具在提供护理中的使用;(3)培养多学科方法来设计人工智能课程,对于促进hcp之间在实施人工智能工具方面的合作至关重要。本研究确定了五项关键建议,以使医护人员具备人工智能驱动的未来所需的知识和技能。
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