The Effect of a WeChat-Based Tertiary A-Level Hospital Intervention on Medication Adherence and Risk Factor Control in Patients With Stable Coronary Artery Disease: Multicenter Prospective Study

Boqun Shi, Xi Liu, Qiuting Dong, Yuxiu Yang, Zhongxing Cai, Haoyu Wang, Dong Yin, Hongjian Wang, Kefei Dou, Weihua Song, Boqun Shi, Xi Liu, Qiuting Dong, Yuxiu Yang, Zhongxing Cai, Haoyu Wang, Dong Yin, Hongjian Wang, Kefei Dou, Weihua Song

Abstract

Background: In China, ischemic heart disease is the main cause of mortality. Having cardiac rehabilitation and a secondary prevention program in place is a class IA recommendation for individuals with coronary artery disease. WeChat-based interventions seem to be feasible and efficient for the follow-up and management of chronic diseases.

Objective: This study aims to evaluate the effectiveness of a tertiary A-level hospital, WeChat-based telemedicine intervention in comparison with conventional community hospital follow-up on medication adherence and risk factor control in individuals with stable coronary artery disease.

Methods: In this multicenter prospective study, 1424 patients with stable coronary artery disease in Beijing, China, were consecutively enrolled between September 2018 and September 2019 from the Fuwai Hospital and 4 community hospitals. At 1-, 3-, 6-, and 12-month follow-up, participants received healthy lifestyle recommendations and medication advice. Subsequently, the control group attended an offline outpatient clinic at 4 separate community hospitals. The intervention group had follow-up visits through WeChat-based telemedicine management. The main end point was medication adherence, which was defined as participant compliance in taking all 4 cardioprotective medications that would improve the patient's outcome (therapies included antiplatelet therapy, β-blockers, statins, and angiotensin-converting-enzyme inhibitors or angiotensin-receptor blockers). Multivariable generalized estimating equations were used to compare the primary and secondary outcomes between the 2 groups and to calculate the relative risk (RR) at 12 months. Propensity score matching and inverse probability of treatment weighting were performed as sensitivity analyses, and propensity scores were calculated using a multivariable logistic regression model.

Results: At 1 year, 88% (565/642) of patients in the intervention group and 91.8% (518/564) of patients in the control group had successful follow-up data. We matched 257 pairs of patients between the intervention and control groups. There was no obvious advantage in medication adherence with the 4 cardioprotective drugs in the intervention group (172/565, 30.4%, vs 142/518, 27.4%; RR 0.99, 95% CI 0.97-1.02; P=.65). The intervention measures improved smoking cessation (44/565, 7.8%, vs 118/518, 22.8%; RR 0.48, 95% CI 0.44-0.53; P<.001) and alcohol restriction (33/565, 5.8%, vs 91/518, 17.6%; RR 0.47, 95% CI 0.42-0.54; P<.001).

Conclusions: The tertiary A-level hospital, WeChat-based intervention did not improve adherence to the 4 cardioprotective medications compared with the traditional method. Tertiary A-level hospital, WeChat-based interventions have a positive effect on improving lifestyle, such as quitting drinking and smoking, in patients with stable coronary artery disease and can be tried as a supplement to community hospital follow-up.

Trial registration: ClinicalTrials.gov NCT04795505; https://ichgcp.net/clinical-trials-registry/NCT04795505.

Keywords: WeChat; coronary artery disease; medication adherence; mobile phone; telemedicine.

Conflict of interest statement

Conflicts of Interest: None declared.

©Boqun Shi, Xi Liu, Qiuting Dong, Yuxiu Yang, Zhongxing Cai, Haoyu Wang, Dong Yin, Hongjian Wang, Kefei Dou, Weihua Song. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 27.10.2021.

Figures

Figure 1
Figure 1
Overview of the WeChat-based telemedicine intervention. HbA1c: glycated hemoglobin A1c; LDL-C: low-density lipoprotein cholesterol.
Figure 2
Figure 2
Screenshots of the user registration and binding interface.
Figure 3
Figure 3
Screenshots of educational materials related to coronary heart disease in the patient terminal.
Figure 4
Figure 4
Screenshot of the initiation of a question in the patient terminal.
Figure 5
Figure 5
Backstage management interface of the WeChat-based secondary prevention program.
Figure 6
Figure 6
Screenshots of the answering of questions in the physician terminal.
Figure 7
Figure 7
Synchronous data-capture system of the WeChat-based secondary prevention program.
Figure 8
Figure 8
Participant flow diagram.
Figure 9
Figure 9
Proportions of medical adherence to 4 cardioprotective drugs in the intervention group and control group.
Figure 10
Figure 10
Subgroup analysis of primary outcome. Values are n (%) for categorical variables. The interaction between treatment effect and subgroups was evaluated using multivariable generalized estimating equations models. The analysis was performed in the whole population and adjusted for baseline factors including sex, age, control of hypertension, current smoker, current drinker, BMI, low-density lipoprotein cholesterol, and glycated hemoglobin. HbA1c: glycated hemoglobin A1c; LDL-C: low-density lipoprotein cholesterol. RR: relative risk.

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