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Predicting and preventing asthma attacks in children

Asthma is the commonest chronic childhood condition, affecting 1 in 11 children, acute asthma attacks remain a leading cause of unplanned hospital admissions, emergency visits and missed schooldays. Early recognition and management of deterioration in asthma control can prevent attacks and emergencies. The challenge underpinning this unmet need is the inability to detect the signs of deterioration objectively and early at home. 

Albus Health (BreatheOx Limited) have invented a small non-contact table-top device and associated AI algorithms that automatically monitor a range of physiological and environmental metrics without requiring patients to do or wear anything. The device collects objective, continuous and long-term data on a range of physiological symptoms, living conditions and outer environment. 

In this project, we are implementing this innovative monitoring and prediction technology for children. Our objectives include demonstrating value in NHS care pathways by deploying the system within existing NHS infrastructure and generating real-world evidence of clinical and economic value. 

To ensure efficient planning, management and delivery, our project team includes Albus Health (Oxford University med-tech spinout company), Birmingham Women’s and Children’s Hospital NHS Trust (one of the busiest UK paediatric asthma centres), Imperial College London (largest UK paediatric severe asthma translational research programme), Asthma UK, and Oxford AHSN. This independent research is funded by the National Institute for Health Research (Artificial Intelligence, Prediction and Prevention of Asthma attacks in Children, AI_AWARD02005) and NHSX. 


Case study

Evaluation assesses home monitoring device which uses AI to predict and prevent asthma attacks in children