The implementation of remote home monitoring models during the COVID-19 pandemic in England

• Published in: EClinicalMedicine 2021-04, Vol.34, p.100799-100799, Article 100799
• Main Authors: Vindrola-Padros, Cecilia, Sidhu, Manbinder S., Georghiou, Theo, Sherlaw-Johnson, Chris, Singh, Kelly E., Tomini, Sonila M., Ellins, Jo, Morris, Steve, Fulop, Naomi J.
• Format: Article
• Language: English
• Subjects: Research Paper
• ISSN: 2589-5370; 2589-5370
• DOI: 10.1016/j.eclinm.2021.100799

There is a paucity of evidence for the implementation of remote home monitoring for COVID-19 infection. The aims of this study were to identify the key characteristics of remote home monitoring models for COVID-19 infection, explore the experiences of staff implementing these models, understand the use of data for monitoring progress against outcomes, and document variability in staffing and resource allocation. This was a multi-site mixed methods study conducted between July and August 2020 that combined qualitative and quantitative approaches to analyse the implementation and impact of remote home monitoring models developed during the first wave of the COVID-19 pandemic in England. The study combined interviews (n = 22) with staff delivering these models across eight sites in England with the collection and analysis of data on staffing models and resource allocation. The models varied in relation to the healthcare settings and mechanisms used for patient triage, monitoring and escalation. Implementation was embedded in existing staff workloads and budgets. Good communication within clinical teams, culturally-appropriate information for patients/carers and the combination of multiple approaches for patient monitoring (app and paper-based) were considered facilitators in implementation. The mean cost per monitored patient varied from £400 to £553, depending on the model. It is necessary to provide the means for evaluating the effectiveness of these models, for example, by establishing comparator data. Future research should also focus on the sustainability of the models and patient experience (considering the extent to which some of the models exacerbate existing inequalities in access to care).