Impact of artificial intelligence-assisted health management on blood pressure and self-management efficacy in older adults with hypertension

Purpose This paper examined the impacts of artificial intelligence (AI)-assisted health management on blood pressure control and self-management effectiveness in older adults with hypertension.Materials and Methods Two hundred hypertensive patients were randomly assigned to a usual care group (routine health management) or an intervention group (AI-assisted health management, including aspects such as intelligent monitoring, early warning and proactive intervention, among others) (n = 100 each). Primary outcomes included blood pressure control rate (<140/<90 mm Hg) and systolic and diastolic blood pressure (SBP and DBP). Secondary outcomes included improvement in lifestyle behaviors, level of hypertension knowledge awareness, self-management efficacy, medication beliefs, quality of life, and management satisfaction.Results Following one year intervention, the intervention group demonstrated a higher blood pressure control rate than the usual care group (88.66% vs. 64.89%), along with lower SBP (128.49 ± 6.63 vs. 135.38 ± 7.31 mmHg) and DBP (77.49 ± 6.07 vs. 81.84 ± 5.44 mmHg) (all P < 0.05). Additionally, the intervention group showed superior improvements in smoking behavior change, alcohol consumption behavior change, low-salt and low-fat diet adherence, and regular exercise attainment, as well as higher scores on the Hypertension Knowledge-Level Scale, Hypertension Patient Self-Management Behavior Rating Scale, Modified Beliefs about Medicines Questionnaire, physical component summary and the mental component summary, and Client Satisfaction Questionnaire-8 (all P < 0.05).Conclusion AI-assisted health management enhances blood pressure control, and improves self-management capacity, quality of life, and service satisfaction in older adults with hypertension.