A clinical risk prediction model that will allow healthcare professionals to identify patients who are at higher risk of serious illness from coronavirus is being developed by researchers.
A team from Oxford University, in conjunction with NHS Digital, is leading on the project which could support GPs and other clinicians to provide advice that is tailored to the individual patient during consultations. Algorithms from data provided by NHS Digital will be created to build the prediction model.
NHS Digital said the model could also be “used to inform mathematical modelling of the potential impact of national public health policies on shielding and preventing infection” and also “help identify those at highest risk to be vaccinated".
NHS Digital said it was unclear at this stage how pharmacies would be able to access and use the tool.
Professor Jonathan Benger, interim chief medical officer at NHS Digital, said: "NHS Digital is delighted to use our data expertise to contribute to this hugely important piece of work. This is a comprehensive analysis of large patient data sets that will provide policy makers with high quality, evidence-led insights."
Julia Hippisley-Cox, professor of epidemiology and general practice at the University of Oxford’s Nuffield Department of Primary Care Health Sciences, said: "Driven by real patient data, this risk assessment tool could enable a more sophisticated approach to identifying and managing those most at risk of infection and more serious Covid-19 disease.
"Importantly, it will provide better information for GPs to identify and verify individuals in the community who, in consultation with their doctor, may take steps to reduce their risk, or may be advised to shield."