Javier Gazquez-Garcia, Carlos Luis Sánchez-Bocanegra, Jose Luis Sevillano
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引用次数: 0
Abstract
Background: Technological advancements have significantly reshaped health care, introducing digital solutions that enhance diagnostics and patient care. Artificial intelligence (AI) stands out, offering unprecedented capabilities in data analysis, diagnostic support, and personalized medicine. However, effectively integrating AI into health care necessitates specialized competencies among professionals, an area still in its infancy in terms of comprehensive literature and formalized training programs.
Objective: This systematic review aims to consolidate the essential skills and knowledge health care professionals need to integrate AI into their clinical practice effectively, according to the published literature.
Methods: We conducted a systematic review, across databases PubMed, Scopus, and Web of Science, of peer-reviewed literature that directly explored the required skills for health care professionals to integrate AI into their practice, published in English or Spanish from 2018 onward. Studies that did not refer to specific skills or training in digital health were not included, discarding those that did not directly contribute to understanding the competencies necessary to integrate AI into health care practice. Bias in the examined works was evaluated following Cochrane's domain-based recommendations.
Results: The initial database search yielded a total of 2457 articles. After deleting duplicates and screening titles and abstracts, 37 articles were selected for full-text review. Out of these, only 7 met all the inclusion criteria for this systematic review. The review identified a diverse range of skills and competencies, that we categorized into 14 key areas classified based on their frequency of appearance in the selected studies, including AI fundamentals, data analytics and management, and ethical considerations.
Conclusions: Despite the broadening of search criteria to capture the evolving nature of AI in health care, the review underscores a significant gap in focused studies on the required competencies. Moreover, the review highlights the critical role of regulatory bodies such as the US Food and Drug Administration in facilitating the adoption of AI technologies by establishing trust and standardizing algorithms. Key areas were identified for developing competencies among health care professionals for the implementation of AI, including: AI fundamentals knowledge (more focused on assessing the accuracy, reliability, and validity of AI algorithms than on more technical abilities such as programming or mathematics), data analysis skills (including data acquisition, cleaning, visualization, management, and governance), and ethical and legal considerations. In an AI-enhanced health care landscape, the ability to humanize patient care through effective communication is paramount. This balance ensures that while AI streamlines tasks and potentially increases patient interaction time, health care professionals maintain a focus on compassionate care, thereby leveraging AI to enhance, rather than detract from, the patient experience. .
背景:技术进步极大地重塑了医疗保健,引入了加强诊断和患者护理的数字解决方案。人工智能(AI)脱颖而出,在数据分析、诊断支持和个性化医疗方面提供了前所未有的能力。然而,有效地将人工智能整合到医疗保健中需要专业人员的专业能力,就综合文献和正式培训计划而言,这一领域仍处于起步阶段。目的:根据已发表的文献,本系统综述旨在巩固卫生保健专业人员将人工智能有效融入临床实践所需的基本技能和知识。方法:我们在PubMed、Scopus和Web of Science数据库中对同行评审的文献进行了系统回顾,这些文献直接探讨了医疗保健专业人员将人工智能整合到他们的实践中所需的技能,这些文献自2018年以来以英语或西班牙语发表。未涉及数字卫生具体技能或培训的研究未被纳入,丢弃了那些不能直接有助于理解将人工智能纳入卫生保健实践所需能力的研究。根据Cochrane基于领域的建议评估被检查作品的偏倚。结果:初始数据库检索共获得2457篇文章。在删除重复、筛选标题和摘要后,选择了37篇文章进行全文审查。其中,只有7例符合本系统评价的所有纳入标准。审查确定了各种各样的技能和能力,我们根据其在选定研究中的出现频率将其分为14个关键领域,包括人工智能基础、数据分析和管理以及道德考虑。结论:尽管扩大了搜索标准以捕捉医疗保健中人工智能的不断发展的性质,但该综述强调了在必要能力的重点研究方面存在重大差距。此外,该审查强调了美国食品和药物管理局(fda)等监管机构在通过建立信任和标准化算法促进人工智能技术采用方面的关键作用。确定了在医疗保健专业人员中培养实施人工智能的能力的关键领域,包括:人工智能基础知识(更侧重于评估人工智能算法的准确性、可靠性和有效性,而不是编程或数学等更多技术能力)、数据分析技能(包括数据采集、清洁、可视化、管理和治理)以及道德和法律考虑。在人工智能增强的医疗保健领域,通过有效沟通使患者护理人性化的能力至关重要。这种平衡确保了在人工智能简化任务并可能增加患者互动时间的同时,医疗保健专业人员仍然专注于富有同情心的护理,从而利用人工智能来增强而不是减损患者的体验。