Application of intelligent nursing system based on big data in maintenance hemodialysis patients

IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS
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Abstract

Maintenance hemodialysis (MHD) is one of the most important renal replacement therapies for patients with end-stage renal disease. However, long-term and frequent treatment not only damages the physiological functions of patients but also leads to serious economic burdens and mental stress. This can easily cause a series of psychological disorders in patients, resulting in severe rejection and fear of MHD. To reduce patient resistance and improve the quality of life of MHD, this article built an intelligent nursing system based on big data and then used the constructed intelligent nursing system to research MHD. Through experiments, it has been found that compared to self-efficacy intervention, intelligent nursing systems can control the concurrent rate of MHD patients below 14 %, and self-efficacy intervention methods can control the concurrent rate of MHD patients above 13 %. Moreover, using intelligent nursing systems can improve the ability of MHD patients to self-care. At the same time, before the use of intelligent nursing systems, the nursing satisfaction of MHD patients also varied greatly, with the overall satisfaction rate after use being 70 % higher than before. Using intelligent nursing systems can improve the satisfaction of MHD patients with nursing outcomes.

基于大数据的智能护理系统在血液透析患者维护中的应用。
维持性血液透析(MHD)是终末期肾病患者最重要的肾脏替代疗法之一。然而,长期频繁的治疗不仅会损害患者的生理功能,还会造成严重的经济负担和精神压力。这很容易使患者产生一系列心理障碍,从而对 MHD 产生严重的排斥和恐惧心理。为了减少患者的抵触情绪,提高 MHD 的生活质量,本文构建了基于大数据的智能护理系统,然后利用构建的智能护理系统对 MHD 进行研究。通过实验发现,与自我效能干预相比,智能护理系统可以将MHD患者的并发率控制在14%以下,自我效能干预方法可以将MHD患者的并发率控制在13%以上。此外,使用智能护理系统可以提高 MHD 患者的自我护理能力。同时,在使用智能护理系统前,MHD 患者的护理满意度也存在较大差异,使用后的总体满意度比使用前提高了 70%。使用智能护理系统可以提高 MHD 患者对护理效果的满意度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
SLAS Technology
SLAS Technology Computer Science-Computer Science Applications
CiteScore
6.30
自引率
7.40%
发文量
47
审稿时长
106 days
期刊介绍: SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.
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