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a647f003-18d5-4609-a5bb-66acbb48fc65-739017Chest X-ray A.I Solution for the Yorkshire Imaging Collaborative. Funding via the NHSE A.I Development Fund . With this fund we will introduce a single Chest X-ray AI tool to pre-read all chest radiographs for our whole population in every clinical setting immediately after acquisition so that the AI interpretation will be available at the point of front-line clinical contact for doctors and the growing spectrum of non-medical health professionals. The most pivotal benefit will be derived from an "AI first read" with labelling of suspected pathology for care providers who formerly waited a median 7-days (max 10-days) for a full radiological report. In addition, AI triaging of "normal vs abnormal" will accelerate local human reporting of studies where abnormal findings were found, to allow faster critical alerting of important time sensitive findings. YIC is already fully network level compliant with the RCR Critical Alerts Guidance (2023). YIC will carry out an early deployment into our network pilot test site using DICOM secondary capture, this will allow early benefit realisation as well as engineering work to create a deep integration template which can be rapidly deployed to the other member Trusts. Important targeted pathway improvements we wish to affect and improve are: • Time to diagnosis and treatment in (chest derived) sepsis - Improving Outcomes of Patients with Sepsis, pub. December 2015 and Surviving Sepsis: Antibiotic Timing Guidelines. Society of Critical Care Medicine, pub. October 2021). • Reduction of Never Events in placement of NG feeding tubes in hospitals (NHS England National Patient Safety Alert. pub. 2013). Recent Regulation 28 report. • Faster 'time to use' of NG feeding tubes for critical drug and nutritional administration • Improvement in consistency and speed of lung cancer detection on chest radiographs. As a region West Yorkshire has amongst the highest incidence of lung cancer in England. (Cancer registration statistics, England: 2017 [Internet]. ONS Report. 2019). • Improved 'time to MDT' for suspected lung cancers by AI pre-reading and prioritising formal reporting of abnormal studies.
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a647f003-18d5-4609-a5bb-66acbb48fc65-739017Awards and suppliers
Buyer: Leeds Teaching Hospitals NHS TrustSupplier: Annalise.ai
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