Association of Adherence to Weight Telemonitoring With Health Care Use and Death

Haynes, Sarah C.; Tancredi, Daniel J.; Tong, Kathleen; Hoch, Jeffrey S.; Ong, Michael; Evangelista, Lorraine S.; Black, Jeffrey D.; Auerbach, Andrew D.; Romano, Patrick S.

doi:10.1001/jamanetworkopen.2020.10174

Cited by 25 publications

(32 citation statements)

References 27 publications

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“…Evidence concerning the relationship between patient's health status and adherence to telemonitoring seems to be also controversial. Some studies indicated that if patients are feeling weak or frail, they may inhibit adherence to telemonitoring (Haynes et al, 2020), while our findings suggested that bariatric patients with no postsurgical complications are less motivated to continue, and would easily drop out if they did not perceive it beneficial for their health. On the other hand, participants in this study who understood the benefits and their role in self-managing their condition were more likely to continue to comply as it empowers them (Maeder et al, 2015;Rho et al, 2014).…”

Section: Discussionmentioning

confidence: 52%

“…Clinical and service benefits of using telemonitoring for patients with a variety of chronic conditions have been well‐documented in the literature; however, an area that requires further research is the importance of patient engagement and motivation (Su et al, 2019), and the relationship with compliance and adherence to telemonitoring (Ding et al, 2020; Maeder et al, 2015). According to Haynes et al (2020), patient adherence is not static but rather a dynamic measure that often changed within patients over time, and which is influenced and associated with patient's socio‐demographic characteristics, such as age, sex and education and their health status (Uddin and Gu, 2019). Adherence to telemonitoring among age groups is debatable, some indicated no significant differences between younger and older subgroups (Celler et al, 2018), while Ware et al (2019) showed a higher adherence rate among older patients with congestive heart failure compared to Uddin and Gu (2019) who indicated that older patients with heart failure tend to show less compliance.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Patients’ experiences of telenursing follow‐up care after bariatric surgery

Arnaert

Girard

Craciunas

et al. 2021

Journal of Clinical Nursing

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Section: Discussionmentioning

confidence: 52%

Section: Discussionmentioning

confidence: 99%

Patients’ experiences of telenursing follow‐up care after bariatric surgery

Arnaert

Girard

Craciunas

et al. 2021

Journal of Clinical Nursing

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“…The key characteristics of the interventions are presented in ( Multimedia Appendix 3 ). In approximately 50% (16/32) of the studies [ 14 , 35 , 38 , 40 , 43 , 45 , 47 - 49 , 52 - 55 , 57 , 58 , 60 ], patients used smartphones, 28% (9/32) [ 36 , 37 , 39 , 42 , 46 , 59 , 61 - 63 ] used tablet computers, 6.25% (2/32) [ 50 , 56 ] used PDAs, and 16% (5/32) used either portable telemonitoring devices [ 34 , 44 ] or a combination of smartphones, smart watches, and tablet computers [ 45 , 51 , 64 ] as integral components of mHealth systems for the management of HF symptoms or for the provision of HF-related self-care education.…”

Section: Resultsmentioning

confidence: 99%

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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“…Although technologies demonstrate their ability to support specific provider functions such as remote monitoring and patient education, they add functions and place high levels of accountability on single providers. For instance, remote monitoring technologies could yield large quantities of data that providers then become responsible for sorting through and acting on, adding another function to their workload [ 120 , 153 ]. Integration of such technologies in clinical practice could be unfeasible because the added provider functions are among the prominent barriers to the uptake of technologies [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

Recommendations for the Design and Delivery of Transitions-Focused Digital Health Interventions: Rapid Review

Singh¹,

Tang²,

Gray³

et al. 2022

JMIR Aging

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Background Older adults experience a high risk of adverse events during hospital-to-home transitions. Implementation barriers have prevented widespread clinical uptake of the various digital health technologies that aim to support hospital-to-home transitions. Objective To guide the development of a digital health intervention to support transitions from hospital to home (the Digital Bridge intervention), the specific objectives of this review were to describe the various roles and functions of health care providers supporting hospital-to-home transitions for older adults, allowing future technologies to be more targeted to support their work; describe the types of digital health interventions used to facilitate the transition from hospital to home for older adults and elucidate how these interventions support the roles and functions of providers; describe the lessons learned from the design and implementation of these interventions; and identify opportunities to improve the fit between technology and provider functions within the Digital Bridge intervention and other transition-focused digital health interventions. Methods This 2-phase rapid review involved a selective review of providers’ roles and their functions during hospital-to-home transitions (phase 1) and a structured literature review on digital health interventions used to support older adults’ hospital-to-home transitions (phase 2). During the analysis, the technology functions identified in phase 2 were linked to the provider roles and functions identified in phase 1. Results In phase 1, various provider roles were identified that facilitated hospital-to-home transitions, including navigation-specific roles and the roles of nurses and physicians. The key transition functions performed by providers were related to the 3 categories of continuity of care (ie, informational, management, and relational continuity). Phase 2, included articles (n=142) that reported digital health interventions targeting various medical conditions or groups. Most digital health interventions supported management continuity (eg, follow-up, assessment, and monitoring of patients’ status after hospital discharge), whereas informational and relational continuity were the least supported. The lessons learned from the interventions were categorized into technology- and research-related challenges and opportunities and informed several recommendations to guide the design of transition-focused digital health interventions. Conclusions This review highlights the need for Digital Bridge and other digital health interventions to align the design and delivery of digital health interventions with provider functions, design and test interventions with older adults, and examine multilevel outcomes. International Registered Report Identifier (IRRID) RR2-10.1136/bmjopen-2020-045596

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Association of Adherence to Weight Telemonitoring With Health Care Use and Death

Cited by 25 publications

References 27 publications

Patients’ experiences of telenursing follow‐up care after bariatric surgery

Patients’ experiences of telenursing follow‐up care after bariatric surgery

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

Recommendations for the Design and Delivery of Transitions-Focused Digital Health Interventions: Rapid Review

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