AI Voice Agents Revolutionize Blood Pressure Management for Older Adults

AI voice agents helped improve accuracy of blood pressure measurements in older adults

American Heart AssociationSep 8 2025 Artificial intelligence (AI) voice agents helped older adults with high blood pressure to accurately report their blood pressure readings and improved blood pressure management, according to preliminary research presented at the American Heart Association's Hypertension Scientific Sessions 2025. The meeting is in Baltimore, September 4-7, 2025, and is the premier scientific exchange focused on recent advances in basic and clinical research on high blood pressure and its relationship to cardiac and kidney disease, stroke, obesity and genetics. Controlling blood pressure remains a cornerstone for improving cardiovascular outcomes for patients, however, capturing timely, compliant blood pressure readings remains a challenge, particularly for patients with limited access to care. In our study, we were able to improve accuracy of blood pressure measures and patient outcomes." Tina-Ann Kerr Thompson, M.D., lead study author, senior vice president of the primary care service line and executive director of the population health collaborative at Emory Healthcare, Atlanta AI voice agents are conversational systems powered by large language models that can understand and produce natural speech in real time when interacting with humans. This study included 2,000 adults, a majority ages 65 and older, and was designed to evaluate the effectiveness and scalability of a voice-enabled AI agent in engaging patients to self-report accurate blood pressure readings, in place of a phone call with a health care professional about their blood pressure measures. The AI agent also identified patients in need of follow-up medical care based on their blood pressure readings. The AI voice-agent calls to patients were made using commercially available AI in multiple languages, including English and Spanish. A blood pressure reading outside the threshold range for readings that vary based on the presence of other conditions, such as diabetes, resulted in the call being escalated to a licensed nurse or medical assistant. The presence of symptoms such as dizziness, blurred vision or chest pain also prompted escalation of the call. Escalation to additional care was immediate in urgent situations or within 24 hours for non-urgent issues. The patients were contacted by the voice agent to provide recent blood pressure readings or to conduct live measurements during the call. After the call, the readings were entered into the patient's electronic health record and reviewed by a clinician. Call routing and referrals for care management were prompted for patients with difficult-to-control high blood pressure. This process reduced the manual workload by clinicians and resulted in an 88.7% lower cost-per-reading. This amount was calculated by comparing the cost of commercially available AI voice agents with the use of human nurses to perform similar tasks that result in successfully obtaining patient self-reported blood pressure readings. The study found that integrating AI into clinical workflows lowered costs and improved care management for patients. During the study period: 85% of patients were successfully reached by the voice-based AI agent. Of those patients, 67% completed the call, and 60% took a compliant blood pressure reading during the call. Among these patients, 68% met CBP (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. The Medicare Advantage (MA) and Healthcare Effectiveness Data and Information Set (HEDIS) CBP measure increased from a previously reported 1-star rating to 4-star rating. At the end of each completed call, patients received a two-question survey to rate their satisfaction on a scale of 1 to 10, with 10 being 100% satisfied. Among the completed calls, the average patient-reported satisfaction rate exceeded 9 out of 10, reflecting an excellent overall experience with the voice-based AI agent. "We were surprised by the high patient satisfaction scores after interacting with artificial intelligence-based voice agents," said Thompson. "We are excited for what that means for the future, since patient engagement and satisfaction are so critical to health care outcomes." "This could be a game-changing study," said Eugene Yang, M.D., M.S., FACC, an American Heart Association volunteer expert. "Accurate blood pressure readings are essential to improving control, and new approaches can help make that possible. Breakthrough AI technologies like this could transform how we manage blood pressure by reaching patients wherever they are and addressing critical barriers, such as limited access to care and gaps in patient support." Yang, who was not involved in this study, is a professor in the division of cardiology and the Carl and Renée Behnke Endowed Chair for Asian Health at University of Washington School of Medicine. The study has several limitations. This study was observational and did not have a control group. The consecutive AI calls were not compared to human calls; instead, AI voice-calls were deployed because it was not possible to make an adequate number of human-only calls. In addition, the study was retrospective, meaning it reviewed existing data, and evaluation was completed after the clinically identified calls were already made. Study details, background and design: Participants included 2,000 adults; a majority were ages 65 or older (average age of 72 years; 61% women) receiving care for high blood pressure. Review of electronic health records identified patients who were missing blood pressure data or whose most recent BP reading was not within the normal range of <120/80 mm Hg. Patients with these gaps in data were tagged to receive calls from the AI voice agent. The study was conducted with patients at Emory Healthcare in Atlanta during a 10-week period. Patients received at least one phone call during the study. Patients received more than one call if they did not answer the phone. Patients with open gaps in managing blood pressure were identified through electronic medical records (EMR) and payer analytics. Patient lists were reviewed to ensure the information in their records was correct, and they were verified for outreach by a clinical operations team to ensure real-time accuracy of gaps before outreach to the patients. AI texts, phone calls from the conventional care team, recent clinical visits where documentation could be found for a blood pressure reading and generative AI voice agents were used to contact patients to provide recent blood pressure readings or take their blood pressure reading during the call. These included any recent clinical visits where documentation could be found for a BP recorded. A post-call validation step was integrated into the workflow, in which readings were entered into the EHR, reviewed by a clinician and submitted as supplemental data to close the Stars quality gap. For patients with uncontrolled high blood pressure, clinical escalation referrals were made to care management teams. The Centers for Medicare and Medicaid Services (CMS) developed the Star Ratings system, known as MA Stars, to rate Medicare Advantage (MA) (Part C) and prescription drug (Part D) plans on a 5-star scale with 1 being the lowest score and 5 being the highest score. MA plans are plans from private insurance companies approved by Medicare and not issued by Medicare itself. Hospitals, care centers and clinicians are eligible to receive a bonus payment increase if they achieve at least a 4-star rating. Self-measured blood pressure is a focus area of Target:BP, an American Heart Association initiative that helps health care organizations improve blood pressure control rates through an evidence-based program. Home blood pressure monitoring is recommended for all adults with any level of high blood pressure, as noted in the Association's new 2025 guideline on high blood pressure, released last month. American Heart Association

AI helps older adults report accurate blood pressure readings at home

Artificial intelligence (AI) voice agents helped older adults with high blood pressure to accurately report their blood pressure readings and improved blood pressure management, according to preliminary research presented at the American Heart Association's Hypertension Scientific Sessions 2025 held in Baltimore, September 4-7, 2025. "Controlling blood pressure remains a cornerstone for improving cardiovascular outcomes for patients, however, capturing timely, compliant blood pressure readings remains a challenge, particularly for patients with limited access to care," said lead study author Tina-Ann Kerr Thompson, M.D., senior vice president of the primary care service line and executive director of the population health collaborative at Emory Healthcare in Atlanta. "In our study, we were able to improve accuracy of blood pressure measures and patient outcomes." AI voice agents are conversational systems powered by large language models that can understand and produce natural speech in real time when interacting with humans. This study included 2,000 adults, the majority aged 65 and older, and was designed to evaluate the effectiveness and scalability of a voice-enabled AI agent in engaging patients to self-report accurate blood pressure readings, in place of a phone call with a health care professional about their blood pressure measures. The AI agent also identified patients in need of follow-up medical care based on their blood pressure readings. The AI voice-agent calls to patients were made using commercially available AI in multiple languages, including English and Spanish. A blood pressure reading outside the threshold range for readings that vary based on the presence of other conditions, such as diabetes, resulted in the call being escalated to a licensed nurse or medical assistant. The presence of symptoms such as dizziness, blurred vision or chest pain also prompted escalation of the call. Escalation to additional care was immediate in urgent situations or within 24 hours for non-urgent issues. The patients were contacted by the voice agent to provide recent blood pressure readings or to conduct live measurements during the call. After the call, the readings were entered into the patient's electronic health record and reviewed by a clinician. Call routing and referrals for care management were prompted for patients with difficult-to-control high blood pressure. This process reduced the manual workload by clinicians and resulted in an 88.7% lower cost-per-reading. This amount was calculated by comparing the cost of commercially available AI voice agents with the use of human nurses to perform similar tasks that result in successfully obtaining patient self-reported blood pressure readings. The study found that integrating AI into clinical workflows lowered costs and improved care management for patients. During the study period: * 85% of patients were successfully reached by the voice-based AI agent. * Of those patients, 67% completed the call, and 60% took a compliant blood pressure reading during the call. Among these patients, 68% met CBP (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. The Medicare Advantage (MA) and Healthcare Effectiveness Data and Information Set (HEDIS) CBP measure increased from a previously reported 1-star rating to 4-star rating. * At the end of each completed call, patients received a two-question survey to rate their satisfaction on a scale of 1 to 10, with 10 being 100% satisfied. Among the completed calls, the average patient-reported satisfaction rate exceeded 9 out of 10, reflecting an excellent overall experience with the voice-based AI agent. "We were surprised by the high patient satisfaction scores after interacting with artificial intelligence-based voice agents," said Thompson. "We are excited for what that means for the future, since patient engagement and satisfaction are so critical to health care outcomes." "This could be a game-changing study," said Eugene Yang, M.D., M.S., FACC, an American Heart Association volunteer expert. "Accurate blood pressure readings are essential to improving control, and new approaches can help make that possible. Breakthrough AI technologies like this could transform how we manage blood pressure by reaching patients wherever they are and addressing critical barriers, such as limited access to care and gaps in patient support." Yang, who was not involved in this study, is a professor in the division of cardiology and the Carl and Renée Behnke Endowed Chair for Asian Health at University of Washington School of Medicine. The study has several limitations. This study was observational and did not have a control group. The consecutive AI calls were not compared to human calls; instead, AI voice calls were deployed because it was not possible to make an adequate number of human-only calls. In addition, the study was retrospective, meaning it reviewed existing data, and evaluation was completed after the clinically identified calls were already made. Study details, background and design: * Participants included 2,000 adults; a majority were ages 65 or older (average age of 72 years; 61% women) receiving care for high blood pressure. * Review of electronic health records identified patients who were missing blood pressure data or whose most recent BP reading was not within the normal range of <120/80 mm Hg. Patients with these gaps in data were tagged to receive calls from the AI voice agent. * The study was conducted with patients at Emory Healthcare in Atlanta during a 10-week period. Patients received at least one phone call during the study. Patients received more than one call if they did not answer the phone. * Patients with open gaps in managing blood pressure were identified through electronic medical records (EMR) and payer analytics. Patient lists were reviewed to ensure the information in their records was correct, and they were verified for outreach by a clinical operations team to ensure real-time accuracy of gaps before outreach to the patients. * AI texts, phone calls from the conventional care team, recent clinical visits where documentation could be found for a blood pressure reading and generative AI voice agents were used to contact patients to provide recent blood pressure readings or take their blood pressure reading during the call. These included any recent clinical visits where documentation could be found for a BP recorded. * A post-call validation step was integrated into the workflow, in which readings were entered into the EHR, reviewed by a clinician and submitted as supplemental data to close the Stars quality gap. For patients with uncontrolled high blood pressure, clinical escalation referrals were made to care management teams. * The Centers for Medicare and Medicaid Services (CMS) developed the Star Ratings system, known as MA Stars, to rate Medicare Advantage (MA) (Part C) and prescription drug (Part D) plans on a 5-star scale with 1 being the lowest score and 5 being the highest score. MA plans are plans from private insurance companies approved by Medicare and not issued by Medicare itself. Hospitals, care centers and clinicians are eligible to receive a bonus payment increase if they achieve at least a 4-star rating. Self-measured blood pressure is a focus area of Target:BP, an American Heart Association initiative that helps health care organizations improve blood pressure control rates through an evidence-based program. Home blood pressure monitoring is recommended for all adults with any level of high blood pressure, as noted in the Association's new 2025 guideline on high blood pressure, released in August.

AI Aids Seniors In Reading, Reporting Blood Pressure At Home

By Deanna Neff HealthDay ReporterMONDAY, Sept. 8, 2025 (HealthDay News) -- Older adults managing high blood pressure might just have one more tool in the toolbox. A new study suggests that artificial intelligence (AI)-powered voice agents can help older adults manage their high blood pressure, potentially transforming how remote patient care is delivered. These preliminary findings were presented Sunday during an American Heart Association meeting in Baltimore. During the study, an AI voice agent prompted patients who were missing blood pressure data or whose most recent BP reading was not within the normal range of less than 120/80 mm Hg to report home blood pressure readings. The research aimed to assess how adding AI into the clinical workflow could improve patients' management of home blood pressure checks and identify those needing follow-up medical care. The voice agent was designed to function like a health care professional, contacting patients, talking to them and asking them to provide blood pressure readings. "Controlling blood pressure remains a cornerstone for improving cardiovascular outcomes for patients, however, capturing timely, compliant blood pressure readings remains a challenge, particularly for patients with limited access to care," said lead author Dr. Tina-Ann Kerr Thompson, a senior vice president at Emory Healthcare in Atlanta. "In our study, we were able to improve accuracy of blood pressure measures and patient outcomes," she added in a news release. Home monitoring is recommended for all adults with any level of high blood pressure, according to the AHA's 2025 guideline on high blood pressure, released last month. The 10-week study included 2,000 adults, most of whom were 65 or older. The AI agent placed calls to patients, who were asked to provide a recent blood pressure reading or take a live measurement during the call. The agent, which spoke multiple languages including English and Spanish, automatically escalated the call to a nurse or medical assistant if a reading was outside a pre-set threshold or if the patient reported symptoms like dizziness or chest pain. This automated process proved to be highly effective and efficient. By reducing the manual workload for clinical staff, the cost per reading was 88.7% lower than using human nurses for similar tasks. In all, the voice agent successfully reached 85% of patients. Of those, 67% completed the call, and 60% took a compliant blood pressure reading while on the phone. This led to a notable improvement in blood pressure control, while reaching more patients and closing gaps in care. Patient satisfaction with the AI agent was also remarkably high. At the end of each call, patients were asked to rate their experience on a scale of 1 to 10. The average score was over 9, indicating a very positive experience, results showed. "We were surprised by the high patient satisfaction scores after interacting with artificial intelligence-based voice agents," Thompson said. "We are excited for what that means for the future, since patient engagement and satisfaction are so critical to health care outcomes." An American Heart Association volunteer expert, Dr. Eugene Yang, a clinical professor in the cardiology division at the University of Washington School of Medicine in Seattle, called the findings "game-changing," noting the potential for new technologies to address barriers to care. "Accurate blood pressure readings are essential to improving control, and new approaches can help make that possible," he said in a news release. "Breakthrough AI technologies like this could transform how we manage blood pressure by reaching patients wherever they are and addressing critical barriers, such as limited access to care and gaps in patient support." The study had some limitations. The AI calls were not directly compared to human-only calls, as it was not feasible to make enough human calls to complete the study, researchers said. Findings presented at medical meetings should be considered preliminary until published in a peer-reviewed journal. More information Tulane University has more on strategies for effective communication in health care. SOURCE: American Heart Association, news release, Sept. 7, 2025