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Procurement and early deployment of artificial intelligence tools for chest diagnostics in NHS services in England: a
Angus I G Ramsay1, Nadia Crellin2, Rachel Lawrence1
1Institute of Epidemiology and Health Care, University College London, UK.
Background:
Artificial Intelligence (AI) may support accurate, efficient radiology diagnostics. However, little is known about implementing AI in clinical settings. In 2023, NHS England launched a programme funding 12 networks of 66 NHS Trusts to implement AI for chest diagnostics, including lung cancer.
Methods:
Rapid evaluation (March-September 2024) of procurement and early deployment of AI for chest diagnostics at network (n = 10) and Trust (n = 6) levels. We interviewed network teams, Trust staff, and AI suppliers (n = 51); observed planning, governance, and training (n = 57); and analysed relevant documents (n = 166). The NASSS framework guided thematic analysis.
Findings:
Procurement and deployment of AI took longer than anticipated. Procurement involved engaging selection panels, assessing tenders, and contracting AI suppliers. Preparation for deployment involved AI integration; governance processes; staff engagement and training; planning patient engagement; and collating impact data; patient communication plans varied and were still developing. Challenges included: engaging staff with high clinical workloads; staff's limited AI knowledge, time to participate, and concerns over appropriate tool usage; managing unsuccessful suppliers' responses; and varied local governance processes, IT systems, and data availability and quality. Enablers included: programme leadership's support; networks sharing expertise and capacity; committed clinical, technical, and procurement specialists and AI suppliers; clinical champions; and dedicated project management.
Interpretation:
Implementing AI involved complex social and technical processes, requiring significant resources. Future implementation may benefit from ensuring sufficient time and capacity, ongoing stakeholder engagement at multiple levels, and greater consideration of patients and equity, diversity, and inclusion. Influential factors identified here mirror research on other healthcare innovations, suggesting AI may not address service challenges as straightforwardly as policymakers anticipate.
Funding:
National Institute for Health and Care Research (NIHR), Health and Social Care Delivery Research programme (NIHR156380). NJF and AIGR are supported by NIHR Central London Patient Safety Research Collaboration. NJF is an NIHR Senior Investigator.
