PDF(Pubmed)
Abstract：
BACKGROUND: The leaders of health care organizations are grappling with rising expenses and surging demands for health services. In response, they are increasingly embracing artificial intelligence (AI) technologies to improve patient care delivery, alleviate operational burdens, and efficiently improve health care safety and quality.
OBJECTIVE: In this paper, we map the current literature and synthesize insights on the role of leadership in driving AI transformation within health care organizations.
METHODS: We conducted a comprehensive search across several databases, including MEDLINE (via Ovid), PsycINFO (via Ovid), CINAHL (via EBSCO), Business Source Premier (via EBSCO), and Canadian Business & Current Affairs (via ProQuest), spanning articles published from 2015 to June 2023 discussing AI transformation within the health care sector. Specifically, we focused on empirical studies with a particular emphasis on leadership. We used an inductive, thematic analysis approach to qualitatively map the evidence. The findings were reported in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines.
RESULTS: A comprehensive review of 2813 unique abstracts led to the retrieval of 97 full-text articles, with 22 included for detailed assessment. Our literature mapping reveals that successful AI integration within healthcare organizations requires leadership engagement across technological, strategic, operational, and organizational domains. Leaders must demonstrate a blend of technical expertise, adaptive strategies, and strong interpersonal skills to navigate the dynamic healthcare landscape shaped by complex regulatory, technological, and organizational factors.
CONCLUSIONS: In conclusion, leading AI transformation in healthcare requires a multidimensional approach, with leadership across technological, strategic, operational, and organizational domains. Organizations should implement a comprehensive leadership development strategy, including targeted training and cross-functional collaboration, to equip leaders with the skills needed for AI integration. Additionally, when upskilling or recruiting AI talent, priority should be given to individuals with a strong mix of technical expertise, adaptive capacity, and interpersonal acumen, enabling them to navigate the unique complexities of the healthcare environment.
OBJECTIVE: In this paper, we map the current literature and synthesize insights on the role of leadership in driving AI transformation within health care organizations.
METHODS: We conducted a comprehensive search across several databases, including MEDLINE (via Ovid), PsycINFO (via Ovid), CINAHL (via EBSCO), Business Source Premier (via EBSCO), and Canadian Business & Current Affairs (via ProQuest), spanning articles published from 2015 to June 2023 discussing AI transformation within the health care sector. Specifically, we focused on empirical studies with a particular emphasis on leadership. We used an inductive, thematic analysis approach to qualitatively map the evidence. The findings were reported in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines.
RESULTS: A comprehensive review of 2813 unique abstracts led to the retrieval of 97 full-text articles, with 22 included for detailed assessment. Our literature mapping reveals that successful AI integration within healthcare organizations requires leadership engagement across technological, strategic, operational, and organizational domains. Leaders must demonstrate a blend of technical expertise, adaptive strategies, and strong interpersonal skills to navigate the dynamic healthcare landscape shaped by complex regulatory, technological, and organizational factors.
CONCLUSIONS: In conclusion, leading AI transformation in healthcare requires a multidimensional approach, with leadership across technological, strategic, operational, and organizational domains. Organizations should implement a comprehensive leadership development strategy, including targeted training and cross-functional collaboration, to equip leaders with the skills needed for AI integration. Additionally, when upskilling or recruiting AI talent, priority should be given to individuals with a strong mix of technical expertise, adaptive capacity, and interpersonal acumen, enabling them to navigate the unique complexities of the healthcare environment.
摘要：
背景：医疗机构的领导者正在努力应对不断上涨的费用和对医疗服务的需求激增。作为回应,他们越来越多地采用人工智能（AI）技术来改善患者护理流程，减轻业务负担，并有效提高医疗质量。
目标：在本文中，我们将回顾现有文献，并综合有关领导力在推动医疗保健领域AI转型中的作用的见解。
方法：我们对多个数据库进行了全面的搜索，包括MEDLINE（通过Ovid），PsycINFO（通过Ovid），CINAHL（通过EBSCO），BusinessSourcePremier（通过EBSCO），和加拿大商业与时事（通过ProQuest），2015年至2023年6月发表的关于医疗保健行业人工智能转型的文章。具体来说,我们专注于实证研究，特别强调领导力。我们用了一个归纳法,定性绘制证据的专题分析方法。根据PRISMA-ScR（系统评论的首选报告项目和范围评论的荟萃分析扩展）报告了研究结果。
结果：对2,813篇独特摘要的回顾导致检索了97篇全文文章以供评估，其中我们包括22篇文章供审查。我们对文献的映射表明，医疗保健行业内领先的AI转型涉及导航受复杂的各种监管影响的不断变化的格局。技术和组织环境。技术,战略,操作,需要组织领导才能推动AI转型。跨技术领域的领导力，适应性，和人际交往能力对于成功驾驭这一转变至关重要。
结论：结论：这篇综述提供了对领导力职能领域的见解，必要的领导能力，以及塑造与人工智能转型相关的领导行为的环境因素。未来对医疗保健中人工智能的研究应该将领导力作为一个关键因素进行调查，并检查功能领域的相互关联性。领导能力和背景，通过严格的研究方法，以加强现有的证据基础。
背景：
目标：在本文中，我们将回顾现有文献，并综合有关领导力在推动医疗保健领域AI转型中的作用的见解。
方法：我们对多个数据库进行了全面的搜索，包括MEDLINE（通过Ovid），PsycINFO（通过Ovid），CINAHL（通过EBSCO），BusinessSourcePremier（通过EBSCO），和加拿大商业与时事（通过ProQuest），2015年至2023年6月发表的关于医疗保健行业人工智能转型的文章。具体来说,我们专注于实证研究，特别强调领导力。我们用了一个归纳法,定性绘制证据的专题分析方法。根据PRISMA-ScR（系统评论的首选报告项目和范围评论的荟萃分析扩展）报告了研究结果。
结果：对2,813篇独特摘要的回顾导致检索了97篇全文文章以供评估，其中我们包括22篇文章供审查。我们对文献的映射表明，医疗保健行业内领先的AI转型涉及导航受复杂的各种监管影响的不断变化的格局。技术和组织环境。技术,战略,操作,需要组织领导才能推动AI转型。跨技术领域的领导力，适应性，和人际交往能力对于成功驾驭这一转变至关重要。
结论：结论：这篇综述提供了对领导力职能领域的见解，必要的领导能力，以及塑造与人工智能转型相关的领导行为的环境因素。未来对医疗保健中人工智能的研究应该将领导力作为一个关键因素进行调查，并检查功能领域的相互关联性。领导能力和背景，通过严格的研究方法，以加强现有的证据基础。
背景：
