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New technology to identify people at high risk from COVID

New technology has been introduced in England to help clinicians identify, for the first time, a new group of people who may be at high risk from COVID-19.

Over 800,000 adults will now be prioritised to receive a vaccine as part of the current vaccination cohorts. The technology analyses a combination of risk factors based on medical records, to assess whether somebody may be more vulnerable than was previously understood, helping clinicians provide vaccination more quickly to them and ensuring patients can benefit from additional advice and support.

This assessment is made possible with new technology and emerging evidence about the impact of COVID-19 on different groups and who could be most vulnerable – which means further steps can be taken to protect those most at risk.

The research, commissioned by England’s Chief Medical Officer, Chris Whitty, and funded by the National Institute of Health Research, found there are several health and personal factors, such as age, ethnicity and body mass index (BMI), as well as certain medical conditions and treatments, which, when combined, could mean someone is at a higher risk from COVID-19.

The University of Oxford turned their research into a risk-prediction model called QCovid, which has been independently validated by the Office for National Statistics (ONS).

NHS Digital used the University of Oxford’s model to develop a population risk assessment. The risk assessment uses the model to predict on a population basis whether adults with a combination of risk factors may be at more serious risk from COVID-19, enabling them to be flagged to clinicians for priority access to vaccination, alongside appropriate advice and support. These individuals will be added to the Shielded Patient List on a precautionary basis and to enable rapid vaccination.

The research to develop and validate the model is published in the British Medical Journal along with the underlying model for transparency. Additional code underpinning the QCovid model will be made available openly by the University of Oxford within a month. As scientific understanding of the virus develops, the model will be updated.

Up to 1.7 million patients have been identified. Those within this group who are over 70 will have already been invited for vaccination and 820,000 adults between 19 and 69 years will now be prioritised for a vaccination.

The patients identified through the risk assessment will be sent a letter from NHS England explaining that their risk factors may help identify them as high clinical risk and that they are included within the support and advice for the clinically extremely vulnerable. They will be invited to receive a COVID-19 vaccine as soon as possible if they have not already had the jab, and will be given advice on precautionary measures, including shielding where this is current advice. Their GPs are also being notified.

Deputy Chief Medical Officer for England Dr Jenny Harries said: "For the first time, we are able to go even further in protecting the most vulnerable in our communities. This new model is a tribute to our health and technology researchers. The model’s data-driven approach to medical risk assessment will help the NHS identify further individuals who may be at high risk from COVID-19 due to a combination of personal and health factors.

"This action ensures those most vulnerable to COVID-19 can benefit from both the protection that vaccines provide, and from enhanced advice, including shielding and support, if they choose it."

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Upcoming Events

AfPP Annual Conference 2022

University of York
8-11 September 2022

Infection 360: What's trending in infection prevention & control

Edgbaston Stadium, Birmingham
27-28 September 2022

IP2022 IS COMING TO BOURNEMOUTH IN OCTOBER 2022

Bournemouth
17-19 October 2022

UKHCA Conference: Listen Up

Pendulum Hotel and Manchester Conference Centre, Manchester
3rd November 2022

MEDICA 2022

Dusseldorf Germany
14th November - 17th November

Future Surgery 2022

ExCel, London
15th - 16th November 2022

Access the latest issue of Clinical Services Journal on your mobile device together with an archive of back issues.

Download the FREE Clinical Services Journal app from your device's App store

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