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使用基于智能手机的药物依从性平台改善退伍军人2型糖尿病控制不佳的结局:前瞻性病例交叉研究。

Use of a Smartphone-Based Medication Adherence Platform to Improve Outcomes in Uncontrolled Type 2 Diabetes Among Veterans: Prospective Case-Crossover Study.

作者信息

Rai Amneet, Riddle Mark, Mishra Rajendra, Nguyen Nhien, Valine Kelly, Fenney Megan

机构信息

Veterans Affairs Sierra Nevada Healthcare System, Reno, NV, United States.

University of Nevada Reno School of Medicine, Reno, NV, United States.

出版信息

JMIR Diabetes. 2023 Aug 10;8:e44297. doi: 10.2196/44297.

Abstract

BACKGROUND

Medication nonadherence is a problem that impacts both the patient and the health system.

OBJECTIVE

The objective of this study was to evaluate the impact of a novel smartphone app with patient-response-directed clinical intervention on medication adherence and blood glucose control in noninsulin-dependent patients with type 2 diabetes mellitus (T2DM).

METHODS

We enrolled 50 participants with T2DM not on insulin with smartphones from a rural health care center in Northern Nevada for participation in this case-crossover study. Participants underwent a standard of care arm and an intervention arm. Each study arm was 3 months long, for a total of 6 months of follow-up. Participants had a hemoglobin A (HbA) lab draw at enrollment, 3 months, and 6 months. Participants had monthly "medication adherence scores" (MAS) and "Self-Efficacy for Appropriate Medication Use Scale" (SEAMS) questionnaires completed at baseline and monthly for the duration of the study. Our primary outcomes of interest were the changes in HbA between study arms. Secondary outcomes included the evaluation of the difference in the proportion of participants achieving a clinically meaningful reduction in HbA and the difference in the number of participants requiring diabetes therapy escalation between study arms. Exploratory outcomes included the analysis of the variation in medication possession ratio (MPR), MAS, and SEAMS during each study arm.

RESULTS

A total of 30 participants completed both study arms and were included in the analysis. Dropouts were higher in participants enrolled in the standard of care arm first (9/25, 36% vs 4/25, 16%). Participants had a median HbA of 9.1%, had been living with T2DM for 6 years, had a median age of 66 years, and had a median of 8.5 medications. HbA reduction was 0.69% in the intervention arm versus 0.35% in the standard of care arm (P=.30). A total of 70% (21/30) of participants achieved a clinically meaningful reduction in HbA of 0.5% in the app intervention arm versus 40% (12/30) in the standard of care arm (odds ratio 2.29, 95% CI 0.94-5.6; P=.09). Participants had higher odds of a therapy escalation while in the standard of care arm (18/30, 60% vs 5/30, 16.7%, odds ratio 4.3, 95% CI 1.2-15.2; P=.02). The median MPR prior to enrollment was 109%, 112% during the study's intervention arm, and 102% during the standard of care arm. The median real-time MAS was 93.2%. The change in MAS (1 vs -0.1; P=.02) and SEAMS (1.9 vs -0.2; P<.001) from baseline to month 3 was higher in the intervention arm compared to standard of care.

CONCLUSIONS

A novel smartphone app with patient-response-directed provider intervention holds promise in the ability to improve blood glucose control in complex non-insulin-dependent T2DM and is worthy of additional study.

摘要

背景

药物治疗依从性不佳是一个影响患者和医疗系统的问题。

目的

本研究的目的是评估一款新型智能手机应用程序(具有针对患者反应的临床干预功能)对非胰岛素依赖型2型糖尿病(T2DM)患者的药物治疗依从性和血糖控制的影响。

方法

我们从内华达州北部的一个农村医疗中心招募了50名未使用胰岛素治疗的T2DM患者,他们均配备智能手机,参与这项病例交叉研究。参与者经历了标准治疗组和干预组。每个研究组为期3个月,总共随访6个月。参与者在入组时、3个月和6个月时进行血红蛋白A(HbA)实验室检测。参与者在基线时以及研究期间每月完成“药物治疗依从性评分”(MAS)和“合理用药自我效能量表”(SEAMS)问卷。我们感兴趣的主要结局是研究组之间HbA的变化。次要结局包括评估达到HbA临床有意义降低的参与者比例差异以及研究组之间需要升级糖尿病治疗的参与者数量差异。探索性结局包括分析每个研究组期间药物持有率(MPR)、MAS和SEAMS的变化。

结果

共有30名参与者完成了两个研究组并纳入分析。首先进入标准治疗组的参与者中退出率更高(9/25,36% 对 4/25,16%)。参与者的HbA中位数为9.1%,患T2DM已6年,年龄中位数为66岁,服用药物中位数为8.5种。干预组的HbA降低了0.69%,而标准治疗组为0.35%(P = 0.30)。在应用程序干预组中,共有70%(21/30)的参与者HbA实现了0.5%的临床有意义降低,而标准治疗组为40%(12/30)(优势比2.29,95%置信区间0.94 - 5.6;P = 0.09)。在标准治疗组期间,参与者升级治疗的几率更高(18/30,60% 对 5/30,16.7%,优势比4.3,95%置信区间1.2 - 15.2;P = 0.02)。入组前MPR中位数为109%,研究干预组期间为112%,标准治疗组期间为102%。实时MAS中位数为93.2%。与标准治疗组相比,干预组从基线到第3个月的MAS变化(1对 -0.1;P = 0.02)和SEAMS变化(1.9对 -0.2;P < .001)更大。

结论

一款具有针对患者反应的医疗服务提供者干预功能的新型智能手机应用程序有望改善复杂的非胰岛素依赖型T2DM患者的血糖控制,值得进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0a5/10450533/77c1fc6dbf87/diabetes_v8i1e44297_fig1.jpg

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