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人工智能融入护理流程:基于NANDA、NOC和NIC的护理计划比较分析

The Integration of AI into the Nursing Process: A Comparative Analysis of NANDA, NOC, and NIC-Based Care Plans.

作者信息

Gilart Ester, Bocchino Anna, Gilart-Cantizano Patricia, Cotobal-Calvo Eva Manuela, Lepiani-Diaz Isabel, Román-Sánchez Daniel, Palazón-Fernández José Luis

机构信息

Department of Nursing and Physiotherapy, University of Cádiz, 11009 Cádiz, Spain.

Nursing Faculty "Salus Infirmorum", University of Cádiz, Calle Ancha 29, 11001 Cádiz, Spain.

出版信息

Nurs Rep. 2025 May 27;15(6):186. doi: 10.3390/nursrep15060186.

Abstract

: Nursing diagnosis is a complex process that requires clinical judgment, time, and resources and whose implementation is hindered by factors such as workload, lack of time, and resistance to computerized systems. This study aimed to compare the quality and efficiency of care plans generated by nursing professionals versus those produced by an artificial intelligence (AI) model, using the NANDA, NOC, and NIC taxonomies as criteria. : An observational study was carried out with three simulated clinical cases. Thirty experts, fifty-four nursing professionals, and the ChatGPT model (GPT-4) were included. The experts established the referral plans using the Delphi technique. Responses were evaluated with a validated rubric (EADE-2) and analyzed using nonparametric tests. Professionals' perceptions on the use of computer systems were also collected. : ChatGPT scored significantly higher on several dimensions ( < 0.001) and resolved all three cases in 35 s, compared to an average of 30 min for practitioners. Professionals expressed dissatisfaction with current diagnostic documentation systems. : AI demonstrates high potential in optimizing the diagnostic process in nursing, although for its implementation human supervision, ethical aspects and improvements in current systems must be considered to achieve effective integration.

摘要

护理诊断是一个复杂的过程,需要临床判断、时间和资源,其实施受到工作量、时间不足以及对计算机系统的抵触等因素的阻碍。本研究旨在以北美护理诊断协会(NANDA)、护理结局分类(NOC)和护理干预分类(NIC)分类法为标准,比较护理专业人员生成的护理计划与人工智能(AI)模型生成的护理计划的质量和效率。

开展了一项针对三个模拟临床病例的观察性研究。纳入了30名专家、54名护理专业人员和ChatGPT模型(GPT - 4)。专家们使用德尔菲技术制定转诊计划。用经过验证的评分标准(EADE - 2)对回答进行评估,并使用非参数检验进行分析。还收集了专业人员对使用计算机系统的看法。

ChatGPT在几个维度上得分显著更高(<0.001),并在35秒内解决了所有三个病例,而从业者平均需要30分钟。专业人员对当前的诊断记录系统表示不满。

人工智能在优化护理诊断过程方面显示出巨大潜力,不过为了实现有效整合,在其实施过程中必须考虑人工监督、伦理方面以及对当前系统的改进。

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