Consumer Mobile Technologies in CV Care: Key Points

Varma N, Han JK, Passman R, et al.
Promises and Perils of Consumer Mobile Technologies in Cardiovascular Care: JACC Scientific Statement. J Am Coll Cardiol 2024;83:611-631.

The following are key points to remember from a JACC Scientific Statement on the promises and perils of consumer mobile technologies in cardiovascular (CV) care:

  1. Direct-to-consumer (D2C) wearables are increasingly accessible and affordable and acquire health data that may facilitate cardiovascular disease (CVD) management.
  2. D2C wearables have the potential to personalize CVD management by assisting in the comprehensive management of comorbidities and by enabling prognostication, behavioral modification (e.g., push notifications, avatars, gamification), and tailored disease management strategies (e.g., REACT-AF is testing "pill-in-pocket" oral anticoagulation based on atrial fibrillation [AF] detected by a digital health device).
  3. Multiple studies have demonstrated the ability of wearables to detect AF, using either smartwatch photoplethysmography (PPG)-based irregular pulse detection (with confirmation by an electrocardiography [ECG] patch) or by handheld ECG platforms. D2C wearables may have the greatest impact on the management of known AF. Patients with nonpermanent AF have the potential to benefit from self-management of lifestyle modification, rate and rhythm control, and anticoagulation when in close collaboration with a clinician.
  4. Important limitations exist when using mHealth technologies for AF management. Mobile health studies have varied in their designs, population characteristics (e.g., clinical risk), interventions, and outcomes, thereby limiting their implementation in clinical practice. Additionally, the value of detecting subclinical AF remains uncertain, as illustrated by prior studies of patients with cardiac implantable electronic devices.
  5. The experience of wearables with AF raises important questions that need be addressed before patient-generated health data (PGHD) from wearable devices can be broadly incorporated into clinical workflows for CVD management. Salient issues include the following:
    • Diagnostic accuracy: Diagnostic accuracy of D2C wearables is variable based on device type (handheld vs. wearable), technology (PPG vs. ECG), and duration of monitoring.
    • Regulatory oversight: A lack of standardized data collection and processing procedures and inconsistent reporting of technological and demographic factors impede the interpretability and generalizability of wearable device studies. At present, many D2C wearables are considered "general wellness devices" and fall outside of traditional medical device regulation.
    • Security: There is a need for robust technological solutions to improve data protections at the source, legislative frameworks to deter misuse (e.g., inflation of premiums for arrhythmias), and consumer education regarding their role in cybersecurity. PGHD from D2C devices is typically not protected by the Health Insurance Portability and Accountability Act (HIPAA) at present.
    • Behavioral heterogeneity: Research is needed to understand the inadvertent psychological effects from use of D2C wearables (e.g., pathological anxiety leading to frequent health system contact) and how to maintain adherence and engagement over time.
    • Digital access and health equity: The digital divide (i.e., unequal access to and use of digital technology due to sociodemographic factors) and varying levels of digital literacy limit the use of D2C wearables, and efforts are needed to improve digital inclusion. Additionally, the widespread use of mHealth devices by the general population, many of whom are at low CV risk, has the potential to result in data overload and thereby divert resources and attention from high-risk, vulnerable populations.
    • Clinical integration: Mechanisms are currently lacking for clinicians to use wearable device data in their practices. At present, data enter the electronic medical records through locally created and implemented application programming interfaces and patient portals (i.e., self-reported data of variable quality). Proper infrastructure and use of a universal platform is needed for long-term sustainability. There is additionally a need for machine learning algorithms to filter PGHD into actionable alerts and for proper supporting infrastructure (i.e., time, space, personnel).
    • Reimbursement: Reimbursement models are in their primacy and only apply to the minority of devices meeting the FDA definition of a medical device.
  6. New biosignals are emerging though are in their infancy. These include facial video plethysmography (for mass AF screening), voice analysis (for detection of AF and heart failure decompensation), eye tracking headsets (for cognitive impairment and fall risk), and transdermal sensors (for bloodlessly measuring levels of troponin, electrolytes, coagulation profiles), among others.

Clinical Topics: Arrhythmias and Clinical EP, Atrial Fibrillation/Supraventricular Arrhythmias, Cardiovascular Care Team

Keywords: Atrial Fibrillation, Wearable Electronic Devices

< Back to Listings