Mobile APP-assisted family physician program for improving blood pressure outcome in hypertensive patients.

BACKGROUND: This study was aimed to examine the effectiveness of App-assisted self-care in a Beijing community based on intelligent family physician-optimised collaborative model (IFOCM) program.  METHODS: We conducted a survey of 12,050 hypertensive patients between Jan 2014 and Dec 2021. Generalized linear model was used to analyze the covariates that associated with blood pressure (BP) control. Decision tree and random forest algorithm was used to extract the important factors of BP outcome. RESULTS: The study included 5937 patients, mean age 66.2 ± 10.8, with hypertension in the baseline; 3108(52.4) were female. The community management resulted in mean systolic BP and diastolic BP reductions of 4.6 mmHg and 3.8 mmHg at follow-up. There were 3661 (61.6%) hypertension patients with BP control, increasing from 55.0% in 2014 to 75.0% in 2021. After adjusted for covariates, antihypertensive medication adherence, diabetes, and APP-assisted self-care were common predictors associated with BP control in GLM model and machine learning algorithm. CONCLUSION: Community management based on IFOCM program significantly improved BP control in hypertensive patients. APP-assisted self-care would be beneficial for the management of chronic disease.