Remote home monitoring (virtual wards) during the COVID-19 pandemic
Despite previous research on the use of remote home monitoring models for other health conditions, there is a paucity of evidence on the implementation of models for remote home monitoring during the COVID-19 pandemic.
This is a collaborative project between BRACE and RSET (a second NIHR HS&DR programme rapid evaluation team) with input from colleagues at Public Health England (PHE) and NHS England (NHSE), NHS Digital and NHSX, and with other research teams working in this area.
Delays in the presentation of patients with COVID-19 has led to patients arriving in acute care emergency departments with very low oxygen saturations, often without accompanying breathlessness (‘silent hypoxia’). Remote home monitoring models (sometimes referred to as ‘virtual wards’) seek to remotely monitor patients considered high-risk of deterioration at home to: 1) avoid unnecessary hospital admissions (appropriate care at the appropriate place), and 2) escalate cases of deterioration at an earlier stage to avoid invasive ventilation and ICU admission. In the UK, over 10 remote home monitoring models have been documented. Some models have been led by secondary care while others are mainly based in primary care. Furthermore, some models have been designed as pre-hospital models (preventing unnecessary hospital admissions) while others have functioned as step-down wards (facilitating early discharge from hospital).
Phase one will develop a conceptual map of remote home monitoring models (including their key characteristics), explore the experiences of staff implementing these models during the first wave of the COVID-19 pandemic, understand the use of data for monitoring progress against outcomes, and document variability in staffing and resource allocation.
In Phase two the models implemented during the second wave of the pandemic will be evaluated using a mixed-methods study design. The final research questions and design of phase 2 of the evaluation will be informed by the findings from phase 1.
Phase one will be divided in two main workstreams: a scoping review of the literature and a rapid qualitative study to capture the lessons learnt during the first wave of the pandemic based on telephone semi-structured interviews with a purposive sample of staff from eight pilot sites implemented during the first wave of the pandemic, documentary analysis, as well as the collection and analysis of data on staffing models and resource allocation.
In Phase two, qualitative fieldwork will be based on telephone semi-structured interviews with a purposive sample of staff from pilot sites implemented during the second wave of the pandemic and documentary analysis of internal documents developed by these sites. The interviews will focus on capturing the theories of change and logic models guiding the design and implementation of remote home monitoring models, patient and staff experiences of implementing, delivering, and receiving treatment from models during the second wave of the pandemic, the allocation of resources during implementation and decisions made in relation to the collection of patient data and expected outcomes.
- Naomi Fulop (NIHR RSET, PI for the project)
- Theo Georghiou, Nuffield Trust (NIHR RSET)
- Chris Sherlaw-Johnson, Nuffield Trust (NIHR RSET)
- Sonila Tomini, UCL (NIHR RSET)
- Cecilia Vindrola, UCL (NIHR RSET)
- Holly Walton (NIHR RSET)
- Pei Li Ng, UCL (NIHR RSET)
- Jo Ellins, University of Birmingham (NIHR BRACE)
- Manbinder Sidhu, University of Birmingham (NIHR BRACE)
- Kelly Singh, University of Birmingham (NIHR BRACE)
- An article in EClinical Medicine, April 2021: The implementation of remote home monitoring models during the COVID-19 pandemic in England presents findings to identify key characteristics of remote home monitoring models for COVID-19 exploring the important role it has for patients and staff experiences
- Remote home monitoring (virtual wards) during the COVID-19 pandemic: a systematic review .
- A synthesis of main lessons learnt during the implementation of remote home monitoring models during the first and second waves of the pandemic (including use of data and staffing models).
July 2020- June 2021