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Artificial intelligence (AI) implementation within the National Health Service (NHS): the South West London AI
S C Shelmerdine1, D Togher2, S Rickaby3
1Department of Clinical Radiology, Great Ormond Street Hospital for Children, London, WC1H 3JH, UK; University College London, Gower Street, London, WC1E 6BT, UK; UCL Great Ormond Street Institute of Child Health, Great Ormond Street Hospital for Children, London, WC1N 1EH, UK; NIHR Great Ormond Street Hospital Biomedical Research Centre, 30 Guilford Street, Bloomsbury, London, WC1N 1EH, UK.
Abstract:
In the rapidly evolving field of artificial intelligence (AI) for radiology, with a plethora of vendor options and use-cases and evidence claims to sift through, the pressing question is how to effectively implement the right tool for enhanced patient care? This article presents a structured approach to AI deployment, drawing from a comprehensive case study in South West London. We underscore the necessity of forming a dedicated AI team with a clear vision and assertive leadership to navigate such complexities. Central to our discussion is the significance of crafting an AI implementation plan, with an overarching aim to augment patient care, promote operational efficiency, and lay down standardized protocols for seamless AI adoption. By presenting a blueprint for AI implementation within the National Health Service (NHS), we intend to demystify the process for radiology departments across the UK, enabling them to make informed decisions and empowering their staff to embrace and leverage AI responsibly ensuring that patient welfare remains at the heart of innovation. Thus, having a framework to follow when implementing an AI solution that addresses a vision for scalable adoption, core team members with diversity of skillset, staff engagement and education, plan for vendor selection, and change management is crucial for success.
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