Achieving rapid blood pressure control with digital therapeutics: Retrospective cohort and machine learning study

Abstract

Background: Behavioral therapies, such as electronic counseling and self-monitoring dispensed through mobile apps, have been shown to improve blood pressure, but the results vary and long-term engagement is a challenge. Machine learning is a rapidly advancing discipline that can be used to generate predictive and responsive models for the management and treatment of chronic conditions and shows potential for meaningfully improving outcomes. Objective: The objectives of this retrospective analysis were to examine the effect of a novel digital therapeutic on blood pressure in adults with hypertension and to explore the ability of machine learning to predict participant completion of the intervention. Methods: Participants with hypertension, who engaged with the digital intervention for at least 2 weeks and had paired blood pressure values, were identified from the intervention database. Participants were required to be ≥18 years old, reside in the United States, and own a smartphone. The digital intervention offers personalized behavior therapy, including goal setting, skill building, and self-monitoring. Participants reported blood pressure values at will, and changes were calculated using averages of baseline and final values for each participant. Machine learning was used to generate a model of participants who would complete the intervention. Random forest models were trained at days 1, 3, and 7 of the intervention, and the generalizability of the models was assessed using leave-one-out cross-validation. Results: The primary cohort comprised 172 participants with hypertension, having paired blood pressure values, who were engaged with the intervention. Of the total, 86.1% participants were women, the mean age was 55.0 years (95% CI 53.7-56.2), baseline systolic blood pressure was 138.9 mmHg (95% CI 136.6-141.3), and diastolic was 86.2 mmHg (95% CI 84.8-87.7). Mean change was -11.5 mmHg for systolic blood pressure and -5.9 mmHg for diastolic blood pressure over a mean of 62.6 days (P