The National Institute for Health Research (NIHR) has published a case study on QCOVID, a clinical risk prediction model, which has played a key role during the COVID-19 pandemic in identifying those people at greatest risk.
QCOVID, developed with support from the NIHR Oxford Biomedical Research Centre, has proved an important tool to determine which groups should be prioritised for vaccination.
The tool was developed by a team led by Professor Julia Hippisley-Cox, Professor of Clinical Epidemiology and General Practice at the University of Oxford, after the Chief Medical Officer commissioned them to find a way of predicting patient groups most at risk of serious outcomes from COVID-19 infection.
They began with an analysis of a pre-existing database of more than 8 million people. This included pseudonymised GP records, hospital records, COVID-19 test results and death registrations corresponding to the first wave of the pandemic.
The researchers planned to identify which combinations of health and personal factors put patients at greater risk of hospital admission or dying from COVID-19 infection, so they considered characteristics such as age, gender, ethnicity and body mass index. They also looked at the effects of certain treatments and medical conditions, including cardiovascular disease, diabetes, respiratory disease and cancer.
Using its findings, they developed a clinical risk prediction model, QCovid, which performed well in predicting patients’ outcomes, with those identified by the model to be in the top 5% for predicted risk of death accounting for approximately 76% of actual COVID-19 deaths during the study period, and people in the top 20% accounting for 94% of COVID-19 deaths.
Professor Hippisley-Cox (pictured left) said: “Our population-based risk model has broken new ground by identifying the patients at highest risk of COVID-related death and hospital admission, so that the NHS can target resources to the most vulnerable and those most likely to benefit. It really demonstrates the value of having a cross-partnership team of multiple specialities in delivering innovative research and improvements for the healthcare system.”
QCOVID has been independently validated by the Office for National Statistics, confirming that the model performs in the ‘excellent’ range. It is thought to be the only COVID-19 risk prediction model in the world to meet this standard. QCOVID has also been validated for use in Scotland and Wales.
Less than a year after the research project began, QCOVID was used by NHS Digital to develop the COVID-19 Population Risk Assessment, which was used to identify people not already included on the Shielded Patient List (SPL) who might be at high risk of dying from COVID-19 infection. QCovid identified a further 1.7 million people at high risk who were added to the SPL and advised to shield. This included 820,000 adults aged 19–69 years who were prioritised for vaccination.
As the former Deputy Chief Medical Officer for England and Chief Executive of the Health Security Agency Dr Jenny Harries said: “For the first time, we are able to go even further in protecting the most vulnerable in our communities.
“This 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.”
NHS Digital also used QCovid to produce the COVID-19 Clinical Risk Assessment Tool, to help clinicians review individual patients’ risk level and add or remove them from the SPL as required.
As the COVID-19 vaccination programme was rolled out in the UK, the QCovid team were commissioned by the Chief Medical Officer to develop new risk scores to predict people’s risk of hospital admission or dying from COVID-19 after receiving either one or two doses of vaccine.
The team’s findings indicated that people receiving treatment for cancer or autoimmune disorders, care home residents and those with HIV/AIDS or neurological disorders were among those who remained at higher risk of hospitalisation or death from COVID-19 after one or two vaccine doses.
NHS Digital subsequently updated the Clinical Risk Assessment Tool to include this new evidence.