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.
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).
This project ran from July 2020 to June 2021.
Our Approach
Our Approach
Phase One
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.
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.
Phase Two
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.
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.
Our Outputs
Our Outputs
- In the youtube video 'BRACE rapid evaluation: Covid Oximetry at home service.' Manbinder Sidhu discusses the evaluation of the Covid Oximetry
- National Institute for Health Research Services and Delivery Research stream (NIHR HSDR) Rapid Evaluation Centre Topic Report: A Rapid Mixed Methods Evaluation of Remote Home Monitoring Models During the COVID-19 Pandemic in England; Naomi J. Fulop, Holly Walton, Nadia Crellin, Theo Georghiou, Lauren Herlitz, Ian Litchfield, Efthalia Massou, Chris Sherlaw-Johnson, Manbinder Sidhu, Sonila M. Tomini, Cecilia Vindrola-Padros, Jo Ellins, Stephen Morris, Pei Li Ng, November 2022
Download the NIHR report (PDF) -
An article in Journal of Health Services Research & Policy, July 2023 Staff experiences of training and delivery of remote home monitoring services for patients diagnosed with COVID-19 in England: A mixed-methods study details the nature of 'work' that health care staff in England undertook to manage patients with COVID-19 remotely, how they were supported to deliver these new services, and the factors that influenced delivery of COVID-19 remote home monitoring services for staff.
- An article in Health Expectations, July 2022 Patients' experiences of, and engagement with, remote home monitoring services for COVID-19 patients: A rapid mixed-methods study; presents findings on patient experiences of, and engagement with, remote home monitoring models for COVID-19.
- An article in EClinical Medicine, June 2022: The impact of post-hospital remote monitoring of COVID-19 patients using pulse oximetry: a national observational study using hospital activity data; this study is an evaluation of the impact of the 'Covid Virtual Ward' services on hospital activity.
- An article in EClinical Medicine, March 2022: The impact of remote home monitoring of people with COVID-19 using pulse oximetry: A national population and observational study presents findings on an evaluation of the clinical effectiveness of the pre-hospital monitoring programme, COVID oximetry@home (CO@h).
- A pre-print article on Examining disparities relating to service reach and patient engagement with COVID-19 remote home monitoring services in England: a mixed methods rapid evaluation, February 2022
- A slide set of findings from three independent evaluations of the NHS COVID Oximetry @home programme completed by RSET and BRACE, the Improvement Analytics Unit (Health Foundation), and Imperial College London, November 2021.
- 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).
Our Team
Our Team
- 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)