Samuel Relins – Project I

Children’s Urgent Care Provided in the Right Place Every Time

Bradford is home to one of the country’s leading hospital-at-home services – the Ambulatory Care Experience or ACE. Children suffering with health problems, that may traditionally have been admitted to a hospital ward, can instead receive treatment at home. The familiar household setting reduces anxiety for child and parent and frees up much needed space and resources in hospitals.

Choosing the correct treatment setting for each child is of great importance. A child admitted to hospital that could be treated at home is a waste of vital resources and a source of unnecessary anxiety.  A child referred for home treatment that later returns for a hospital stay is a complication that should be avoided. The traditional clinical factors used to assign patients to the service have made ACE a great success, but there is some scope for improvement.

This project aims to use data analysis and machine learning to increase the accuracy of referrals and better inform decision making within ACE. The service has collected a wealth of information that has the potential to identify key factors that predict successful treatment at home. Using carefully anonymised data, collected at the time a child is referred to the service, modern statistical methods can be used predict the most suitable treatment setting. A particular focus is to produce an accurate model that can not only predict the likelihood of successful treatment in the ACE service, but also the level of confidence (or lack thereof) in this prediction. This information can then be provided as a tool to clinicians, to aid them in making the best referral decision for every patient every time.