ArticleBMC cardiovascular disorders2023
Qualitative analysis of a remote monitoring intervention for managing heart failure.
Article in BMC cardiovascular disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02708654 (Automated Hovering for Congestive Heart Failure Management), which is not on this map. Cited by 2 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Automated Hovering for Congestive Heart Failure Management: (EMPOWER) Electronic Monitoring of Patients Offers Way to Enhance Rehabilitation
Who cites it
2 citing papers in PubMed, 2 syntheses or guidelines pooled it, 2 citations in OpenAlex.
- Factors Influencing the Uptake of Digital Health Interventions for Cardiovascular Disease Prevention Among Healthcare Providers: A Systematic Review.Global heart · 2026Pooled it
- A meta-synthesis of qualitative studies on cardiovascular disease patients' experiences using digital health tools.Frontiers in public health · 2025Pooled it
Corrections and comments
- Update of
Authors and funding
10 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundHeart failure (HF) is one of the most common reasons for hospital admission and is a major cause of morbidity, mortality, and increasing health care costs. The EMPOWER study was a randomized trial that used remote monitoring technology to track patients' weight and diuretic adherence and a state-of-the-art approach derived from behavioral economics to motivate adherence to the reverse monitoring technology.
objectiveThe goal was to explore patient and clinician perceptions of the program and its impact on perceived health outcomes and better understand why some patients or clinicians did better or worse than others in response to the intervention. APPROACH: This was a retrospective qualitative study utilizing semi-structured interviews with 43 patients and 16 clinicians to understand the trial's processes, reflecting on successes and areas for improvement for future iterations of behavioral economic interventions. KEY
resultsMany patients felt supported, and they appreciated the intervention. Many also appreciated the lottery intervention, and while it was not an incentive for enrolling for many respondents, it may have increased adherence during the study. Clinicians felt that the intervention integrated well into their workflow, but the number of alerts was burdensome. Additionally, responses to alerts varied considerably by provider, perhaps because there are no professional guidelines for alerts unaccompanied by severe symptoms.
conclusionOur qualitative analysis indicates potential areas for additional exploration and consideration to design better behavioral economic interventions to improve cardiovascular health outcomes for patients with HF. Patients appreciated lottery incentives for adhering to program requirements; however, many were too far along in their disease progression to benefit from the intervention. Clinicians found the amount and frequency of electronic alerts burdensome and felt they did not improve patient outcomes.
trial registrationClinicalTrials.gov Identifier: NCT02708654.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.