AI Voice Agent Improves Blood Pressure Monitoring Accuracy and Outcomes in Older Adults
TL;DR
Emory Healthcare's AI voice agent system reduced blood pressure monitoring costs by 88.7% and improved their Medicare Advantage star rating from 1 to 4 stars.
AI voice agents contact patients to collect blood pressure readings, escalate urgent cases to nurses, and integrate data into electronic health records for clinician review.
This AI technology improves blood pressure management for older adults, leading to better health outcomes and increased patient satisfaction with healthcare experiences.
AI voice agents achieved 85% patient reach and over 9/10 satisfaction scores while helping close nearly 2,000 blood pressure care gaps.
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Artificial intelligence voice agents significantly improved the accuracy of blood pressure reporting and patient outcomes among older adults with hypertension, according to preliminary research presented at the American Heart Association's Hypertension Scientific Sessions 2025. The study involved 2,000 adults, predominantly aged 65 and older, and evaluated the effectiveness of voice-enabled AI agents in engaging patients to self-report accurate blood pressure readings instead of traditional phone calls with healthcare professionals.
The AI voice agent calls utilized commercially available technology in multiple languages, including English and Spanish, and were designed to identify patients requiring follow-up medical care based on their blood pressure readings. When readings fell outside threshold ranges or when patients reported symptoms such as dizziness, blurred vision, or chest pain, calls were immediately escalated to licensed nurses or medical assistants for urgent situations or within 24 hours for non-urgent issues.
Patients were contacted by the voice agent to provide recent blood pressure readings or conduct live measurements during the call. Following each call, readings were entered into the patient's electronic health record and reviewed by clinicians. This automated process significantly reduced manual workload for healthcare providers and resulted in an 88.7% lower cost-per-reading compared to using human nurses for similar tasks.
The study demonstrated substantial improvements in care management outcomes. During the research period, 85% of patients were successfully reached by the AI voice agent, with 67% completing the calls and 60% taking compliant blood pressure readings during the interaction. Among these patients, 68% met controlling blood pressure Stars compliance thresholds. Overall, 1,939 CBP gaps were closed, elevating the measure from 1-Star to 4-Star performance—a 17% improvement that significantly enhanced Medicare Advantage and Healthcare Effectiveness Data and Information Set (HEDIS) CBP measures.
Patient satisfaction with the AI voice agent system was exceptionally high, with average satisfaction ratings exceeding 9 out of 10 on a scale where 10 represented complete satisfaction. This high level of patient acceptance suggests that AI technologies can effectively engage older adults in their healthcare management while maintaining positive user experiences.
The Centers for Medicare and Medicaid Services (CMS) developed the Star Ratings system, known as MA Stars, to rate Medicare Advantage and prescription drug plans on a 5-star scale. Healthcare organizations achieving at least a 4-star rating become eligible for bonus payment increases, making the improvements demonstrated in this study financially significant for healthcare providers.
Home blood pressure monitoring is recommended for all adults with hypertension, as noted in the American Heart Association's 2025 guideline on high blood pressure. Self-measured blood pressure is also a focus area of Target:BP, an American Heart Association initiative that helps healthcare organizations improve blood pressure control rates through evidence-based programs available at https://www.heart.org/en/professional/quality-improvement/target-bp.
While the study shows promising results, researchers note several limitations. The observational nature of the research meant there was no control group, and AI calls were not directly compared to human calls. The retrospective design also meant evaluation occurred after clinically identified calls had already been made. The findings remain preliminary until published as a full manuscript in a peer-reviewed scientific journal.
The integration of AI voice technology into clinical workflows represents a significant advancement in remote patient monitoring and chronic disease management. By addressing critical barriers such as limited access to care and gaps in patient support, this approach could transform how healthcare providers manage hypertension and other chronic conditions, particularly for older adult populations who may face mobility challenges or limited healthcare access.
Curated from NewMediaWire

