Kathi Sigona described her undiagnosed heart condition as feeling like “a chest full of writhing worms in a bag.” For years, the middle school principal from Modesto, California, experienced debilitating fatigue, yet numerous doctor visits yielded no answers. It wasn’t until a routine colonoscopy 12 years ago that a physician finally detected the irregular heartbeat that had eluded detection for so long.
The diagnosis was atrial fibrillation, or AFib, a condition characterized by an irregular and often rapid heart rate. AFib significantly elevates the risk of serious cardiovascular events. The fleeting nature of its symptoms often leaves both patients and healthcare providers unaware. Sigona’s experience underscores a critical challenge in heart health: traditional medical check-ups provide only a snapshot, often missing the subtle yet crucial signs of chronic conditions. This limitation in data capture hinders our ability to truly learn and understand the complexities of heart health.
For individuals like Sigona, and countless others, the Health eHeart Study emerges as a beacon of hope. Spearheaded by UCSF cardiologists Dr. Jeffrey Olgin, Dr. Gregory Marcus, and epidemiologist Dr. Mark Pletcher, the Health eHeart Study is a pioneering online cardiovascular research initiative. Its ambitious goal is to enroll one million participants globally, leveraging the power of smartphones and wearable technology like the Apple Watch to continuously monitor heart health in everyday life. This innovative approach aims to integrate healthcare seamlessly into the fabric of daily routines, providing a wealth of data for eheart learning and transforming our understanding of cardiovascular well-being.
Bridging Gaps in Cardiac Knowledge through Continuous eHeart Learning
Traditional heart studies, such as the long-standing Cardiovascular Health Study and the Framingham Heart Study, rely heavily on periodic clinic visits – annual or bi-annual – to gather patient data. While these studies have been invaluable, their reliance on infrequent data collection creates significant blind spots. Many cardiac irregularities, particularly intermittent conditions like AFib, may not manifest during these brief check-ups.
The Health eHeart Study directly addresses this limitation by employing technology to capture cardiac data continuously, as participants navigate their daily lives. Supplemented by online health surveys, this constant stream of information paints a far more comprehensive picture of individual heart health. This continuous data collection is crucial for eheart learning, allowing researchers to identify patterns, triggers, and subtle changes that would be missed in traditional settings.
Dr. Eric Topol, a UCSF alumnus and professor of innovative medicine at Scripps Health, emphasizes the importance of real-world data capture. “We mainly rely on getting data from people coming into a doctor’s office, and that’s one of the most contrived environments you can imagine,” he notes. Health eHeart transcends these artificial environments, gathering data in the context of everyday living, offering a richer and more authentic source for eheart learning.
The technological landscape has evolved significantly since the inception of Health eHeart. The widespread adoption of smartphones has revolutionized data collection and participant recruitment. Today, the study utilizes a range of devices and apps, including Apple and Android health applications, Fitbit devices, Apple Watches, and Bluetooth-enabled blood pressure monitors and scales. This broad compatibility ensures accessibility for a diverse participant pool, expanding the scope and potential of eheart learning.
While traditional studies prioritize uniform data collection, Health eHeart intentionally embraces a more flexible approach to maximize participation. Dr. Marcus explains, “But in order to enroll a sufficient number of people and make it easy to participate, that was implemented intentionally.” This trade-off between uniformity and scale is deliberate, recognizing that the sheer volume of data gathered from a large and diverse population compensates for variations in data collection methods, ultimately enriching the eheart learning experience.
Unveiling Actionable Insights: Real-World eHeart Learning in Practice
The Health eHeart Study has successfully enrolled over 163,000 research participants, spanning all 50 U.S. states, over 50 countries, and a wide age range. This vast and varied participant base is a treasure trove for eheart learning. Contrary to initial concerns about skewed demographics, the study boasts a mean participant age of around 50, with representation extending into the 80s and 90s.
This large pool empowers researchers to conduct targeted sub-studies, efficiently recruiting participants for specific investigations. For example, researchers can rapidly launch sub-studies to explore the impact of cognitive behavioral therapy on exercise motivation or investigate other focused research questions. The speed and agility of participant recruitment significantly accelerate the pace of eheart learning and discovery.
The Health eHeart team has already published findings from numerous sub-studies in peer-reviewed journals, demonstrating the tangible outcomes of eheart learning. These studies have explored diverse areas, including the correlation between alcohol perception and consumption, the link between prenatal secondhand smoke exposure and adult-onset AFib, and the impact of pre-bedtime cell phone use on sleep quality.
Furthermore, the study has pioneered innovative techniques like “geofencing” hospitals. By tracking participant location data, the study can identify hospitalizations and prompt participants for relevant information. This approach, initially used for hospitalization tracking, holds immense potential for broader health interventions. Dr. Marcus envisions applying geofencing to various locations, such as grocery stores, gyms, and restaurants, to understand and potentially influence health-related behaviors – further expanding the scope of eheart learning and personalized health strategies.
One of the most impactful discoveries stemming from Health eHeart, in partnership with Cardiogram, is the demonstration that Apple Watch heart rate sensors can detect AFib with remarkable 97 percent accuracy. This finding has direct implications for early detection and intervention, potentially preventing serious cardiovascular events and improving patient outcomes. This is a prime example of how eheart learning translates into practical benefits for individuals at risk.
Empowering Patients and Shaping the Future of eHeart Learning
Enthusiastic participants, like Kathi Sigona, now retired and actively involved at 69, are not merely data points; they are active partners in the research process. Sigona is a member of the Health eHeart Alliance, a participant network dedicated to empowering patients in their health journey. This alliance actively contributes to shaping research directions, ensuring that studies are relevant and patient-centered.
In a 2014 meeting with patients and doctors at UCSF, Sigona’s group, guided by Dr. Marcus, proposed investigating the triggers of AFib episodes. Driven by her own experience, Sigona questioned, “Why did I wake up in the middle of the night with AFib? What went on the evening before? Was it too much caffeine? Was it that the dog was barking next door and I couldn’t fall asleep?” This patient-driven inquiry led to a PCORI-funded study where patients actively participate in identifying and controlling their AFib triggers. This innovative study design, where patients act as both participants and controls, is particularly valuable because AFib triggers are highly individualized. This patient-centered approach is a hallmark of eheart learning, ensuring research is relevant and directly beneficial to those affected by heart conditions.
Dr. Olgin emphasizes the limitations of traditional research in capturing immediate influences on cardiac events. “In conventional research, generally you look at baseline data from one snap-shot in time. For example, on that one day, someone drinks this much alcohol. Then you follow them for a time to see who develops AFib and who doesn’t.” The new study, born from patient questions and leveraging continuous data collection, aims to bridge this gap by understanding how short-term behaviors and exposures acutely trigger cardiovascular episodes. This is a significant step forward in eheart learning, moving beyond population-level trends to personalized insights.
The Health eHeart Study, while focused on cardiovascular health, envisions a future where mobile health research extends to a wide range of conditions globally. Built on the Eureka platform, the study aims to inspire other researchers to adopt this technology, expanding the reach and impact of eheart learning across diverse fields of medicine.
For researchers, the Eureka platform offers global reach and efficient data collection. For participants, the Health eHeart Study provides an opportunity to contribute to medical advancements and help others. The study’s emphasis on community service and altruism is a powerful motivator. Participants can choose research areas aligned with their interests, such as heart disease or cancer, and actively contribute to studies in those fields.
The team remains optimistic about reaching its ambitious goal of one million participants. Dr. Marcus concludes, “The good and the bad is that heart disease is so common. We’re relying on altruism and for people to be willing to make a meaningful contribution.” By joining the Health eHeart Study, individuals can become active participants in eheart learning, contributing to a future of improved heart health and personalized medical care.
Join the Study
Take part in the fight against heart disease. Contribute to eheart learning by completing surveys, connecting your mobile devices, and engaging with Health eHeart every six months.
