AI Triage Impact

  • Research type

    Research Study

  • 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

  • Contact name

    Benjamin C Brown

  • Contact email

    benjamin.brown@manchester.ac.uk

  • Sponsor organisation

    University of Manchester

  • Duration of Study in the UK

    2 years, 4 months, 30 days

  • 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.

  • REC name

    HSC REC A

  • REC reference

    24/NI/0022

  • Date of REC Opinion

    22 Feb 2024

  • REC opinion

    Favourable Opinion