We only share anonymised data for research projects that have been approved by an NHS Research Ethics Committee and the Health Research Authority. Details of those projects are listed on this page.
AI Triage Accuracy
Full title: Improving the accuracy of artificial intelligence triage in primary care
IRAS ID: 331286
Chief Investigator: Dr Benjamin C Brown (University of Manchester). Dr Brown is a part-time employee of Patchs Health as Chief Medical Officer and is a shareholder in the company. Patchs Health develop the Patchs software.
Contact email: patchs.research@manchester.ac.uk
Sponsor organisation: University of Manchester
Research summary:
WHY ARE WE DOING THIS?
When patients contact their GP practice, the first step is to work out what kind of help they need and how quickly it’s needed. This is called ‘triage’ and is important for patient safety. Artificial Intelligence (AI) can help make triage faster. While AI is already being used in the NHS, we don’t know how accurate it is or if it treats all patients fairly.
WHAT WILL WE DO?
We will collect anonymised data from patients that use an AI triage system called Patchs in GP practices in England. The project will last four years. We will analyse the data in four steps:
1. Look at data from GP practices using Patchs without AI triage to see how they currently triage patients and what problems they face.
2. Use data from GP practices using Patchs (both with AI on and off) to make the AI triage more accurate.
3. Check data from GP practices using Patchs with AI triage off to measure how well the updated AI system works.
4. Give the improved AI triage system to GP practices already using AI.
At each step, we will check whether patients from different backgrounds are treated fairly.
HOW WILL WE ANALYSE THE DATA?
We will use statistical methods to compare the triage decisions made by the AI with those made by clinical staff. This analysis will also be used to check that the AI works fairly for patients from different backgrounds.
WHAT DIFFERENCE WILL WE MAKE?
Our research will show the problems with triage and explain how an improved AI system could help patients get the care they need more quickly.
Research Ethics Committee name: Nottingham 1 REC
REC reference: 25/EM/0191
Date of REC Opinion: 01 Aug 2025
AI Triage Impact
Full title: Evaluating the impact of artificial intelligence triage in online consultations to reduce delays in urgent primary care: interrupted time series analysis and quantitative process evaluation
IRAS ID: 331286
Chief Investigator: Dr Benjamin C Brown (University of Manchester). Dr Brown is a part-time employee of Patchs Health as Chief Medical Officer and is a shareholder in the company. Patchs Health develop the Patchs software.
Contact email: patchs.research@manchester.ac.uk
Sponsor organisation: University of Manchester
Research summary:
Background
Online consultations allow patients to ask for help from their GP practice by completing a form on the internet. They have been available in most English GP practices since May 2020. GP practices can receive lots of completed online consultation forms at the same time, which means it can be difficult for them to know which patients need urgent or emergency help. This can lead to delays in patients getting the care they need. We want to test if computers trained to spot urgent and emergency forms (Artificial Intelligence or ‘AI’) can reduce these delays. We also want to know if AI works in the same way for all patients and whether it is good value for money.
What will we do?
We will study an AI system that is already used in NHS GP practices. We will give it to 20 GP practices not currently using it. We will measure the delays for patients receiving urgent and emergency help for 12 months before and after they start using the AI. We will compare this to 20 other GP practices that will not use the AI. We will also measure whether the AI affects staff workload and whether it works in the same way for patients from different backgrounds.
What difference will we make?
If the AI reduces care delays, patients who need urgent and emergency help will receive it sooner. We will help the NHS and companies that make online consultation systems decide whether they should use AI. We will help members of the public and GP practices understand what AI is and how they can use it to benefit both patients and staff.
Research Ethics Committee name: HSC REC A
REC reference: 24/NI/0022
Date of REC Opinion: 22 Feb 2024