Barking, Havering and Redbridge University Hospitals has shared details of how AI and imaging tools are being utilised across the trust, with an aim to reduce waiting times for x-ray results, and support cancer diagnosis and cancer treatment.
As part of the North East London Cancer Alliance, the trust is participating in an initiative to utilise AI to reduce waiting times for X-ray results “from three weeks to just three days” for “scans with significant findings”, using AI to help clinicians prioritise urgent cases and “quickly” sort through normal ones.
The trust is also running a new project aiming to speed up the diagnosis of mouth cancer, inviting patients to attend Barking’s CDC to have photos taken by a clinical photography team which can then be examined by a head and neck consultant, with patients “getting a call back within a day or so to confirm whether they have cancer or not”. The launch followed a trial in which head and neck consultants blind reported on photos without full medical history, which “established an image was enough to make a correct diagnosis”.
Results from the pilot, which has been running since June, have so far meant 95 percent of patients have been “reassured they do not have cancer without facing an anxious wait to see a consultant”, the trust reports, whilst six patients have been diagnosed with mouth cancer and directed to the care they require. Calling the pilot “a totally different experience for patients”, lead consultant Neil Shah shared that it has saved patients time visiting the hospital and allowed the team to concentrate on “the most serious cases”, adding that the feedback from patients has been “fantastic”.
Staff members have also been involved in showcasing the trust’s Cancer and Clinical Support services, sharing ways they are utilising AI in helping patients “start their treatment sooner”, helping reduce the workload for oncologists by incorporating an AI tool to outline target areas for radiotherapy treatment. Whilst an oncologist is still required to check the tool’s work, the process takes “less time than it would take for the oncologist to do it from scratch”.
AI in supporting cancer care
Earlier this year, a skin cancer pilot was launched in Tameside and Glossop featuring an AI platform to help triage and assess skin lesions for suspected cancer, capable of classifying 11 different malignant, pre-malignant, and benign skin lesion types.
We also reported that Cambridge University Hospitals NHS FT Consultant gastroenterologist, Dr Massimiliano di Pietro, was awarded a funding grant of up to £365,000 to explore how artificial intelligence and video can help identify gastric cancer at an earlier stage.
And HTN’s report on the use of AI across the NHS covered use cases including the use of AI in cancer detection in Bolton, and AI in skin cancer detection in Suffolk and North East Essex.
AI: the wider trend
Back in June, the Department of Health and Social Care announced £21 million in funding for artificial intelligence technologies, intended to enable the roll-out of AI technology which, according to the announcement, will “help diagnose patients more quickly for conditions such as cancers, strokes and heart conditions”.
August also saw HTN joined by expert panellists who shared their views on whether AI will live up to the current hype. The session explored topics including what is needed to manage bias; what “responsible AI” really looks like; how to ensure AI is inclusive and equitable; how AI can help support underserved populations; the deployment of AI in the NHS; and the potential to harness AI in supporting the shift from reactive to proactive care.
We also covered the news that the AI Act, a legal framework seeking to address the risks of AI in Europe by setting out clear requirements and obligations in support of “trustworthy AI”, had officially entered into force.
Somerset NHS Foundation Trust’s final version of its AI policy, focused on the need for safe integration and an approach balancing innovation with ethical and legal responsibilities, was shared via LinkedIn, detailing ways the trust is future-proofing its approach and ensuring fairness and transparency around AI use.
And Great Ormond Street Hospital shared plans to expand its pilot of ambient AI to 5,000 patients from a range of different healthcare settings across London, following testing in 100 outpatient appointments.
