主管:国家卫生健康委员会
主办:国家卫生健康委医院管理研究所
中国科技核心期刊(中国科技论文统计源期刊)
中国科学引文数据库(CSCD)核心库期刊
《中文核心期刊要目总览》核心期刊

中国护理管理 ›› 2024, Vol. 24 ›› Issue (9): 1292-1298.doi: 10.3969/j.issn.1672-1756.2024.09.003

• 特别策划·中医专科护理发展 • 上一篇    下一篇

老年慢性病患者居家中医护理技术需求预测

张晓兰 徐妍 叶梦华 姚斌莲 徐敏   

  1. 浙江中医药大学附属第一医院(浙江省中医院)护理部,310006 杭州市(张晓兰,姚斌莲);血液内科(叶梦华);副院长办公室(徐敏);浙江中医药大学护理学院(徐妍)
  • 出版日期:2024-09-15 发布日期:2024-09-15
  • 通讯作者: 徐敏,博士,主任护师,博士生导师,副院长,E-mail:yudi1212@163.com
  • 作者简介:张晓兰,硕士,副主任护师,硕士生导师,临床护理学教研室副主任
  • 基金资助:
    2023年度浙江省“尖兵”“领雁”研发攻关计划项目(2023C03165);浙江中医药大学重点研究项目(2022FSYYZZ06)

Prediction of home-based Traditional Chinese Medicine nursing technology demand of elderly patients with chronic diseases

ZHANG Xiaolan, XU Yan, YE Menghua, YAO Binlian, XU Min   

  1. Department of Nursing, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310006, China
  • Online:2024-09-15 Published:2024-09-15
  • Contact: E-mail:yudi1212@163.com

摘要: 目的:调查老年慢性病患者的居家中医护理技术需求现状并对其需求进行预测,为临床决策提供参考。方法:采用便利抽样法,于2024年2月—6月,使用自行编制的老年慢性病患者居家中医护理技术需求调查问卷对浙江省内9家中医医院门诊及住院的1?026例老年慢性病患者进行横断面调查。运用极端梯度提升算法对需求进行预测,并采用沙普利加性解释方法对模型中的变量重要性进行解释性分析。结果:老年慢性病患者居家中医护理技术的需求率为70.27%,其中刮痧(52.63%)、艾灸(51.85%)、拔罐(48.73%)、耳穴贴压(47.37%)的需求排名位居前列。综合重要性排序,老年慢性病患者对中医护理技术的认知及态度、具体不适症状、家庭人均月收入、文化程度等特征是较为重要的预测因子。模型在训练集中的AUC值为0.95~0.99,测试集中的AUC值为0.80~0.89,模型性能较好。结论:老年慢性病患者的居家中医护理技术需求广泛且受多种因素影响,未来应加强中医护理技术的推广与宣传,提高公众认知。同时加大人才培养力度,针对患者常见的不适症状,提供相应的中医护理技术支持,以满足老年慢性病患者的个性化需求。

关键词: 老年;慢性病;居家;中医护理技术;机器学习;预测模型

Abstract: Objective: To investigate the current situation of home-based Traditional Chinese Medicine (TCM) nursing technology needs of elderly patients with chronic diseases and to predict their needs, so as to provide reference for clinical decision-making. Methods: From February to June 2024, a cross-sectional survey was conducted on 1026 elderly patients with chronic diseases in outpatient and inpatient departments of 9 TCM hospitals in Zhejiang province by using the self-made questionnaire on the needs of home TCM nursing technology for elderly patients with chronic diseases. The extreme gradient lifting algorithm is used to predict the demand, and the importance of the variables in the model is explained by the Shapley Additive Explanations. Results: The demand rate of home-based TCM nursing technology for elderly patients with chronic diseases was 70.27%, of which scraping (52.63%), moxibustion (51.85%), cupping (48.73%), ear point sticking (47.37%) ranked in the forefront. Overall importance ranking, TCM nursing technology cognition and attitude, specific symptoms of discomfort, per capita monthly family income, education level and other characteristics were identified as significant predictors. The AUC value of the model in the training set is 0.95-0.99, and the AUC value in the test set is 0.80-0.89, and the performance of the model is good. Conclusion: The demand for home traditional TCM nursing technology in elderly patients with chronic diseases is extensive and affected by many factors. In the future, the promotion and publicity of TCM nursing technology should be strengthened to improve public awareness. At the same time, we will increase personnel training, provide corresponding TCM nursing technical support for common discomfort symptoms of patients, and meet the personalized needs of elderly patients with chronic diseases.

Key words: elderly; chronic disease; home-based; TCM nursing technology; machine learning; predicting model

中图分类号:  R47;R197