Model that predicts patient risk from COVID-19 wins Florence Nightingale Award for Excellence in Healthcare Data Analytics

The winner of the Florence Nightingale Award for Excellence in Healthcare Data Analytics 2021, jointly awarded by the Health Foundation and the Royal Statistical Society, has today been announced. Now in its second year, the award recognises practitioners in applied health care data analytics who have gone the extra mile in delivering innovative improvements for the health care system.

This year’s award has been given to the COVID-19 Population Risk Assessment team, for their COVID-19 Population Risk Assessment predictive model powered by QCovid®.¹ 

This cross-organisational team produced QCovid, a predictive mode which combines characteristics such as age, ethnicity, gender and deprivation from a number of national datasets to estimate an individual’s risk of catching and then being hospitalised or dying from COVID-19. QCovid was rolled out over every adult in England and it has been running regularly since March 2020. Thanks to this programme, at-risk adults in England could be identified, prioritised for vaccination and added to the national ‘Shielded Patients List’.

Adam Steventon, Director of Data Analytics at the Health Foundation, said: 

‘The pandemic continues to highlight the critical role that data and analytics increasingly play in protecting and improving the health of everybody in our society. The COVID19 Population Risk Assessment team’s work powerfully demonstrates that high quality analytics can make a real difference to patients' lives on a national scale. The level of collaboration, careful navigation of obstacles and the focus on addressing health inequalities on this project are outstanding.’

Stian Westlake, Chief Executive of the Royal Statistical Society, added:

‘Healthcare data analysts across the UK have risen to the numerous challenges and obstacles brought by the COVID-19 pandemic – working responsively, collaboratively and openly together. Congratulations to the winners who have really shown how their work can make a difference to patient outcomes.’

More information

The COVID-19 Population Risk Assessment team includes members from the Department of Health and Social Care, NHS Digital, NHS England, the Office for National Statistics, Public Health England, University of Oxford, NERVTAG, Oxford University Innovations, and the Winton Centre for Risk and Evidence Communication.

Two projects were highly commended: 

• The Big Data Institute (BDI) and Queen’s College, Oxford University - ‘Responsive and timely modelling of the COVID-19 pandemic to inform improved response’
  
  Dr Panovska-Griffiths led a cross-institutional, multi-disciplinary and international group that used data analytics and modelling to inform the response to the pandemic. It was considered an incredibly strong submission for this award. Her modelling work has informed important policy decisions, such as the need for pupils to wear masks when schools reopened in England in early 2021. The judges were impressed by the excellent engagement with individuals across the international healthcare field and a responsive approach to including new, open datasets.  
   
• Bristol, North Somerset and South Gloucestershire Mass Vaccination Programme team (BNSSG) – ‘A system-wide approach to improving COVID-19 vaccines uptake’
  
  Uptake analysis has been crucial to the vaccine roll-out, and the BNSSG team went above and beyond to gain a better understanding of groups less likely to come forward for a vaccine. The data was presented in accessible formats to aid better decision-making and is an outstanding example of analysis as a tool to examine health inequalities. The team made a concerted effort to creatively engage with faith and community leaders as well as healthcare professionals to successfully improve vaccine coverage.

Media contact

Simon Perry

Simon.Perry@health.org.uk

020 7257 2093