人工智能在卫生行业监管中的应用——三个司法管辖区护士监管机构的定性探索

IF 4.2 4区 医学 Q1 NURSING
Anna van der Gaag MSc, PhD, Robert Jago BA, MPhil (Cantab), Ann Gallagher SRN, MRN, BA, MA, PhD, Kostas Stathis PhD, Michelle Webster BA, MSc, PhD, Zubin Austin BScPhm, MBA, MISc, PhD, FCAHS
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引用次数: 0

摘要

人工智能(AI)是指在日常生活中越来越普遍的一组广泛的技术;然而,它们在监管实践中的应用有限。目的本研究探讨护理监管机构对人工智能在监管中的作用和价值的看法,以及人工智能吸收和实施的潜在障碍和促进因素。方法与来自澳大利亚、英国和美国的28名监管机构代表进行了三次便利的焦点小组会议。完成了逐字抄本的内容分析。出现的关键主题包括(a)对人工智能如何增强可持续性和提高某些监管流程的成本效益的兴趣,以及(b)对“人工智能”一词本身可能存在问题的担忧。在监管中采用人工智能的具体障碍包括对系统偏见的编纂、负面的公众看法以及对决策问责制缺乏明确性的担忧。促进实施的因素包括加强流程的一致性,改进决策和在支持趋势分析和审计职能方面的效用。在探索如何最好地将不断发展的人工智能技术纳入监管实践以及它们应该被命名方面,还需要做更多的工作,但这些发现表明,有希望的结果可能就在前面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence in Health Professions Regulation: An Exploratory Qualitative Study of Nurse Regulators in Three Jurisdictions

Background

Artificial intelligence (AI) refers to a broad group of technologies that are increasingly commonplace in everyday life; however, they have had only limited application in regulatory practice.

Purpose

The present study explored nursing regulators’ perceptions of the role and value of AI in regulation and potential barriers and facilitators to the uptake and implementation of AI.

Methods

Three facilitated focus group sessions with 28 representatives of regulators from Australia, the United Kingdom, and the United States were conducted. Content analysis of verbatim transcripts was completed.

Results

Key themes that emerged included (a) interest in how AI could enhance sustainability and improve cost-effectiveness of certain regulatory processes and (b) concerns regarding how the term “artificial intelligence” itself could be problematic. Specific barriers to the uptake of AI in regulation included concerns regarding codification of system bias, negative public perception, and lack of clarity around accountability for decision-making. Facilitators to implementation included enhancing the consistency of processes and improving the decision-making and utility in supporting trend analyses and audit functions.

Conclusion

Additional work in exploring how best to incorporate evolving AI technologies in regulatory practice—and what they should be named—is required, but these findings suggest that promising outcomes may lie ahead.

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来源期刊
CiteScore
4.60
自引率
12.50%
发文量
50
审稿时长
54 days
期刊介绍: Journal of Nursing Regulation (JNR), the official journal of the National Council of State Boards of Nursing (NCSBN®), is a quarterly, peer-reviewed, academic and professional journal. It publishes scholarly articles that advance the science of nursing regulation, promote the mission and vision of NCSBN, and enhance communication and collaboration among nurse regulators, educators, practitioners, and the scientific community. The journal supports evidence-based regulation, addresses issues related to patient safety, and highlights current nursing regulatory issues, programs, and projects in both the United States and the international community. In publishing JNR, NCSBN''s goal is to develop and share knowledge related to nursing and other healthcare regulation across continents and to promote a greater awareness of regulatory issues among all nurses.
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