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糖尿病管理应用程序的连续使用对真实临床实践中血糖控制的影响:回顾性分析。

The Effects of Continuous Usage of a Diabetes Management App on Glycemic Control in Real-world Clinical Practice: Retrospective Analysis.

机构信息

H2 Inc, Taipei, Taiwan.

School of Public Health, Taipei Medical University, Taipei, Taiwan.

出版信息

J Med Internet Res. 2021 Jul 15;23(7):e23227. doi: 10.2196/23227.

DOI:10.2196/23227
PMID:34264192
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8323018/
Abstract

BACKGROUND

The efficacy of digital technology in improving diabetes management has typically been demonstrated through studies such as randomized controlled trials, which have reported a steeper reduction in hemoglobin A (HbA) values for patients who adopted a digital solution. However, evidence from real-world clinical practice is still limited.

OBJECTIVE

This study aimed to evaluate the effectiveness of digital interventions by tracking HbA improvements over 1 year in real-world clinical settings.

METHODS

Patients used the Health2Sync mobile app to track self-measured outcomes and communicate with health care professionals (HCPs). HCPs used the web-based Patient Management Platform to monitor patient data, view test results from clinical laboratories, and communicate with patients. Patients who have been onboarded for at least 13 months and have consecutive HbA findings for 5 quarters were included in the analysis. They were then stratified into 3 groups (high, mid, and low retention) based on their level of use of Health2Sync in the first 6 months of onboarding. A mixed model was built to compare the slopes of the rate of reduction in HbA among the groups. In addition, these patients' retention on the app from the seventh to the 12th month was verified through multiple comparisons.

RESULTS

A sample of 2036 users was included in the analysis. With the mixed model coefficient estimates, we found that app users had significant HbA percentage reductions as the passed quarter count increased (t=-9.869; P<.001), and that effectiveness increased in the high (t=-5.173) and mid retention (t=-6.620) groups as the interaction effects were significantly negative compared to that in the low retention group (P<.001) in the passed quarter count. The low retention group also had the highest average HbA value at the end of 13 months (high: 7.01%, SD 1.02%; mid: 6.99%, SD 1.00%; low: 7.17%, SD 1.14%) (Bonferroni correction: high vs low, P=.07; mid vs low, P=.02; high vs mid, P>.99). The level of use of the app remained consistent in the seventh to the 12th month after onboarding (high: 5.23 [SD 1.37] months, mid: 2.43 [SD 1.68] months, low: 0.41 [SD 0.97] months) (P<.001).

CONCLUSIONS

Our analysis shows that continuous usage of the diabetes management app is associated with better glycemic control in real-world clinical practice. Further studies are required to reveal the efficacy for specific diabetes types and to observe effects beyond 1 year.

摘要

背景

数字技术在改善糖尿病管理方面的疗效通常通过随机对照试验等研究得到证明,这些研究报告称,采用数字解决方案的患者的血红蛋白 A(HbA)值降低幅度更大。然而,来自真实临床实践的证据仍然有限。

目的

本研究旨在通过在真实临床环境中跟踪 HbA 在 1 年内的改善情况来评估数字干预措施的有效性。

方法

患者使用 Health2Sync 移动应用程序来跟踪自我测量的结果并与医疗保健专业人员(HCP)进行沟通。HCP 使用基于网络的患者管理平台来监测患者数据、查看临床实验室的测试结果并与患者进行沟通。纳入分析的患者已入组至少 13 个月,并且在 5 个季度中有连续的 HbA 结果。然后,根据他们在入组后前 6 个月使用 Health2Sync 的程度,将他们分为 3 组(高、中、低保留)。建立混合模型以比较各组中 HbA 降低率的斜率。此外,通过多次比较验证了这些患者从第 7 个月到第 12 个月在应用程序上的保留情况。

结果

共纳入 2036 名用户进行分析。通过混合模型系数估计,我们发现随着通过的季度计数增加,应用程序用户的 HbA 百分比显著降低(t=-9.869;P<.001),并且在高(t=-5.173)和中(t=-6.620)保留组中,由于交互效应显著为负,与低保留组相比(P<.001),在通过的季度计数方面效果增加。低保留组在 13 个月结束时的平均 HbA 值也最高(高:7.01%,SD 1.02%;中:6.99%,SD 1.00%;低:7.17%,SD 1.14%)(Bonferroni 校正:高与低,P=.07;中与低,P=.02;高与中,P>.99)。在入组后的第 7 至 12 个月,应用程序的使用水平保持一致(高:5.23 [SD 1.37] 个月,中:2.43 [SD 1.68] 个月,低:0.41 [SD 0.97] 个月)(P<.001)。

结论

我们的分析表明,在真实临床实践中,持续使用糖尿病管理应用程序与更好的血糖控制相关。需要进一步的研究来揭示特定糖尿病类型的疗效,并观察 1 年以上的效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/611f33aa0c8f/jmir_v23i7e23227_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/b1a66eb0360e/jmir_v23i7e23227_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/9f542d574783/jmir_v23i7e23227_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/163cd8cb720d/jmir_v23i7e23227_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/b4c451da4bcd/jmir_v23i7e23227_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/c514dd5989d9/jmir_v23i7e23227_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/611f33aa0c8f/jmir_v23i7e23227_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/b1a66eb0360e/jmir_v23i7e23227_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/9f542d574783/jmir_v23i7e23227_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/163cd8cb720d/jmir_v23i7e23227_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/b4c451da4bcd/jmir_v23i7e23227_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/c514dd5989d9/jmir_v23i7e23227_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8f/8323018/611f33aa0c8f/jmir_v23i7e23227_fig6.jpg

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