App developed to help clinicians identify and manage acute kidney injury

Acute Kidney Injury (AKI), an abrupt deterioration in kidney function, occurs in up to one in five emergency admissions to hospital. The financial burden to the NHS is estimated to be more than £1bn per year. Early identification of, and response, to AKI is key to improving outcomes for patients with AKI.

A novel care pathway has been developed, which combines NHS guidelines for best practice with a mobile app - called “streams-AKI". This app applies an NHS algorithm to live patient clinical data. This digital pathway aims to help improve diagnosis times and treatment of patients.

We collaborated with Google DeepMind Health to develop and evaluate this app, and establish if it helped clinicians to identify patients at risk of acute kidney injury, in real time.

Using a mixture of qualitative and quantitative methods, and working alongside clinical nephrologists, critical care outreach nurses and IT staff, we evaluated the care pathway enabled by this app in an NHS hospital. 

Key evaluation findings following implementation include:

• significant improvements in the speed of recognition (in-app review of blood tests in 14 minutes) and treatment of AKI
• average health care costs reduced by £2k per patient
• earlier, more constructive end-of-life planning
• a need for training clinicians in prevention and prioritisation

Informed by our research, this innovation won the 2019 HSJ Patient Safety Award (Deteriorating Patients & Rapid Response Systems Award category).

This pathway has been implemented at the Royal Free London NHS Foundation Trust.

University College London

UCLH Biomedical Research Centre

DeepMind Health

Royal Free London NHS Foundation Trust