Kettering General Hospital is preparing to deploy an AI system to support the allocation of beds to patients.
It has completed a proof of concept supported by the Accelerated Capability Environment (ACE) and is now planning to run user testing then integrate the system with others, notable for patient administration, incorporating all speciality treatments, wards and bed types.
The proof of concept, which has been published on the NHS England GitHub Repository, was run with Faculty.ai – one of the Vivace community of organisations that contributes to ACE – and involved senior clinical and administrative staff from Kettering General. It was completed in 14 weeks.
ACE said this has provided a patient flow tool built around a virtual hospital environment modelled on a selection of Kettering General’s wards.
It uses historic admissions data to plot immediate against predicted demand, generates bed suggestions for patients coming through the emergency department, and explains its recommendations to promote trust. It also uses machine learning to make bed scheduling more efficient.
Predicted benefits
ACE said this has laid the ground for benefits linking effective bed scheduling, a reduction in moving patients between beds, improved patient outcomes and cost reductions.
The organisation is a government body that aims to solve public safety and security challenges that arise from changes in digital and data technologies.
