Intelligent Navigation using AI to bust waiting times for urgent healthcare (INA)

Delays harm patients who require urgent care and long waiting times lower staff morale while reducing public satisfaction in the NHS. Demand for urgent and same day care is rising as the population ages and more people are living with multiple health conditions. A growing number of people awaiting planned treatments or hospital admission end up needing urgent care because their health deteriorates. These patients need to be assessed and managed more quickly.

The problem with the current system

Currently, systems used by patients to access same day or urgent care make decisions are based on a patient’s current or ‘presenting’ symptoms, and cannot take account of patients’ medical history or overall health. Yet patient records, held by GPs, hospitals and other services can provide vital extra information to help assess how urgently patients need to be seen.

Proposed solution

Our project will evaluate a system that we call Intelligent Navigation. Instead of relying on patients, or receptionists/call handlers to run through a set list of questions, Intelligent Navigation uses AI (artificial intelligence) and a text-based app (similar to WhatsApp or SMS messaging) accessed from the NHS App, to help prioritise patients based on their symptoms AND medical history ensuring the most urgent cases are seen first.

Intelligent Navigation combines a medically approved tool (Visiba Triage) with AI-based software developed by Johns Hopkins University in America that can analyse medical history and health data quickly. We want to see if this AI-based intelligent triage can reduce waiting times for urgent care.

How it works

When patients contact their general practice seeking urgent same day care they will be asked to use the text-based chat in the NHS App. The patient will answer a series of questions using text-chat on a mobile phone to provide information about their symptoms/problem and Intelligent Navigation will quickly assess them and in the background review their health records to create a summary that goes straight to the clinical team. In this project, the AI-generated summary will also have pulled through contextual data from the Electronic Patient Record System, specifically the Johns Hopkins ACG score. This score will allow the clinician to rapidly triage the patient, knowing the underlying complexity of the patient. This process of assessing the patient takes less than 3 minutes.

What we will study

We want to look at whether AI-based intelligent triage can reduce waiting times for urgent care, improve continuity of care, and whether it provides value for money. We will develop and roll out this new system in General Practices within the Surrey and Sussex Integrated Care Board area, and conduct a comprehensive mixed methods evaluation. We have a patients and communities panel to make sure we listen to what patients have to say.

Our aim

Our goal is to determine whether or not AI-based intelligent triage can deliver shorter waiting times and better urgent care for patients.

Working with People and Communities

The patient and community involvement strategy ensures AI-based intelligent triage addresses real patient needs. Led by lay co-investigator Rachel Gerrard, we have an advisory group of 7 additional patient and public contributors who will provide oversight throughout the project, contributing to study design, survey and interview topic guide development, implementation insights, and dissemination. Their feedback will be systematically integrated to drive continuous improvement, with co-produced dissemination materials extending impact beyond the project and supporting wider public understanding of AI in urgent care.

Project details

Full project title: Intelligent Navigation using AI to bust waiting times for urgent healthcare (INA)

Length of project: March 2026 to August 2027

Funder: NIHR Invention for Innovation Programme

Project reference number: NIHR503515

Total: £709,630.00

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