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1.
Contemp Clin Trials Commun ; 14: 100318, 2019 Jun.
Article in English | MEDLINE | ID: mdl-30656241

ABSTRACT

OBJECTIVES: The advent of large databases, wearable technology, and novel communications methods has the potential to expand the pool of candidate research participants and offer them the flexibility and convenience of participating in remote research. However, reports of their effectiveness are sparse. We assessed the use of various forms of outreach within a nationwide randomized clinical trial being conducted entirely by remote means. METHODS: Candidate participants at possibly higher risk for atrial fibrillation were identified by means of a large insurance claims database and invited to participate in the study by their insurance provider. Enrolled participants were randomly assigned to one of two groups testing a wearable sensor device for detection of the arrhythmia. RESULTS: Over 10 months, the various outreach methods used resulted in enrollment of 2659 participants meeting eligibility criteria. Starting with a baseline enrollment rate of 0.8% in response to an email invitation, the recruitment campaign was iteratively optimized to ultimately include website changes and the use of a five-step outreach process (three short, personalized emails and two direct mailers) that highlighted the appeal of new technology used in the study, resulting in an enrollment rate of 9.4%. Messaging that highlighted access to new technology outperformed both appeals to altruism and appeals that highlighted accessing personal health information. CONCLUSIONS: Targeted outreach, enrollment, and management of large remote clinical trials is feasible and can be improved with an iterative approach, although more work is needed to learn how to best recruit and retain potential research participants. TRIAL REGISTRATION: Clinicaltrials.govNCT02506244. Registered 23 July 2015.

2.
Am Heart J ; 175: 77-85, 2016 May.
Article in English | MEDLINE | ID: mdl-27179726

ABSTRACT

Efficient methods for screening populations for undiagnosed atrial fibrillation (AF) are needed to reduce its associated mortality, morbidity, and costs. The use of digital technologies, including wearable sensors and large health record data sets allowing for targeted outreach toward individuals at increased risk for AF, might allow for unprecedented opportunities for effective, economical screening. The trial's primary objective is to determine, in a real-world setting, whether using wearable sensors in a risk-targeted screening population can diagnose asymptomatic AF more effectively than routine care. Additional key objectives include (1) exploring 2 rhythm-monitoring strategies-electrocardiogram-based and exploratory pulse wave-based-for detection of new AF, and (2) comparing long-term clinical and resource outcomes among groups. In all, 2,100 Aetna members will be randomized 1:1 to either immediate or delayed monitoring, in which a wearable patch will capture a single-lead electrocardiogram during the first and last 2 weeks of a 4-month period beginning immediately or 4 months after enrollment, respectively. An observational, risk factor-matched control group (n = 4,000) will be developed from members who did not receive an invitation to participate. The primary end point is the incidence of new AF in the immediate- vs delayed-monitoring arms at the end of the 4-month monitoring period. Additional efficacy and safety end points will be captured at 1 and 3 years. The results of this digital medicine trial might benefit a substantial proportion of the population by helping identify and refine screening methods for undiagnosed AF.


Subject(s)
Asymptomatic Diseases/epidemiology , Atrial Fibrillation , Electrocardiography, Ambulatory/methods , Mass Screening , Stroke/prevention & control , Aged , Atrial Fibrillation/diagnosis , Atrial Fibrillation/epidemiology , Atrial Fibrillation/physiopathology , Cost Savings , Female , Humans , Incidence , Male , Mass Screening/economics , Mass Screening/instrumentation , Mass Screening/methods , Middle Aged , Outcome and Process Assessment, Health Care , Risk Factors , Stroke/etiology , Telemedicine/methods , United States/epidemiology
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