The 'risk prediction' model will help GPs work out if someone should be shielding.
Clinicians and GPs will soon be able to better identify patients who are at a higher risk of serious illness from the coronavirus.
An Oxford-led team is working with a number of other universities to develop a new data-driven risk prediction model.
The aim is to help specialists provide more targeted advice on shielding, based on individual levels of risk.
Julia Hippisley-Cox, Professor of Epidemiology and General Practice at 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.’
The model could also be used to inform mathematical modelling of the potential impact of national public health policies on shielding, and potentially help identify those at highest risk to be vaccinated, once a jab is available.
It will use the anonymized electronic health records of 8 million adults in the UK, to identify factors that can be used to predict those at highest risk of infection and serious illness from COVID-19. That includes age, sex, ethnicity, deprivation, smoking status and pre-existing medical conditions.
Algorithms from the data analysis will be developed in conjunction with clinical and data experts at NHS Digital to create the risk prediction tool.
Professor Keith Channon, Deputy Head of Medical Sciences and Director of Oxford Academic Health Partners, said: ‘Combining leading expertise in clinical epidemiology and analytical techniques with very large sets of NHS clinical data to develop this new tool illustrates the power of our University and NHS researchers working together, to benefit people at risk of COVID-19.’
The project was a commission from the Office of the Chief Medical Officer for England to NERVTAG (New and Emerging Respiratory Virus Threats Advisory Group), who established the parameters and brought together the team as a sub-group of NERVTAG.
Chief Medical Officer for England, Professor Chris Whitty, said: ‘The level of threat posed by COVID-19 varies across the population, and as more is learned about the disease and the risk factors involved, we can start to make risk assessment more nuanced.
'When developed, this risk prediction tool will improve our ability to target shielding, if it is needed, to those most at risk.’
The research is funded by the National Institute for Health Research Oxford Biomedical Research Centre, and the University of Oxford COVID-19 Rapid Response Fund with support from Wellcome and Cancer Research UK.