Evaluating Efficacy of Digital Health Technology in the Treatment of Congestive Heart Failure
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About
The purpose of this study is to determine the efficacy of three novel digital health technologies versus usual care in the management of congestive heart failure, as assessed by a primary outcome of improvement in quality of life, and a variety of secondary outcomes that include metrics measuring patient and provider satisfaction, clinical efficiency, and patient outcomes.
Full description
Heart failure is the most common cause of mortality and morbidity in the United States and in Western Europe. However, patient etiology and prognosis varies considerably, and guidance about how to best treat patients has relied on large clinical trials that only include snapshots of the syndrome (at the time the patient interaction with the healthcare system). It remains to be seen whether behavioral interventions can improve patient engagement, increase self-management of the conditions, and thus improve overall clinical outcomes.
Digital health technologies have a great potential to streamline and optimize the clinical management of heart failure. Such technologies can take the form of mobile applications or wearable devices that may provide both patients and providers with valuable real-time information about patient status and cardiovascular health, provide automated patient-tailored coaching and motivational tools, or a mix of both. Integration of these technologies into healthcare systems may allow for genuine engagement of the patient in their own care and management of their disease and/or enhance clinical decision making. To date, no prior study has comprehensively examined the ability of digital heath technologies to improve self-management of heart failure or subsequent clinical outcomes.
This study is an unblinded, 4-arm, parallel group randomized controlled trial to measure the efficacy of four digital health technologies in improving the management of care and quality of life of patients with congestive heart failure (CHF). Patients actively managed by one of Yale New Haven Hospital's heart failure-based clinics will be eligible for this study and approached for consent. Enrolled subjects will be randomized to one of four groups: a control (usual care) arm, or to one of three intervention arms, each of which assesses one of three digital health technologies. These technologies are:
- BodyPort: A data-driven smart scale that provides enhanced cardiac monitoring and risk assessment data.
- Noom: A live, data-driven coaching application providing personalized diet and weight management.
- Conversa: An automated conversational platform providing patient motivation and educational tools for CHF management.
Patients will be enrolled in the study for 6 months. The first three months will typically involve active clinic management and will be the point of our primary outcome assessment, while the final three months will assess stability of effect on patient care and outcomes.
The primary outcome is the rate of improvement in quality of life after 90 days post-enrollment, as measured by the Kansas City Cardiomyopathy Questionnaire (KCCQ). A variety of prespecified secondary outcomes will be measured to determine effects on patient outcomes, quality of care, clinical efficiency, and provider and patient satisfaction with the product.
Enrollment
Sex
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Volunteers
Inclusion criteria
- Adults greater than or equal to 18 and less than 80 years of age
- Enrolled in one of Yale New Haven Hospital's Disease Management or Heart Failure-focused cardiology clinics
- Diagnosed with congestive heart failure (preserved or reduced ejection fraction with or without diabetes)
Exclusion criteria
- Class IV heart failure
- Stage 4 or end stage renal disease (eGFR < 30)
- Recipient of a heart transplant of ventricular assist device
- Under hospice care
- Dementia
- Incarceration
- Pregnancy
- Currently homeless or residing in an unstable living situation (i.e., transitional housing, rehab facility, etc.)
- Inability to consent
- Currently enrolled in a study investigating a digital health product or technology
- Life expectancy of less than 6 months as determined by clinical judgement of primary treating physician
- weight greater than 400 pounds
- unable to stand straight up for 30 seconds without assistance, such as from a cane, walker, or wall.
- non-English speaking
Trial design
Primary purpose
Allocation
Interventional model
Masking
182 participants in 4 patient groups
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Data sourced from clinicaltrials.gov
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