健康管理干预控制老年高脂血症等慢性病的临床观察与评价。

IF 3.7 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology Pub Date : 2025-06-19 DOI:10.1016/j.slast.2025.100318

Hongxia Liu

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引用次数: 0

摘要

饮食不规律、缺乏锻炼和睡眠质量差导致了各种疾病，高脂血症等慢性疾病在老年人中最常见。随着医疗物联网（MIoT）的发展，医疗数据现在支持更有效的护理策略。健康管理干预作为一种新的干预手段，旨在提高老年患者对慢性疾病的认识和管理。本研究将200例老年高脂血症患者随机分为对照组（常规护理）和实验组（健康管理干预）。结果显示，干预后健康知识掌握水平显著提高，男性从61.8%提高到74.4%，女性从56.8%提高到71.6%。因此，基于医疗数据的健康管理干预有效地提高了患者的健康素养。

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Clinical observation and evaluation of health management intervention in controlling senile chronic diseases such as hyperlipidemia

Irregular diet, lack of exercise, and poor sleep quality have led to various diseases, with chronic conditions like hyperlipidemia being most common among the elderly. With advances in the medical Internet of Things (MIoT), medical data now supports more effective care strategies. Health management intervention, as a novel approach, aims to improve elderly patients’ understanding and management of chronic diseases. In this study, 200 elderly patients with hyperlipidemia were randomly divided into a control group (routine care) and an experimental group (health management intervention). Results showed that health knowledge mastery improved significantly with intervention—rising from 61.8 % to 74.4 % in males and from 56.8 % to 71.6 % in females. Thus, health management intervention based on medical data effectively enhances patients’ health literacy.

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来源期刊

SLAS Technology Computer Science-Computer Science Applications

CiteScore

6.30

自引率

7.40%

发文量

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.