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Nursing Science 2025
智能医疗数据分析技术在外科术后护理中的应用效果评估
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Abstract:
目的:提升外科术后护理质量,以减少并发症并促进患者恢复。方法:结合大数据、物联网和机器学习技术,构建智能医疗物联网框架及智能术后护理系统,通过对比实验分析某三甲医院的医疗数据。结果:与传统术后护理方法相比,智能医疗数据分析技术在促进伤口愈合、提高护理处理量和降低错误率、改善睡眠质量和饮食状况等方面表现出显著效果,护理效率提升了6.9%,超越了同行研究中普遍的3%~5%的提升幅度。结论:智能医疗数据分析技术在外科术后护理中应用效果显著,能够有效提升护理质量与效率,为大数据时代下的术后护理模式创新提供了实践依据和发展建议。
Objective: To enhance the quality of postoperative surgical care, reduce complications, and promote patient recovery. Methods: A smart medical IoT framework and intelligent postoperative care system were constructed using big data, the Internet of Things (IoT), and machine learning technologies. Comparative experiments were conducted using medical data from a tertiary hospital. Results: Compared with traditional postoperative care methods, intelligent medical data analysis technology demonstrated significant effectiveness in promoting wound healing, increasing care throughput, reducing error rates, and improving sleep quality and dietary conditions. Care efficiency improved by 6.9%, surpassing the common improvement range of 3% - 5% reported in peer studies. Conclusion: The application of intelligent medical data analysis technology in postoperative surgical care has proven to be effective in significantly improving care quality and efficiency, providing practical evidence and development recommendations for innovation in postoperative care models in the era of big data.
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