人工智能：护理行业的挑战与机遇

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Artificial intelligence (AI) is a strategy to explain the techniques developed for teaching computers that are used to mimic human cognitive functions, including reasoning, communication, learning and decision-making. AI can be defined as the use of software and hardware systems designed by humans to achieve a complex goal in the physical or digital dimension by understanding their environment through the collection and interpretation of structured or unstructured data. Ultimately, this data serves to decide the best actions to achieve a given goal (Mobayen et al., 2022; Von Gerich et al., 2021). The history of AI in the nursing profession dates back four decades ago. The first case was related to the Medline base in 1985. AI offers ways to increase the efficiency of health care services and reduce costs. It is estimated that by 2025, the use of AI technologies could potentially save US$ 150 billion in healthcare costs (McGrow, 2019).

In recent years, evidence about AI in the nursing profession has developed increasingly, which indicates the popularity of AI in this profession. Today, health care systems offer several possibilities for the development of AI in the nursing profession. However, at commencement, the challenges facing the acceptance of AI in the nursing profession have raised concerns. These challenges discuss the importance of the need to develop new perspectives on technology acceptance and identify barriers to technology acceptance among nurses (Robert, 2019). Nurses, as specialists in occupational care, are potential users of AI-based technologies to guide and shape the evolution of AI. However, most nurses are ditched in the early stages of the analysis, design and development of AI (McGrow, 2019).

The introduction of AI-based technologies in the nursing profession has sparked challenges and public debate. It is feared that these technologies will replace human-to-human interaction and jeopardise care ethics. Other fundamental concerns regarding the ethical use of these technologies are the substitution of these technologies with nurses and the bias in data management. The lack of common understanding between specialists and vocabulary in the fields of nursing and technology has been raised as another challenge for nurses' participation in AI research (Stokes & Palmer, 2020). In addition, the lack of a comprehensive evaluation of the results including the quality of patient care, care burden, patient satisfaction, impact on nursing care, compliance with professional guidelines and economic aspects of using AI technologies that lead to an inadequate description of the connection between AI technologies and the nursing profession are another challenge (Von Gerich et al., 2021). Some of these challenges can be alleviated using the provision of adequate information about AI and by creating transparent discussions about AI in the nursing profession. It is obvious that the development and implementation of AI technologies in the nursing profession should be developed for easy and practical use. These technologies provide an opportunity for nurses to move away from their routine administrative tasks and focus their efforts on professional and patient-centred care. Hence, a key step is to identify areas where real applications of AI are presented to nurses (McGrow, 2019). Other opportunities include emphasising the development of guidelines for clinical nurses about the safe and appropriate acceptance of such innovations that require basic knowledge of the development and use of AI-based technologies, in-depth understanding of these technologies by nurses and their proper use can be effective in reducing the workload of nurses and improving the quality of nursing care (McGrow, 2019, Von Gerich et al., 2021).

Future research is needed to clarify the impact of AI-based technologies on the nursing profession, including how to implement and evaluate clinical outcomes to improve the quality of information collected. Nurses' attitudes and concerns about the adoption of AI technologies in clinical settings should also be considered. Managers and policymakers of the nursing profession, in order to implement nursing informatics and determine the competence of AI at all levels of nursing education, need more evidence to examine the professional role of nurses in the development and implementation of technologies based on AI.

全文翻译（仅供参考）

人工智能 (AI) 是一种策略，用于解释为教授计算机而开发的用于模仿人类认知功能的技术，包括推理、交流、学习和决策。人工智能可以定义为使用人类设计的软件和硬件系统，通过收集和解释结构化或非结构化数据来了解其环境，从而实现物理或数字维度的复杂目标。最终，这些数据用于决定实现给定目标的最佳行动（Mobayen 等人，  2022 年；Von Gerich 等人，  2021 年））。人工智能在护理行业的历史可以追溯到 40 年前。第一个案例与 1985 年的 Medline 基地有关。人工智能提供了提高医疗保健服务效率和降低成本的方法。据估计，到 2025 年，人工智能技术的使用可能会节省 1500 亿美元的医疗保健成本（McGrow，  2019 年）。

近年来，有关人工智能在护理行业的证据越来越多，这表明人工智能在该行业中的普及。今天，医疗保健系统为护理行业的人工智能发展提供了多种可能性。然而，在一开始，护理行业接受人工智能所面临的挑战引起了人们的关注。这些挑战讨论了需要开发关于技术接受的新观点的重要性，并确定护士接受技术的障碍（罗伯特，  2019 年）。护士作为职业护理专家，是基于人工智能的技术的潜在用户，可以指导和塑造人工智能的发展。然而，大多数护士在人工智能分析、设计和开发的早期阶段就被抛弃了（McGrow，  2019）。

在护理行业中引入基于人工智能的技术引发了挑战和公众辩论。人们担心这些技术将取代人与人之间的互动并危及护理伦理。关于这些技术的伦理使用的其他基本问题是护士替代这些技术以及数据管理中的偏见。护理和技术领域的专家和词汇缺乏共同理解已成为护士参与人工智能研究的另一个挑战（Stokes & Palmer,  2020）。此外，缺乏对结果的全面评估，包括患者护理质量、护理负担、患者满意度、对护理的影响、对专业指南的遵守情况以及使用人工智能技术的经济方面，导致对连接的描述不充分人工智能技术和护理专业之间是另一个挑战（Von Gerich et al.,  2021）。通过提供足够的人工智能信息和在护理专业中建立关于人工智能的透明讨论，可以缓解其中一些挑战。很明显，人工智能技术在护理行业的开发和实施应该是为了方便和实用而开发的。这些技术为护士提供了一个摆脱日常管理任务的机会，将精力集中在专业和以患者为中心的护理上。因此，一个关键步骤是确定向护士展示人工智能真正应用的领域（McGrow，  2019）。其他机会包括强调为临床护士制定关于安全和适当接受此类创新的指南，这些创新需要对基于人工智能的技术的开发和使用具有基本知识，护士对这些技术的深入了解及其正确使用可以有效减轻护士工作量，提高护理质量（McGrow,  2019 , Von Gerich et al.,  2021）。

未来的研究需要阐明基于人工智能的技术对护理专业的影响，包括如何实施和评估临床结果以提高所收集信息的质量。还应考虑护士对在临床环境中采用人工智能技术的态度和担忧。护理专业的管理者和决策者，为了实施护理信息学并确定人工智能在各级护理教育中的能力，需要更多的证据来检验护士在基于人工智能的技术的开发和实施中的专业作用。