Woubot - an A.I. predictive system for personalised care of wounds

  • Research type

    Research Study

  • Full title

    Woubot an A.I. predictive system to produce personalised care recommendations for chronic lower limb wounds

  • IRAS ID

    279993

  • Contact name

    Elaine Taylor-Whilde

  • Contact email

    elaine.taylor-whilde@ninecic.org.uk

  • Sponsor organisation

    Nine Health Global Ltd

  • Duration of Study in the UK

    0 years, 11 months, 30 days

  • Research summary

    Data suggests that approximately 2.2 million patients currently have a chronic wound (Guest et al 2016) with the annual cost to the NHS of managing these wounds and associated comorbidities being £5.3 billion (Guest et al 2015).

    Up to 40% of chronic leg wounds never heal, often leading to serious complications and even death. We are undertaking a feasibility study to test our artificially intelligent software on data from this group of patients. We are combining them our clinical knowledge with an existing non-health sector technology to create creating a new mobile device/smartphone application(app).

    We will train the artificial intelligence (AI) to identify people likely to develop chronic leg wounds and manage their preventative care. In those that already have leg wounds, such as diabetic foot ulcers, the software will help to ensure that evidence-based guidelines for treatment are turned into simple steps which are available quickly and easily to front-line NHS staff.

    Our software will rapidly sift through millions of data items in secure NHS approved facilities. This will enable recommendations to be generated via a mobile app. The software will generate a personalised care pathway with a series of recommendations for use in the NHS.

    Most of this care will be delivered by nurses and other healthcare professionals in clinics and the community. Recommendations, whether for exercise, other lifestyle changes, medication, or dressings, will be individualised for each patient based on their history and biological makeup and linked to the latest clinical evidence. We will also use image software to monitor progress easily and accurately.

    There are currently no automated predictive/preventative software tools generating a series of options for care based on the personalised profiles of patients. Research studies produce variable and conflicting results for those treating hard to heal wounds.

  • REC name

    London - London Bridge Research Ethics Committee

  • REC reference

    21/PR/0024

  • Date of REC Opinion

    9 Mar 2021

  • REC opinion

    Favourable Opinion