人工智能辅助远程医疗护理:范围审查。

IF 3.5 3区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Journal of Telemedicine and Telecare Pub Date : 2025-01-01 Epub Date: 2023-04-18 DOI:10.1177/1357633X231167613
Jeeyae Choi, Seoyoon Woo, Anastasiya Ferrell
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引用次数: 0

摘要

背景:由于COVID-19大流行,远程医疗作为一种方便高效的医疗服务方式重新浮出水面。研究人员指出,人工智能(AI)可以进一步促进在远程医疗中提供高质量的护理。必须找到支持性证据,以便在护理中使用人工智能辅助的远程医疗干预措施。目的:本范围审查侧重于发现用户对人工智能辅助远程医疗干预的满意度和感知,人工智能算法的性能以及所使用的人工智能技术类型。方法:在PubMed、CINAHL、Web of Science、OVID、PsycINFO和ProQuest 6个数据库中进行结构化检索,按照系统评价的首选报告项目和范围评价的元分析扩展的指导。使用医学教育研究研究质量工具评估最终审查研究的质量。结果:2017年至2022年间发表的41项研究中有8项被纳入最终评审。在美国进行了六项研究,一项在日本,一项在韩国。四项研究收集了参与者的数据(n = 3014)。两项研究使用图像数据(n = 1986),两项研究使用智能家居传感器数据为护士检测患者健康事件(n = 35)。研究质量为中等至高质量研究(平均值= 10.1,范围= 7.7-13.7)。两项研究报告了较高的用户满意度,三项研究评估了用户对远程医疗中人工智能的看法,只有一项研究表明人工智能的可接受性很高。两项研究揭示了人工智能算法的高性能。五项研究使用了机器学习算法。结论:人工智能辅助远程医疗干预是一种高效且有前景的护理方式。
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 assisted telehealth for nursing: A scoping review.

Background: Due to the COVID-19 pandemic, telehealth resurfaced as a convenient efficient healthcare delivery method. Researchers indicate that Artificial Intelligence (AI) could further facilitate delivering quality care in telehealth. It is essential to find supporting evidence to use AI-assisted telehealth interventions in nursing.

Objectives: This scoping review focuses on finding users' satisfaction and perception of AI-assisted telehealth intervention, performances of AI algorithms, and the types of AI technology used.

Methods: A structured search was performed in six databases, PubMed, CINAHL, Web of Science, OVID, PsycINFO, and ProQuest, following the guidance of the Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Reviews. The quality of the final reviewed studies was assessed using the Medical Education Research Study Quality Instrument.

Results: Eight of the 41 studies published between 2017 and 2022 were included in the final review. Six studies were conducted in the United States, one in Japan, and one in South Korea. Four studies collected data from participants (n = 3014). Two studies used image data (n = 1986), and two used sensor data from smart homes to detect patients' health events for nurses (n = 35). The quality of studies implied moderate to high-quality study (mean = 10.1, range = 7.7-13.7). Two studies reported high user satisfaction, three assessed user perception of AI in telehealth, and only one showed high AI acceptability. Two studies revealed the high performance of AI algorithms. Five studies used machine learning algorithms.

Conclusions: AI-assisted telehealth interventions were efficient and promising and could be an effective care delivery method in nursing.

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来源期刊
CiteScore
14.10
自引率
10.60%
发文量
174
审稿时长
6-12 weeks
期刊介绍: Journal of Telemedicine and Telecare provides excellent peer reviewed coverage of developments in telemedicine and e-health and is now widely recognised as the leading journal in its field. Contributions from around the world provide a unique perspective on how different countries and health systems are using new technology in health care. Sections within the journal include technology updates, editorials, original articles, research tutorials, educational material, review articles and reports from various telemedicine organisations. A subscription to this journal will help you to stay up-to-date in this fast moving and growing area of medicine.
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