Community-based VIrtual Electronic Wards for remote monitoring in suspected cases of COVID-19 (coronavirus): C-VIEW Study

Community-based Virtual Electronic Wards for remote monitoring in suspected cases of COVID-19 (coronavirus): C-VIEW Study.

The pandemic of SARS-CoV-2 (coronavirus, COVID-19) remains a global health problem; to date over 9,277,214 cases have been reported across 216 countries with 478,691 deaths by the World Health Organisation (https://covid19.who.int/. Published 2020. Accessed June 25, 2020). Within in the United Kingdom (UK), 307,980 cases with 43,230 deaths have been reported (https://www.gov.uk/guidance/coronavirus-covid-19-information-for-the-public. Published June 25, 2020. Accessed June 25, 2020). This undoubtedly has stretched resources, created pressures within the National Health Service (NHS) and accelerated a change of how hospitals operate in preparation for efficacious resource management.

Vital signs trends (oxygen saturations, heart rate, respiratory rate, blood pressure, temperature) are routinely used for monitoring hospital patients. Clinical deterioration may be recognised through changes in these parameters, and often precedes an adverse event. The rate of deterioration for individuals suffering with COVID-19 remains an unknown entity; given that novel digital technologies have enabled remote monitoring solutions, ‘virtual wards’ may provide a safe strategy for approaching this pandemic in appropriately selected patient groups.

Virtual wards can be established to manage patients remotely, freeing up staff, avoiding overwhelming hospitals, and reducing patient anxiety by allowing recovery at home. Healthcare professionals in virtual wards can track vital signs of those suspected of COVID-19, in near real-time, receiving alerts for clinical deterioration. Pulse oximeters combined with digital innovation (i.e. mobile applications) allow for systems to recognise early deterioration in vital parameters and self-reported symptoms, supporting clinical decision making. Indeed, pilot work trialling the virtual model demonstrated a saving of 300 bed spaces over a three week period.

The Institute of Global Health Innovation (IGHI) at Imperial College London (ICL) are supporting a programme of urgent COVID-19 work regarding new pathways of care for COVID-19 patients. The work will explore the value of a new care pathway using virtual wards with remote monitoring in suspected cases of COVID-19 in the community to improve

1) health resource utilisation (e.g. hospital admissions, ITU admissions),

2) clinical outcomes and

3) cost-effectiveness through early detection of clinical deterioration.

The work is led by NHS England (NHSE) with NHS Digital assisting on data set provision.

NHS England have a programme called NHS@Home, part of which has been asked to trial a remote monitoring pathway for COVID-19 patients. The NHS@Home programme is summarised below:

NHS @home provides an important opportunity to enhance NHS services, utilising the best technologies available to enable personalised clinical support to be delivered virtually to people in the setting of their own home including care homes.

Who the programme targets/ is open to

The initial activities are focusing on three groups, in response to the pandemic and to assist preparations for this winter:

• Group A – All care home residents

• Group B - Deteriorating COVID-19 patients, initially at 2-3 pilot sites, building on work of various other community of practice sites and aligned with work taking place with 8 sites separately, supported by NHS X

• Group C - People identified as higher risk of COVID19, including initially:

- People with a learning disability and diabetes (reaching 3000 people)

- Respiratory conditions (scoping use of peak flow meters to support people with asthma and COPD)

- People with heart failure (initially within 3 STPs, providing self-management support)

- Hypertension (22,000 blood pressure monitors to be distributed)

- Support for 5000 unpaid carers of those with learning disabilities to recognise early deterioration of COVID-19 (scope could be widened)

Group B is the focus of this agreement.

For Group B, the uptake/aims of the project are to pilot virtual wards as a way to manage COVID19 patients in the community through remote monitoring, with the aim of reducing hospital and intensive care stay, and patient mortality. This involves home oximetry monitoring, wearable sensors, medical diary apps and/or phone calls from clinicians to patients – essentially a variety of approaches to monitoring COVID-19 patients at home, referring them into the appropriate health service when needed and avoiding deterioration in the community. There are a number of measures in place to help patients with the remote monitoring and for those who have difficulty with entering data themselves the virtual ward are able to telephone the patient and input the data on their behalf.

Throughout the crisis, a series of ad hoc pilots have been conducted using oximeters and apps (namely the Huma Medopad app) to monitor at home. These pilot sites were disparate and uncoordinated, therefore NHSD have come in to collect data from those pilots so that it can be analysed retrospectively. The role of Imperial College is to access data collected from pilot sites for retrospective analysis and they have also developed a trial protocol and minimum dataset requirements for collecting prospective data. There are 3500 patients that will be included in the retrospective analysis and the prospective analysis cohort is unlikely to exceed 300 patients.

The COVID-19 National Incident Response Board (NIRB) have approved three pilots in London, Slough and South Tees. This has been established to ensure an evaluation can take place. It is recognised there are other initiatives across the country and the programme will look to maximise data from all locations. These are called Communities of Practice.

Tees Valley

Population size 700,000. NHS Tees Valley CCG. Mixed urban & rural with a complex health and care environment that gives the option of assessing scalability of the model to a large population. The Tees Valley has seen some of the highest COVID-19 infection rates in the country; with a rate of 484 per 100,000 population in Middlesbrough; twice the national average in May 2020

Slough

Population coverage 172,000. 4 PCNs. 54% BAME population, most diverse in the UK. 27% don’t speak English and 15.5% have no one in the household speaking English. High deprivation (over 50% fall in deciles 2-4, high population density, multigenerational and larger households (so shielded patients living alongside non-shielded). High Covid-19 rates and high transmission rates.

North West London (also a community of practice)

Allows further assessment in a metropolitan area

Imperial College have developed the Data Set. They are leading on the evaluation to inform the NHS England decision making on whether a national programme should be mandated and run centrally.

NHSX are leading on a procurement platform based on their experience with MedoPad (Huma) pilot. This would provide a platform for the NHS to buy equipment required if there is a national roll out. National roll out will not be determined until the results of the pilot are made available and analysed. NHS X are not part of this data sharing agreement, they will be involved in some follow up work should the pilot be successful and it's deemed that the NHS needs to buy equipment to facilitate use of these monitoring apps.

The purpose of the data request described in this agreement is to determine the value and viability of using virtual wards for Covid-19 patients from a clinical, administrative and cost effectiveness perspective. In order to achieve this, there are four specific service evaluation objectives:

1. To roll out the use of virtual wards in a selected location for symptomatic COVID-19 suspected or swab positive patients

2. Integrated retrospective analysis of quantitative outcomes for previous pilot virtual ward/remote community monitoring observational trials across the UK. These will be applied as a source for power analysis and prioritisation of primary trial outcomes.

3. To use quantitative data returned from remote monitoring devices and routinely collected health data to determine whether virtual wards improve clinical outcomes, healthcare utilisation and cost effectiveness as compared to traditional pathways

4. To determine the optimal thresholds for referral to hospital across different patient groups

5. To gather qualitative insights from clinicians and patients involved in virtual wards to assess their viability for future roll out.

The study design tests the effectiveness of the new care pathway of virtual wards site for healthcare delivery for individuals suspected of COVID-19. Furthermore, questionnaires and semi-structured interviews of participants will provide insight into wider implementation of this technology and provide feedback for improvements; semi-structured interviews of staff will provide a healthcare perspective, particularly thoughts on reducing potential infection risk through remote monitoring services.

The study population comprises patients managed on a pilot virtual ward/remote community monitoring observational trial for proven or suspected high-risk of COVID-19 between March 2020 and July 2020.

Setting

The evaluation will be conducted in community regions (such as in London, Slough, South Tees and the North of England) as a continuation of established pilots in association with NHS Digital and the NHS@Home programme.

Participants:

Eligible individuals (i.e. those suspected of COVID-19) will be identified by general practitioners, emergency department teams, or 111 staff for study participation.

The data collection and analysis will enable several key service evaluation questions to be answered.

• Which patients should be in a virtual ward based on risk factors and initial physiological readings?

• How long should they be monitored for and how frequently?

• What are the thresholds for admission to hospital or stopping monitoring?

• Does it work? i.e. improve outcomes and/or reduce length of stay, long-term disability

Once these key service evaluation questions are explored the outputs will be used to inform a decision on national roll out. Early indications are that virtual wards could reduce mortality and/or reduce length of stay in hospital.

The Virtual Wards dataset encompasses a cut of General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR data). This data has had the Type 1 Objections applied to it before it was released to NHS Digital. That objection will continue to be upheld when the dataset is made available as part of the Virtual Wards Dataset as part of the dissemination from NHS Digital to Imperial College London.

Imperial College London and NHS England are joint data controllers for this project.

All results will be published at aggregate level with small number suppression and in accordance with NHS Digital’s usual statistical disclosure control practices.

The principle output is Imperial College London's evaluation - provided to NERVTAG (New and Emerging Respiratory Virus Threats Advisory Group) to enable them to evaluate whether a national programme should be mandated and run centrally.

Reports on the uptake and effectiveness of the intervention will be presented to internal NHS stakeholders as part of Imperial College London's role as their evaluation partner.

Academic articles describing the uptake and effectiveness of a remote monitoring programme will be submitted to leading peer reviewed journals (e.g. BMJ).

Results will also be disseminated in internal and external academic meetings and shared with other learned bodies. Similarly, only aggregate data with small number suppression will be used.

Findings will be reported in 1-2 peer-reviewed journal publications. These publications would have an academic audience and include findings from the analysis and evaluation of Virtual Wards. Publications would be made open-access to ensure dissemination of learning from this analysis.

Community-based Virtual Electronic Wards for remote monitoring in suspected cases of COVID-19 (coronavirus): C-VIEW Study.

The pandemic of SARS-CoV-2 (coronavirus, COVID-19) remains a global health problem; to date over 9,277,214 cases have been reported across 216 countries with 478,691 deaths by the World Health Organisation (https://covid19.who.int/. Published 2020. Accessed June 25, 2020). Within in the United Kingdom (UK), 307,980 cases with 43,230 deaths have been reported (https://www.gov.uk/guidance/coronavirus-covid-19-information-for-the-public. Published June 25, 2020. Accessed June 25, 2020). This undoubtedly has stretched resources, created pressures within the National Health Service (NHS) and accelerated a change of how hospitals operate in preparation for efficacious resource management.

Vital signs trends (oxygen saturations, heart rate, respiratory rate, blood pressure, temperature) are routinely used for monitoring hospital patients. Clinical deterioration may be recognised through changes in these parameters, and often precedes an adverse event. The rate of deterioration for individuals suffering with COVID-19 remains an unknown entity; given that novel digital technologies have enabled remote monitoring solutions, ‘virtual wards’ may provide a safe strategy for approaching this pandemic in appropriately selected patient groups.

Virtual wards can be established to manage patients remotely, freeing up staff, avoiding overwhelming hospitals, and reducing patient anxiety by allowing recovery at home. Healthcare professionals in virtual wards can track vital signs of those suspected of COVID-19, in near real-time, receiving alerts for clinical deterioration. Pulse oximeters combined with digital innovation (i.e. mobile applications) allow for systems to recognise early deterioration in vital parameters and self-reported symptoms, supporting clinical decision making. Indeed, pilot work trialling the virtual model demonstrated a saving of 300 bed spaces over a three week period.

The Institute of Global Health Innovation (IGHI) at Imperial College London (ICL) are supporting a programme of urgent COVID-19 work regarding new pathways of care for COVID-19 patients. The work will explore the value of a new care pathway using virtual wards with remote monitoring in suspected cases of COVID-19 in the community to improve

1) health resource utilisation (e.g. hospital admissions, ITU admissions),

2) clinical outcomes and

3) cost-effectiveness through early detection of clinical deterioration.

The work is led by NHS England (NHSE) with NHS Digital assisting on data set provision.

NHS England have a programme called NHS@Home, part of which has been asked to trial a remote monitoring pathway for COVID-19 patients. The NHS@Home programme is summarised below:

NHS @home provides an important opportunity to enhance NHS services, utilising the best technologies available to enable personalised clinical support to be delivered virtually to people in the setting of their own home including care homes.

Who the programme targets/ is open to

The initial activities are focusing on three groups, in response to the pandemic and to assist preparations for this winter:

• Group A – All care home residents

• Group B - Deteriorating COVID-19 patients, initially at 2-3 pilot sites, building on work of various other community of practice sites and aligned with work taking place with 8 sites separately, supported by NHS X

• Group C - People identified as higher risk of COVID19, including initially:

- People with a learning disability and diabetes (reaching 3000 people)

- Respiratory conditions (scoping use of peak flow meters to support people with asthma and COPD)

- People with heart failure (initially within 3 STPs, providing self-management support)

- Hypertension (22,000 blood pressure monitors to be distributed)

- Support for 5000 unpaid carers of those with learning disabilities to recognise early deterioration of COVID-19 (scope could be widened)

Group B is the focus of this agreement.

For Group B, the uptake/aims of the project are to pilot virtual wards as a way to manage COVID19 patients in the community through remote monitoring, with the aim of reducing hospital and intensive care stay, and patient mortality. This involves home oximetry monitoring, wearable sensors, medical diary apps and/or phone calls from clinicians to patients – essentially a variety of approaches to monitoring COVID-19 patients at home, referring them into the appropriate health service when needed and avoiding deterioration in the community. There are a number of measures in place to help patients with the remote monitoring and for those who have difficulty with entering data themselves the virtual ward are able to telephone the patient and input the data on their behalf.

Throughout the crisis, a series of ad hoc pilots have been conducted using oximeters and apps (namely the Huma Medopad app) to monitor at home. These pilot sites were disparate and uncoordinated, therefore NHSD have come in to collect data from those pilots so that it can be analysed retrospectively. The role of Imperial College is to access data collected from pilot sites for retrospective analysis and they have also developed a trial protocol and minimum dataset requirements for collecting prospective data. There are 3500 patients that will be included in the retrospective analysis and the prospective analysis cohort is unlikely to exceed 300 patients.

The COVID-19 National Incident Response Board (NIRB) have approved three pilots in London, Slough and South Tees. This has been established to ensure an evaluation can take place. It is recognised there are other initiatives across the country and the programme will look to maximise data from all locations. These are called Communities of Practice.

Tees Valley

Population size 700,000. NHS Tees Valley CCG. Mixed urban & rural with a complex health and care environment that gives the option of assessing scalability of the model to a large population. The Tees Valley has seen some of the highest COVID-19 infection rates in the country; with a rate of 484 per 100,000 population in Middlesbrough; twice the national average in May 2020

Slough

Population coverage 172,000. 4 PCNs. 54% BAME population, most diverse in the UK. 27% don’t speak English and 15.5% have no one in the household speaking English. High deprivation (over 50% fall in deciles 2-4, high population density, multigenerational and larger households (so shielded patients living alongside non-shielded). High Covid-19 rates and high transmission rates.

North West London (also a community of practice)

Allows further assessment in a metropolitan area

Imperial College have developed the Data Set. They are leading on the evaluation to inform the NHS England decision making on whether a national programme should be mandated and run centrally.

NHSX are leading on a procurement platform based on their experience with MedoPad (Huma) pilot. This would provide a platform for the NHS to buy equipment required if there is a national roll out. National roll out will not be determined until the results of the pilot are made available and analysed. NHS X are not part of this data sharing agreement, they will be involved in some follow up work should the pilot be successful and it's deemed that the NHS needs to buy equipment to facilitate use of these monitoring apps.

The purpose of the data request described in this agreement is to determine the value and viability of using virtual wards for Covid-19 patients from a clinical, administrative and cost effectiveness perspective. In order to achieve this, there are four specific service evaluation objectives:

1. To roll out the use of virtual wards in a selected location for symptomatic COVID-19 suspected or swab positive patients

2. Integrated retrospective analysis of quantitative outcomes for previous pilot virtual ward/remote community monitoring observational trials across the UK. These will be applied as a source for power analysis and prioritisation of primary trial outcomes.

3. To use quantitative data returned from remote monitoring devices and routinely collected health data to determine whether virtual wards improve clinical outcomes, healthcare utilisation and cost effectiveness as compared to traditional pathways

4. To determine the optimal thresholds for referral to hospital across different patient groups

5. To gather qualitative insights from clinicians and patients involved in virtual wards to assess their viability for future roll out.

The study design tests the effectiveness of the new care pathway of virtual wards site for healthcare delivery for individuals suspected of COVID-19. Furthermore, questionnaires and semi-structured interviews of participants will provide insight into wider implementation of this technology and provide feedback for improvements; semi-structured interviews of staff will provide a healthcare perspective, particularly thoughts on reducing potential infection risk through remote monitoring services.

The study population comprises patients managed on a pilot virtual ward/remote community monitoring observational trial for proven or suspected high-risk of COVID-19 between March 2020 and July 2020.

Setting

The evaluation will be conducted in community regions (such as in London, Slough, South Tees and the North of England) as a continuation of established pilots in association with NHS Digital and the NHS@Home programme.

Participants:

Eligible individuals (i.e. those suspected of COVID-19) will be identified by general practitioners, emergency department teams, or 111 staff for study participation.

The data collection and analysis will enable several key service evaluation questions to be answered.

• Which patients should be in a virtual ward based on risk factors and initial physiological readings?

• How long should they be monitored for and how frequently?

• What are the thresholds for admission to hospital or stopping monitoring?

• Does it work? i.e. improve outcomes and/or reduce length of stay, long-term disability

Once these key service evaluation questions are explored the outputs will be used to inform a decision on national roll out. Early indications are that virtual wards could reduce mortality and/or reduce length of stay in hospital.

The Virtual Wards dataset that will be provided in the Trusted Research Environment by NHS Digital encompasses a cut of General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR data). This data has had the Type 1 Objections applied to it before it was released to NHS Digital. That objection will continue to be upheld when the dataset is made available in the DAE as part of the Virtual Wards Dataset.

Imperial College London and NHS England are joint data controllers for this project.

All results will be published at aggregate level with small number suppression and in accordance with NHS Digital’s usual statistical disclosure control practices.

The principle output is Imperial College London's evaluation - provided to NERVTAG (New and Emerging Respiratory Virus Threats Advisory Group) to enable them to evaluate whether a national programme should be mandated and run centrally.

Reports on the uptake and effectiveness of the intervention will be presented to internal NHS stakeholders as part of Imperial College London's role as their evaluation partner.

Academic articles describing the uptake and effectiveness of a remote monitoring programme will be submitted to leading peer reviewed journals (e.g. BMJ).

Results will also be disseminated in internal and external academic meetings and shared with other learned bodies. Similarly, only aggregate data with small number suppression will be used.

Findings will be reported in 1-2 peer-reviewed journal publications. These publications would have an academic audience and include findings from the analysis and evaluation of Virtual Wards. Publications would be made open-access to ensure dissemination of learning from this analysis.

Yielded Benefits is not a requirement for new applications.