The primary objective is to establish a Cleveland Clinic-led registry designed to integrate continuous physiological data from consumer wearables, captured by the HeartBit app and a Case Western Reserve University (CWRU)-based platform, with clinical data from patients' individual Electronic Health Record (EHR). This proposal is for understanding the use of personal wearable devices (such as: Fitbit, and Apple Watch) to gather physiological data (such as: heart-rate, steps taken, sleep cycles, and calories expended) and correlate those data with self-reported health status. The research team intends to collect all of the data generated by the participant's personal wearable devices and to perform an integrated analysis of the physiological data generated by the wearable devices. The investigators specifically aim to uncover patterns from the data that they can evolve models from. The investigators' goal is to better predict and diagnose the adverse effects associated with daily lifestyle, including cardiovascular risk, musculoskeletal, metabolic risks, stress, and sleep disturbances. These data may be used to better understand the daily habits and lifestyle choices to possibly predict a person's health and disease risk to provide a more comprehensive diagnosis with early recognition and prevention. As wearable devices become more accurate and cheaper to purchase for the general public, integrative analysis of wearable data from multiple devices may lead to models that can be used by clinicians and basic scientists to make inferences about the daily lifestyle and its effects on health and disease.
Study Type
OBSERVATIONAL
Enrollment
500
Cleveland Clinic
Cleveland, Ohio, United States
RECRUITINGEstablish Wearables Registry
To establish a Cleveland Clinic-led registry that integrates continuous physiological data from consumer wearables, captured by the HeartBit app and a Case Western Reserve University-based platform, with comprehensive clinical and laboratory data from the Cleveland Clinic EHR.
Time frame: 10 years
Association between Wearable-derived Heart Rate and Clinical Outcomes
To determine whether, and to what extent, changes in wearable-derived heart rate are associated with clinical outcomes, including hospitalizations, emergency department visits, and changes in laboratory markers.
Time frame: 10 years
Association between Wearable-derived Physical Activity and Clinical Outcomes
To determine whether, and to what extent, changes in wearable-derived physical activity are associated with clinical outcomes, including hospitalizations, emergency department visits, and changes in laboratory markers.
Time frame: 10 years
Association between Wearable-derived Sleep Metrics and Clinical Outcomes
To determine whether, and to what extent, changes in wearable-derived sleep metrics are associated with clinical outcomes, including hospitalizations, emergency department visits, and changes in laboratory markers.
Time frame: 10 years
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