He added: “We’re investigating the effectiveness of interventions like support for energy bills on the health of young people by using Artificial Intelligence to digitally mimic their household environments and evaluate the impact of simulated interventions. This will help guide future policy changes to improve health conditions, reduce inequalities, and in turn reduce pressures on NHS services.”

Other projects include studies aiming to ease pressures on emergency services by using hospital data to speed up patient flow through and out of emergency departments, as well as a project using an analysis approach called ‘machine learning’ to predict peaks of infection with the common bug, Respiratory Syncytial Virus (RSV), that can cause serious illness in young children and put pressure on paediatric intensive care units.

Professor Cathie Sudlow, Chief Scientist at HDR UK said: “By using existing data, research teams, and infrastructure these projects are able to respond rapidly to evolving pressures on the NHS. Within three months, they will have honed in on key pain points in the health service, and developed evidence-led recommendations on how best to manage resources and prevent unnecessary illness through the winter.”

Each project is designed to generate findings in just a few months so that they can be implemented for future winters. After being selected in December 2022, the studies will start in January, produce results by the end of March, and publish their findings later this year.

The research is possible thanks to the improved health data infrastructure that was developed during the COVID-19 pandemic, partly led by HDR UK with the support of UKRI and partners across the sector, to enable access to data faster, more securely and at a greater scale than has been previously possible.

Mr Tianyi Liu

Contact details

Research

Research

Digital Health

Research

Digital Health

Based in