Email Alert | RSS    帮助

中国防痨杂志 ›› 2025, Vol. 47 ›› Issue (11): 1433-1441.doi: 10.19982/j.issn.1000-6621.20250227

• 论著 • 上一篇    下一篇

移动医疗技术在结核病患者健康管理中应用效果的Meta分析

高丹1, 姚丽伟2(), 黄金鹏1, 刘晓霞2, 张玥1, 凌琳1   

  1. 1杭州市红十字会医院结核病诊疗中心,杭州 310003
    2杭州市红十字会医院护理部,杭州 310003
  • 收稿日期:2025-05-27 出版日期:2025-11-10 发布日期:2025-10-30
  • 通信作者: 姚丽伟 E-mail:2557228490@qq.com
  • 基金资助:
    浙江省中医药管理局(2025ZL443);浙江省卫生健康委员会(2025KY1123)

Application effect of mobile medical technology in health management of tuberculosis patients: A Meta-analysis

Gao Dan1, Yao Liwei2(), Huang Jinpeng1, Liu Xiaoxia2, Zhang Yue1, Ling Lin1   

  1. 1Tuberculosis Treatment Center,Hangzhou Red Cross Hospital, Hangzhou 310003, China
    2Department of Nursing,Hangzhou Red Cross Hospital, Hangzhou 310003, China
  • Received:2025-05-27 Online:2025-11-10 Published:2025-10-30
  • Contact: Yao Liwei E-mail:2557228490@qq.com
  • Supported by:
    Administration of Traditional Chinese Medicine of Zhejiang Province(2025ZL443);Zhejiang Provincial Health Commission(2025KY1123)

摘要:

目的: 系统评价移动医疗技术在结核病患者健康管理中的应用效果,为临床实践提供参考依据。方法: 计算机系统检索Web of Science、Embase、Cochrane Library、PubMed、CINAHL、中国生物医学文献数据库、中国知网、万方数据库、维普数据库中收录的基于移动医疗技术在结核病患者健康管理中应用效果的随机对照试验。检索时限为建库至2025年5月30日。由2名研究者独立进行文献筛选、数据提取及质量评价,采用RevMan 5.4及Stata 16.0软件进行Meta分析。结果: 共纳入10篇文献,5615例患者。Meta分析结果显示,使用移动医疗技术对结核病患者进行健康管理后,观察组治疗依从率(RR=1.20,95%CI:1.12~1.29,P<0.001)、治疗成功率(RR=1.09,95%CI:1.03~1.16,P=0.006)、痰检率(RR=1.14,95%CI:1.06~1.22,P<0.001)均高于对照组,差异均有统计学意义;两组不良结局发生率比较,观察组低于对照组,差异有统计学意义(RR=0.75,95%CI:0.59~0.96,P=0.020)。亚组分析显示,与信息提醒及电子药盒比较,采用微信程序(RR=1.28,95%CI:1.17~1.40,P<0.001)及手机视频(RR=1.29,95%CI:1.13~1.46,P<0.001)干预形式的患者治疗依从率均较高,差异均有统计学意义;与医院-社区、医院-家庭干预模式比较,采用医院-社区-家庭干预模式的患者治疗依从率高,差异有统计学意义(RR=1.24,95%CI:1.16~1.33,P<0.001);与干预时长≤3个月比较,干预时长>3个月的患者治疗依从率高,差异有统计学意义(RR=1.23,95%CI:1.19~1.27,P<0.001)。结论: 实施移动医疗技术能提升结核病患者治疗依从率、治疗成功率、痰检率,降低不良结局发生率。可运用微信小程序及手机视频等实时互动强的移动医疗技术、采用医院-社区-家庭联动模式、延长干预时间、根据移动医疗技术使用影响因素进行干预方案构建,进一步提升干预效果。

关键词: 结核, 计算机通信网络, Meta分析, 护理

Abstract:

Objective: To systematically evaluate the application effect of mobile medical technology in tuberculosis patient health management, to provide reference for clinical practice. Methods: A systematic search of Web of Science, Embase, Cochrane Library, PubMed, CINAHL, CBM, CNKI, WanFang Data and VIP database was conducted for randomised controlled trials about mobile medical technology’s usage on tuberculosis patient health management. The retrieval time limit was from database establishment to May 30, 2025. Two researchers independently screened literature,extracted data and evaluated quality. Meta-analysis was performed using RevMan 5.4 and Stata 16.0 software. Results: A total of 10 articles and 5615 patients were included. Meta-analysis showed that after applying mobile medical technology for the health management of tuberculosis patients, treatment compliance rate (RR=1.20,95%CI:1.12-1.29,P<0.001), treatment success rate (RR=1.09,95%CI:1.03-1.16,P=0.006), and sputum examination rate (RR=1.14,95%CI:1.06-1.22,P<0.001) of the observation group were all statistically significantly higher than those of the conventional group. Adverse outcomes occurrence in the observation group was significantly lower than that of the conventional group (RR=0.75,95%CI:0.59-0.96,P=0.020). Subgroup analysis showed that compared with information reminders and electronic pill boxes, patients who received intervention through WeChat program (RR=1.28,95%CI:1.17-1.40, P<0.001) and mobile face-to-face video (RR=1.29,95%CI:1.13-1.46,P<0.001) had significantly higher treatment compliance rates; compared with hospital-community and hospital-family intervention models, patients took hospital-community-family intervention model had significantly higher treatment compliance rate (RR=1.24,95%CI:1.16-1.33,P<0.001); compared with an ≤3 months intervention, patients getting intervention >3 months had significantly higher treatment compliance rate (RR=1.23,95%CI:1.19-1.27,P<0.001). Conclusion: The implementation of mobile medical technology can improve treatment compliance rate, treatment success rate and sputum examination rate of tuberculosis patients, and reduce incidence of adverse outcomes. Mobile medical technology with strong real-time interaction such as WeChat and mobile video can be used, together with adopting hospital-community-family linkage mode, extending intervention time, constructing intervention plan according to factors influencing usage of mobile medical technology, to further improve the intervention effect.

Key words: Tuberculosis, Computer communication networks, Mate-analysis, Nursing care

中图分类号: