JMIR Publications

ABSTRACT

Background:

Hypertension is a long-term medical condition. Mobile health (mHealth) services can help patients to self-manage this condition. However, not all management is effective, possibly due to different levels of patient engagement (PE) with mHealth services. Healthcare provider follow-up is an intervention to promote PE and blood pressure (BP) control.

Objective:

This study aims to (1) discover and characterize patterns of PE with hypertension management app; (2) investigate the effect of healthcare provider follow-up on PE; and (3) identify the follow-up effect on BP in each PE pattern.

Methods:

Patient engagement was represented as the number of days that a patient recorded self-measured BP per week. The study period was the first four weeks for a patient to engage in mHealth service for hypertension management. K-means algorithm was used to group patients by PE. There were compliance follow-up, regular follow-up, and abnormal follow-up in management. The follow-up effect was calculated by the changes in PE and SBP before and after each follow-up. Chi-square tests and Z-test were conducted to understand the distribution of gender, age, education level, systolic blood pressure (SBP), and the number of follow-up in each cluster. The follow-up effect was identified by analysis of variances (ANOVA). Once significant effect was detected, Bonferroni multiple comparisons were further conducted to identify difference between two clusters.

Results:

Patients were grouped into four clusters according to PE: (1) PELL: PE started at low level, and remains low; (2) PEHH: PE started high, and always high; (3) PEHL: PE started high, and drop to low; (4) PELH: PE started low, and rise to high. Significantly more patients over 60 years old was in the PEHH cluster (P≤.05). Significantly lower abnormal follow-up was found (P≤.05) in the PELL cluster. Compliance follow-up and regular follow-up can improve PE. In the clusters of PEHH and PELH, the improvement in PE in the first three weeks and the decrease in SBP in all four weeks were significant after follow-up. The SBP of the clusters of PELL and PELH decreased more (-6.1 and -8.4 mmHg) after follow-up in the first week.

Conclusions:

Four distinct PE patterns were identified for patients engaging in using the hypertension management mobile app. Patients aged over 60 years had higher PE in terms of recording self-measured BP using the mobile app. Once SBP reduced, patients with low PE may stop using the app, and continued decline in PE occurred simultaneously with the increase in SBP. The duration and depth of the effect of healthcare provider follow-up were more significant in patients with high or increased engagement after follow-up.