Hypertension, or high blood pressure, affects many people in the United States. The Centers for Disease Control and Prevention (CDC) reports that almost half of American adults have high blood pressure or take medicine to control it. Older adults especially face this problem. They often deal with other health issues, trouble moving around, and less access to health care.
Home blood pressure monitoring (HBPM) is recommended by the American Heart Association and current clinical guidelines to help manage hypertension. But getting consistent and correct readings from patients at home is difficult. Many people forget to check their blood pressure, give wrong numbers, or have trouble using the devices. Because of this, doctors and nurses spend a lot of time making phone calls, checking incomplete information, and managing follow-ups by hand.
Making phone calls manually takes a lot of work and costs a lot. This old method often misses early signs of problems that need quick action. This can lead to worse health for patients.
A study presented at the American Heart Association’s Hypertension Scientific Sessions in 2025 shows how AI voice agents help with blood pressure reporting. Emory Healthcare did this study with 2,000 adults, mostly aged 65 and older, who had trouble managing hypertension.
The AI voice agent called patients in several languages, including English and Spanish. It talked with the patients and asked them to report their blood pressure or take a reading during the call. The AI could understand and explain instructions, help get correct readings, and guide patients through the process. This helped solve common problems with home monitoring.
Key results from the study were:
These results show that AI can help reach more patients and improve reporting at home, especially for older adults.
A key feature of the AI system is how it quickly passes urgent or concerning patient answers to medical staff. If blood pressure readings are too high or low or if a patient reports symptoms like dizziness, chest pain, or blurred vision, the system sends the call to licensed nurses or medical assistants right away.
This process helps patients get medical help fast when needed. Less urgent concerns are checked within 24 hours. This setup supports early care and may stop hospital visits or worse health outcomes.
Using AI calls also helps move verified blood pressure data automatically into electronic health records (EHRs). Doctors can see trends, review data, and manage care faster while spending less time on paperwork.
Adding AI-driven blood pressure monitoring to medical practice workflows helps balance good patient care with less work for clinicians.
Automated Data Collection and Documentation:
The AI voice agent collects home blood pressure readings and puts verified results straight into EHRs. This cuts down errors from manual entry and makes reporting easier.
Smart Task Routing and Clinical Escalation:
AI sorts patient contacts by health risk. Patients at high risk get quick attention, while others can be handled with automated follow-ups. This saves clinician time.
Multilingual and Accessible Communication:
AI calls in many languages improve access for diverse patients. This helps reduce management gaps for those who don’t speak English well.
Integration with Remote Patient Monitoring Platforms:
AI often works with devices like digital blood pressure cuffs, wearables, and apps. These collect data in real time and feed it through EHRs to doctors with helpful analytics.
Reducing Alert Fatigue and Supporting Clinical Decisions:
AI shows only important alerts and blocks less accurate ones, so providers can focus on patients who need help first.
Improving Compliance Reporting and Billing Accuracy:
By making sure blood pressure data collection is timely and follows standards, AI helps with Medicare and quality program reporting. This also supports correct billing and bonuses.
Apart from better monitoring and workflow, AI blood pressure systems offer other benefits for practice leaders in the U.S.:
Although AI offers many benefits, leaders must plan carefully to get the best results. Important factors include:
Healthcare groups in the U.S. are using AI more to handle chronic diseases like hypertension. Some examples:
These examples show growing proof that AI can help with hypertension care and other chronic conditions.
Health leaders running blood pressure programs in the U.S. can benefit from adding AI-based monitoring. It can improve outcomes, cut costs, and reduce workload for clinicians. Key steps are:
As AI keeps improving, it will likely play a bigger role in managing hypertension. These tools offer efficient, cost-effective ways to enhance care for different groups of patients.
Adding AI-driven blood pressure monitoring into clinical work routines gives U.S. medical practices tools to handle growing demands in hypertension care. By improving data accuracy, involving patients more, and cutting administrative work, AI can help improve the quality and efficiency of hypertension management now and in the future.
AI voice agents prompt and engage older adults to self-report accurate blood pressure readings during calls. These conversational agents use natural language processing to facilitate live or recent readings, improving the accuracy and completion rates of home blood pressure monitoring compared to traditional phone calls with healthcare professionals.
The study involved 2,000 adults, predominantly aged 65 or older (average age 72), with 61% women. All participants were receiving care for high blood pressure and were identified through electronic health records as having gaps in blood pressure data or uncontrolled readings.
The AI voice agent escalates calls to a licensed nurse or medical assistant if readings fall outside individualized threshold ranges or if symptoms like dizziness, blurred vision, or chest pain are reported. Escalations occur immediately in urgent cases or within 24 hours for non-urgent concerns.
The AI voice agent communicated with patients in multiple languages, including English and Spanish, ensuring accessibility and engagement across diverse patient populations.
Readings collected via AI calls were entered into the electronic health record (EHR), reviewed by clinicians, and triggered referrals for care management if blood pressure was poorly controlled. This integration reduced manual clinician workload and improved data-driven patient management.
The AI voice agent deployment resulted in an 88.7% reduction in cost per blood pressure reading obtained compared to calls made by human nurses, making the AI solution significantly more cost-effective while maintaining quality outcomes.
Among completed calls, patients reported a high satisfaction rate exceeding 9 out of 10, indicating excellent acceptance of the AI voice agent experience in managing their blood pressure remotely.
The AI intervention closed 1,939 controlling blood pressure (CBP) gaps, improving performance from a 1-Star to a 4-Star rating on Medicare Advantage and HEDIS quality metrics, reflecting a 17% improvement and eligibility for bonus payments.
Limitations included an observational design without a control group, lack of comparison to human-only calls due to feasibility constraints, and retrospective evaluation of existing data, making findings preliminary prior to peer-reviewed publication.
AI voice agents enable remote, scalable outreach to patients with limited access to care, facilitating timely self-monitoring, symptom reporting, and clinical escalation. This helps overcome challenges in patient support, improves blood pressure control, and enhances quality outcomes in preventive care.