NHS Digital has been awarded the Florence Nightingale Award for Excellence in Healthcare Data Analytics by the Royal Statistical Society for its work as part of a cross-sector team, that helped to identify those most vulnerable to COVID-19 and prioritise them for vaccination1.
The work involved collaborating with some of the country’s leading academic clinicians and epidemiologists who had studied the anonymised health records of more than 8 million people using GP records, hospital records and mortality data to create a risk prediction model called QCovid®.
NHS Digital then built a specialised data platform that could apply that statistical model to all patient records, and identified a further 1.5 million people most at risk from becoming seriously ill or dying from coronavirus, so that they could shield.
The project involved access to a range of crucial patient data: aligning hospital, cancer and demographic datasets with the GP records that proved instrumental in allowing the team to then pinpoint those at risk with much greater precision, using the QCovid® model.
This achievement has now been recognised by the Royal Statistical Society, a world-leading organisation who advocate for the importance of statistics and data.
Stephen Koch, Executive Director of Platforms for NHS Digital said: “This was an extremely complex and challenging piece of work to complete in just nine months, but we have proven how using population data in a safe, controlled and effective way can both translate into better outcomes for patients and save lives.
“Collaboration was key to the success of this endeavour – it simply would not have been possible without bringing together the brightest minds across government and academia.
“I am extremely proud of our team. It is such a huge achievement to be recognised by such a prestigious organisation and a testament to how we respect, manage and use data to benefit patients.”
Stian Westlake, Chief Executive at the Royal Statistical Society said: “On behalf of the judging panel, I would like to offer my congratulations on this excellent piece of work.
“It was clear that protecting the vulnerable from devastating health inequality was at the very heart of this project; the measures taken to account for data quality and completeness were considered and comprehensive.
“This project has showcased the value of quality analysis at a nationwide scale. The collaborative spirit, concerted effort and careful consideration of obstacles are all outstanding.”
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