The programme aims to utilise the UK’s substantial health and health-related data assets such as Electronic Health Records, to assess how acute inflammatory episodes affect people’s quality of life and the financial strain they place on the healthcare system. This in turn will provide key policy and clinical insights that will improve respiratory outcomes for the UK’s population. 

Key objectives include mapping the distribution of respiratory and allergic diseases nationwide (such as Asthma and COPD), analysing healthcare usage and outcomes for these conditions, identifying ways to reduce health inequalities over the short and medium term, developing advanced prediction tools to better forecast risks, and evaluating the effectiveness of these strategies through large-scale clinical trials across the UK.  

The goal is to improve health outcomes by addressing resource allocation more effectively and targeting interventions where needed most.  

This approach emphasizes a comprehensive understanding of inflammation’s role in common conditions and aims to enhance healthcare systems’ ability to support affected populations efficiently and how we may use the learnings, datasets and tools created and apply them to other respiratory conditions in the future. 

 

Programme Co- Leads

Sir Aziz Sheikh 

Jennifer Quint 


Respiratory conditions still unnecessarily blight and claim the lives of far too many people in the UK and globally.  We aim to utilise the UK’s outstanding health and health-related data asset, and work with members of the public, colleagues and partners across the UK, to provide key policy and clinical insights that will improve respiratory outcomes for the UK’s population. We will then take the insights from these experiences in respiratory medicine and use these to catalyse similar improvements for other inflammatory and immune-mediated conditions.”  Professor Sir Aziz Sheikh, Professor of Primary Care Research & Development and Director of the Usher Institute at The University of Edinburgh

 

This is a fantastic opportunity to improve the quality of data recording and use of data to better respiratory outcomes for people in the UK and to expand this learning to other diseases which will ultimately be included in the Inflammation and Immunity driver programme.
Professor Jennifer Quint, Professor of Respiratory Epidemiology at Imperial College London

    • Develop whole-system capacity to map the epidemiology, healthcare utilisation, and outcomes for common allergic and respiratory conditions for each of the UK nations. 
    • Map variations in care processes and health outcomes and identify opportunities for reducing these inequalities in the short- and medium-term. 
    • Develop and validate next-generation risk prediction algorithms to improve health outcomes and reduce inequalities. 
    • Evaluate the effectiveness, cost-effectiveness, and impact of these algorithms through large-scale UK-wide clinical trials. 
    • Share outputs, within the community of practice for data science and connect this work with wider global respiratory research efforts to knowledge share. 

Workstreams

  1. Descriptive Epidemiology
  2. Prediction
  3. Evaluation and Intervention

Activities

  • Generate robust and transparent methodology for disease phenotypes and trajectories such as asthma, Chronic Obstructive Pulmonary Disease (COPD), and other respiratory diseases using health data
  • Describe incidence, prevalence, health utility, outcomes, and cost across the four nations in the UK, including understanding of health inequalities, socio-economic status
  • Sex differences in chronic respiratory disease
  • Extend learnings from respiratory disease research into other areas of inflammation and immunity
  • Develop predictive algorithms with a focus on treatable traits
  • Explore novel data linkages like household and meteorological data for improved risk prediction.
  • Hold regular training and research webinars to support early career researchers
  • Provide meaningful Patient and Public Involvement and Engagement (PPIE) across all projects to build trust and transparency in working with health data
  • Seek improved data access, data quality, and cost-effectiveness through standardised cohort creation for researchers.

Outputs