Improving the utility and sustainability of novel health technology to improve clinical outcomes for patients: an East Staffordshire experience of screening for atrial fibrillation with the AliveCor KardiaMobile

Mathew, Savio; Chambers, Ruth

doi:10.3399/bjgpo.2020.0169

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…However, many of these issues could be overcome to some extent in the future with upgraded smartphones/technology and enhanced broadband services. The extra time required for ECG data interpretation and the potential need for additional confirmatory testing supports the findings from other studies (Matthew & Chambers, 2021 ; Orchard et al., 2016 ; Schnabel et al., 2022 ). The challenge of balancing priorities and managing workflow is a widely reported barrier (Lowres et al., 2015 ); however, further research should be considered to address these barriers in the uptake and utility of mobile ECG technology.…”

Section: Discussionsupporting

confidence: 83%

Evaluating the use of the mobile electrocardiogram technology KardiaMobile™ in community settings: An online survey

Emmett,

Kent,

James

et al. 2024

Nursing Open

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BackgroundIn response to issues identified by community healthcare professionals (HCPs), including difficulty in routinely recording electrocardiograms (ECGs) at the time of their assessments with the population of patients referred to as ‘housebound’, one National Health Service (NHS) Trust adopted the mobile ECG technology; KardiaMobile™, supported by the Academic Health and Science Network (AHSN), in 2017–2018. The use and uptake of this technology were evaluated and are reported in this paper.MethodsA cross‐sectional, mixed‐methods online survey was conducted from August 2021 to October 2021. The respondents were a convenience sample of HCPs using KardiaMobile™ to detect atrial fibrillation (AF) with their patients; all were employed by one, predominantly rural NHS trust. Descriptive methods were used to analyse the quantitative data, whilst a reflexive approach to thematic analysis was chosen to analyse the qualitative data (Braun & Clarke, 2019, Qualitative Research in Sport, Exercise and Health, 11, 589).ResultsA total of 33 surveys were completed, with a response rate of 8.8%. All respondents recognised the potential value of KardiaMobile™ for their work. Nineteen respondents (57.6%) reported having a shared understanding of the purpose of KardiaMobile™. Nineteen respondents (57.6%) agreed sufficient training and resources are provided to enable staff to implement KardiaMobile™. Qualitative data analysis found four overarching themes, with six sub‐themes.ConclusionKardiaMobile™ is a feasible means to detect AF in higher‐risk patients, particularly those living remotely or classed as ‘housebound’. Respondents in this survey indicated a desire for further training and input on the appropriate use of digital and mobile devices for AF care in a community setting. Incomplete integration of device‐collected heart rhythm data into the patient electronic health record was identified as a barrier to greater adoption of digital health devices for community HCPs.No Patient or Public ContributionNot required as it is a service evaluation from the perspective of HCPs using KardiaMobile™ technology.

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Section: Discussionsupporting

confidence: 83%

Evaluating the use of the mobile electrocardiogram technology KardiaMobile™ in community settings: An online survey

Emmett,

Kent,

James

et al. 2024

Nursing Open

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An Intelligent Wearable ECG Sensor in Intra-medical Virtual Chain Network and Inter-medical Virtual Chain Network

Bhattarai,

Peng

2024

SN COMPUT. SCI.

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Considering User Experience and Behavioral Approaches in the Design of mHealth Interventions for Atrial Fibrillation: Systematic Review

Suresh Kumar,

Connolly,

Maier

2024

J Med Internet Res

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Background Atrial fibrillation (AF) is a leading chronic cardiac disease associated with an increased risk of stroke, cardiac complications, and general mortality. Mobile health (mHealth) interventions, including wearable devices and apps, can aid in the detection, screening, and management of AF to improve patient outcomes. The inclusion of approaches that consider user experiences and behavior in the design of health care interventions can increase the usability of mHealth interventions, and hence, hopefully, yield an increase in positive outcomes in the lives of users. Objective This study aims to show how research has considered user experiences and behavioral approaches in designing mHealth interventions for AF detection, screening, and management; the phases of designing complex interventions from the UK Medical Research Council (MRC) were referenced: namely, identification, development, feasibility, evaluation, and implementation. Methods Studies published until September 7, 2022, that examined user experiences and behavioral approaches associated with mHealth interventions in the context of AF were extracted from multiple databases. The PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines were used. Results A total of 2219 records were extracted, with only 55 records reporting on usability, user experiences, or behavioral approaches more widely for designing mHealth interventions in the context of AF. When mapping the studies onto the phases of the UK MRC’s guidance for developing and evaluating complex interventions, the following was found: in the identification phase, there were significant differences between the needs of patients and health care workers. In the development phase, user perspectives guided the iterative development of apps, interfaces, and intervention protocols in 4 studies. Most studies (43/55, 78%) assessed the usability of interventions in the feasibility phase as an outcome, although the data collection tools were not designed together with users and stakeholders. Studies that examined the evaluation and implementation phase entailed reporting on challenges in user participation, acceptance, and workflows that could not be captured by studies in the previous phases. To realize the envisaged human behavior intended through treatment, review results highlight the scant inclusion of behavior change approaches for mHealth interventions across multiple levels of sociotechnical health care systems. While interventions at the level of the individual (micro) and the level of communities (meso) were found in the studies reviewed, no studies were found intervening at societal levels (macro). Studies also failed to consider the temporal variation of user goals and feedback in the design of long-term behavioral interventions. Conclusions In this systematic review, we proposed 2 contributions: first, mapping studies to different phases of the MRC framework for developing and evaluating complex interventions, and second, mapping behavioral approaches to different levels of health care systems. Finally, we discuss the wider implications of our results in guiding future mHealth research.

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Improving the utility and sustainability of novel health technology to improve clinical outcomes for patients: an East Staffordshire experience of screening for atrial fibrillation with the AliveCor KardiaMobile

Cited by 3 publications

References 7 publications

Evaluating the use of the mobile electrocardiogram technology KardiaMobile™ in community settings: An online survey

Evaluating the use of the mobile electrocardiogram technology KardiaMobile™ in community settings: An online survey

An Intelligent Wearable ECG Sensor in Intra-medical Virtual Chain Network and Inter-medical Virtual Chain Network

Considering User Experience and Behavioral Approaches in the Design of mHealth Interventions for Atrial Fibrillation: Systematic Review

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