More people at high risk from COVID-19 received priority access to vaccines thanks to research conducted by the University of Oxford using the QResearch database – a not-for-profit initiative between the university and EMIS.
Using QResearch, a database of more than over 35 million anonymised health records derived from GP practices using the EMIS clinical computer system, researchers at the University of Oxford and the New and Emerging Respiratory Virus Threats Advisory Group (NERVTAG) developed a population-wide risk assessment model called QCovid.
The research was commissioned by England’s Chief Medical Officer Chris Whitty and funded by the National Institute of Health Research. It found that there are several health and personal factors which, when combined, could mean someone is at a higher risk from COVID-19. These include characteristics like age, ethnicity and body mass index, as well as certain medical conditions and treatments.
As a result, in February 1.5m high risk individuals were identified, added to the Shielded Patient List as a precautionary measure and prioritised for earlier vaccination. The research also played a vital role in raising public awareness of key COVID-19 risk factors. “
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 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.”
Sarah Wilkinson, chief executive of NHS Digital said: “I’m very pleased that NHS Digital has been able to deliver the platform to allow the QCovid model to be used to identify individuals vulnerable to COVID-19 as a result of combinations of clinical risk factors and personal characteristics.
“This extends the work we did last year to develop the Shielded Patients List, which included individuals with one of a number of specific clinical conditions.
“It is a privilege to be able to support the chief medical officer and his team in their quest to deliver the most sophisticated COVID-19 risk prediction capability.”
Developing the QCovid model
The QCovid model was developed using anonymised data for more than 8 million adults from the QResearch database, which uses anonymised patient data contributed by GPs using EMIS systems. The research to develop and validate the model is published in the British Medical Journal.
Professor Julia Hippisley-Cox, professor of clinical epidemiology and general practice at the University of Oxford, said: “
“The QCovid model, which has been developed using anonymised data from more than eight million adults, provides nuanced assessment of risk by taking into account a number of different factors that are cumulatively used to estimate risk, including ethnicity.
“The research to develop and validate the model is published in the British Medical Journal along with the underlying model for transparency. This will be updated to take account of new information as the pandemic progresses."
“I’m delighted that less than six months after being published, the model is now being used to help protect people at most risk from COVID-19.”
Dr Shaun O’Hanlon, Chief Medical Officer at EMIS, said: “EMIS is proud to have supported this important piece of research, which will enable the NHS to protect more vulnerable people, more quickly, from COVID-19.
“We thank all of the GP practices who have contributed anonymised patient data to the QResearch database over the 15 years it has been in existence. To be able to create this new risk model for COVID-19 less than a year since the start of the pandemic is a truly fantastic achievement.”