East Kent Hospitals University NHS Foundation Trust has started a pilot of an AI tool said to be capable of analysing routine clinical information and identifying infection risk early.
MEMORI, developed in collaboration with teams at the trust and embedded in Sunrise, has reportedly been offered for trial at no cost as part of a long term partnership with Sanome focusing on clinical AI safety. The tool has been rolled out in the Harvey ward at Kent and Canterbury Hospital.
The AI tool is said to analyse individual patient data including observations, medications, and demographics, and using what it has learnt from thousands of other patients to predict an infection risk score. The system also offers alerts if patient risk level changes.
Julie Jones, ward manager, spoke of the team’s excitement about the new tool, saying: “It has incredible potential in terms of recognising signs of infection early, alerting clinicians to review the patient and potentially change their treatment plan. Our patients can be very complex and can deteriorate quickly, so early intervention is vital and potentially life-saving.”
Wider trend: Health AI
For a recent session focusing on AI in healthcare, HTN was joined by an expert panel including Simon Brown, head of digital at Royal Papworth Hospital NHS Foundation Trust; Wahida Jabarzai, clinical AI and automation delivery lead at University Hospitals of Northamptonshire and University Hospitals of Leicester; and Julian Wiggins, healthcare solution director at Rackspace Technology. Our panel considered the wider challenge of AI adoption, looking at what makes a successful deployment, introducing AI safely and sustainably at scale, and some of the use cases currently delivering value across their organisations.
The MHRA has published findings from the National Commission into the Regulation of AI in Healthcareresearch, pointing to the need to balance a desire to use AI in improving patient care and supporting healthcare professionals, with “safe, fast and trusted” regulation. Almost three-quarters of respondents (73 percent) disagreed or strongly disagreed that the current regulatory framework is sufficient to ensure safety and performance standards; with 61 percent disagreed or strongly disagreed with its effectiveness in tackling data governance and data privacy. 61 percent also thought current requirements for clinical evidence are insufficient, and 65 percent pointed to a need for more to be done on post-market surveillance.
The National Institute for Health and Care Research has awarded £8 million to six innovations using AI and digital to speed up diagnosis and improve patient care. Innovations granted a share of the funding include SAMURAI-CT, an AI tool designed to detect “serious findings” from head CT scans with aims of reducing discharge times by more than 20 percent. It is currently being tested across Oxford University Hospitals, Royal Berkshire, University Hospitals of Derby and Burton, and NHS Greater Glasgow and Clyde.
