Question to the Department of Health and Social Care:

To ask the Secretary of State for Health and Social Care, what assessment his Department has made of the potential impact of AI radiotherapy auto-contouring on (a) patient outcomes, (b) productivity and (c) workforce retention.

Artificial intelligence (AI) technologies have huge potential in improving productivity across the National Health Service by supporting clinicians with faster and more accurate diagnosis, enhancing clinical decision-making about treatment plans, and reducing the administrative burden faced by healthcare staff. The Department and NHS England are developing guidance for the responsible use of these tools and how they can be rolled out to make the day-to-day operations of the NHS more productive and provide better outcomes for patients.

The Department is focusing the £21 million AI Diagnostic Fund on the integration of AI technologies in key, high-demand areas such as radiology, particularly for chest x-rays and chest computed tomography scans to enable faster diagnosis and treatment of lung cancer in over half of acute trusts in England. This will not only allow patients to be diagnosed and treated sooner, but will also lower the demands on NHS staff, improving morale and staff retention.

In addition, the National Institute for Health and Care Excellence (NICE), sponsored by the Department, evaluates new health technologies for NHS use, considering clinical effectiveness, value for money, and impacts on staff. As part of this, the NICE conducts Early Value Assessments (EVA) for developers, reviewing their AI tools before they are deployed. For the NHS, EVAs aim to give the NHS a clear signal about which innovations work, offer good value for money, and meet system needs, including productivity gains for staff.

The NICE has recommended that AI technologies can be used in the NHS to help with the contouring of computed tomography and magnetic resonance imaging scans, to plan radiotherapy treatment for people having external beam radiotherapy. Technologies such as these have been shown to contour images almost two and a half times faster than a human. This reduction in time could support the reduction of backlogs, ensure patients receive treatment sooner, save money, and allow healthcare professionals to spend more time with patients.