A Novel Intelligent Two-Way Communication System for Remote Heart Failure Medication Uptitration (the CardioCoach Study): Randomized Controlled Feasibility Trial

Smeets, C. J. P. P.; Storms, Valérie; Vandervoort, Pieter; Dreesen, Pauline; Vranken, Julie; Houbrechts, Marita; Goris, Hanne; Grieten, Lars; Dendale, Paul

doi:10.2196/cardio.9153

Cited by 13 publications

(16 citation statements)

References 37 publications

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“…Patient engagement with mHealth interventions was measured solely based on system usage data in 72% (23/32) of the studies. Among the remaining studies, 6% (2/32) used only qualitative methods to determine engagement (focus groups and semistructured interviews) [ 34 , 39 ]; 19% (6/32) [ 14 , 40 , 48 , 54 , 57 , 62 ] used both system usage data and qualitative methods; and 3% (1/32) [ 43 ] planned to use system usage data, qualitative methods (think aloud), and user engagement questionnaires.…”

Section: Resultsmentioning

confidence: 99%

“…In 20% (6/30) of the 30 studies [ 35 , 44 , 52 , 54 , 55 , 58 ], system usage data were operationalized as the number of assigned tasks completed per patient per number of days equipped with a mobile device or intervention. In 1 of the 6 studies [ 35 ], investigators reported a mean engagement of 5.7%, with a range of 0 to 27, while in the remaining studies, engagement was reported as an overall rate, ranging from 53.3% to 95%.…”

Section: Resultsmentioning

confidence: 99%

“…The emotional, cognitive, and behavioral domains of patient engagement with mHealth interventions, and the constructs used to describe them in qualitative research are summarized in Table 2 . In 8 [ 14 , 34 , 39 , 40 , 48 , 54 , 57 , 62 ] out of the 9 studies that included qualitative measures, open-ended questionnaires, focus groups, and semistructured interviews were used to describe patients’ experience of using mHealth devices. The experiences were categorized under the behavioral, cognitive, and emotional domains of patient engagement.…”

Section: Resultsmentioning

confidence: 99%

“…Of the 32 studies, 16 (50%) [14,[34][35][36][37][38][39][40][41][42][43][44][45][46][47][48] were conducted in the United States. The remaining studies were conducted in Germany (3/32, 9%) [49][50][51], Canada (2/32, 6%) [14,52], Belgium (2/32, 6%) [53,54], Italy (2/32, 6%) [55,56], the United Kingdom (1/32, 3%) [57], Austria (1/32, 3%) [58], Sweden (1/32, 3%) [59], Poland (1/32, 3%) [60], Singapore (1/32, 3%) [61], China (1/32, 3%) [62], and Australia (1/32, 3%) [63]. The duration of the studies ranged from 1 to 26 months, with a median of 3 months.…”

Section: Study and Patient Characteristicsmentioning

confidence: 99%

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Measures of Engagement With mHealth Interventions in Patients With Heart Failure: Scoping Review

Madujibeya¹,

Lennie²,

Aroh³

et al. 2022

JMIR Mhealth Uhealth

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Background Despite the potential of mobile health (mHealth) interventions to facilitate the early detection of signs of heart failure (HF) decompensation and provide personalized management of symptoms, the outcomes of such interventions in patients with HF have been inconsistent. As engagement with mHealth is required for interventions to be effective, poor patient engagement with mHealth interventions may be associated with mixed evidence. It is crucial to understand how engagement with mHealth interventions is measured in patients with HF, and the effects of engagement on HF outcomes. Objective In this review, we aimed to describe measures of patient engagement with mHealth interventions and the effects of engagement on HF outcomes. Methods We conducted a systematic literature search in 7 databases for relevant studies published in the English language from 2009 to September 2021 and reported the descriptive characteristics of the studies. We used content analysis to identify themes that described patient engagement with mHealth interventions in the qualitative studies included in the review. Results We synthesized 32 studies that operationalized engagement with mHealth interventions in 4771 patients with HF (3239/4771, 67.88%, male), ranging from a sample of 7 to 1571 (median 53.3) patients, followed for a median duration of 90 (IQR 45-180) days. Patient engagement with mHealth interventions was measured only quantitatively based on system usage data in 72% (23/32) of the studies, only qualitatively based on data from semistructured interviews and focus groups in 6% (2/32) of studies, and by a combination of both quantitative and qualitative data in 22% (7/32) of studies. System usage data were evaluated using 6 metrics of engagement: number of physiological parameters transmitted (19/30, 63% studies), number of HF questionnaires completed (2/30, 7% studies), number of log-ins (4/30, 13% studies), number of SMS text message responses (1/30, 3% studies), time spent (5/30, 17% studies), and the number of features accessed and screen viewed (4/30, 13% studies). There was a lack of consistency in how the system usage metrics were reported across studies. In total, 80% of the studies reported only descriptive characteristics of system usage data. The emotional, cognitive, and behavioral domains of patient engagement were identified through qualitative studies. Patient engagement levels ranged from 45% to 100% and decreased over time. The effects of engagement on HF knowledge, self-care, exercise adherence, and HF hospitalization were inconclusive. Conclusions The measures of patient engagement with mHealth interventions in patients with HF are underreported and lack consistency. The application of inferential analytical methods to engagement data is extremely limited. There is a need for a working group on mHealth that may consolidate the previous operational definitions of patient engagement into an optimal and standardized measure.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Study and Patient Characteristicsmentioning

confidence: 99%

See 2 more Smart Citations

Measures of Engagement With mHealth Interventions in Patients With Heart Failure: Scoping Review

Madujibeya¹,

Lennie²,

Aroh³

et al. 2022

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

show abstract

“…It has been shown that the uptake and titration of guideline-recommended medical HF therapy could be improved further [ 7 , 8 , 9 , 10 ]. Remote monitoring strategies can be used to aid clinicians in the up-titration of guideline-recommended medical HF therapy [ 11 ]. Over the last years, multiple monitoring strategies, such as non-invasive remote monitoring (consisting of structured telephone support or non-invasively monitoring of parameters including body weight, blood pressure, and heart rate), monitoring using cardiac implantable electronic devices (such as implantable cardioverter-defibrillator or cardiac resynchronization therapy devices) and invasive remote hemodynamic monitoring, have been proposed and tested [ 12 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Remote Monitoring in Chronic Heart Failure Patients: Is Non-Invasive Remote Monitoring the Way to Go?

Veenis

Radhoe

Hooijmans

et al. 2021

Sensors

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Heart failure (HF) is a major health care issue, and the incidence of HF is only expected to grow further. Due to the frequent hospitalizations, HF places a major burden on the available hospital and healthcare resources. In the future, HF care should not only be organized solely at the clinical ward and outpatient clinics, but remote monitoring strategies are urgently needed to guide, monitor, and treat chronic HF patients remotely from their homes as well. The intuitiveness and relatively low costs of non-invasive remote monitoring tools make them an appealing and emerging concept for developing new medical apps and devices. The recent COVID-19 pandemic and the associated transition of patient care outside the hospital will boost the development of remote monitoring tools, and many strategies will be reinvented with modern tools. However, it is important to look carefully at the inconsistencies that have been reported in non-invasive remote monitoring effectiveness. With this review, we provide an up-to-date overview of the available evidence on non-invasive remote monitoring in chronic HF patients and provide future perspectives that may significantly benefit the broader group of HF patients.

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Interventions for Optimization of Guideline-Directed Medical Therapy

Tang,

Brownell,

Roberts

et al. 2024

JAMA Cardiol

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ImportanceImplementation of guideline-directed medical therapy (GDMT) in real-world practice remains suboptimal. It is unclear which interventions are most effective at addressing current barriers to GDMT in patients with heart failure with reduced ejection fraction (HFrEF).ObjectiveTo perform a systematic review to identify which types of system-level initiatives are most effective at improving GDMT use among patients with HFrEF.Evidence ReviewPubMed, Embase, Cochrane, CINAHL, and Web of Science databases were queried from January 2010 to November 2023 for randomized clinical trials that implemented a quality improvement intervention with GDMT use as a primary or secondary outcome. References from related review articles were also included for screening. Quality of studies and bias assessment were graded based on the Cochrane Risk of Bias tool and Oxford Centre for Evidence-Based Medicine.FindingsTwenty-eight randomized clinical trials were included with an aggregate sample size of 19 840 patients. Studies were broadly categorized as interdisciplinary interventions (n = 15), clinician education (n = 5), electronic health record initiatives (n = 6), or patient education (n = 2). Overall, interdisciplinary titration clinics were associated with significant increases in the proportion of patients on target doses of GDMT with a 10% to 60% and 2% to 53% greater proportion of patients on target doses of β-blockers and renin-angiotensin-aldosterone system inhibitors, respectively, in intervention groups compared with usual care. Other interventions, such as audits, clinician and patient education, or electronic health record alerts, were also associated with some improvements in GDMT utilization, though these findings were inconsistent across studies.Conclusions and RelevanceThis review summarizes interventions aimed at optimization of GDMT in clinical practice. Initiatives that used interdisciplinary teams, largely comprised of nurses and pharmacists, most consistently led to improvements in GDMT. Additional large, randomized studies are necessary to better understand other types of interventions, as well as their long-term efficacy and sustainability.

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A Novel Intelligent Two-Way Communication System for Remote Heart Failure Medication Uptitration (the CardioCoach Study): Randomized Controlled Feasibility Trial

Cited by 13 publications

References 37 publications

Measures of Engagement With mHealth Interventions in Patients With Heart Failure: Scoping Review

Measures of Engagement With mHealth Interventions in Patients With Heart Failure: Scoping Review

Remote Monitoring in Chronic Heart Failure Patients: Is Non-Invasive Remote Monitoring the Way to Go?

Interventions for Optimization of Guideline-Directed Medical Therapy

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