- Train: to significantly increase education and training, as well as increasing apprenticeships and alternative routes into professional roles, to deliver more doctors and dentists, more nurses and midwives, and more of other professional groups, including new roles designed to better meet the changing needs of patients and support the ongoing transformation of care.
- Retain: ensuring more staff stay within the health service by better supporting people throughout their careers, supporting flexible working in ways that suit staff and patients, and continuing to improve the culture and leadership across NHS organisations.
- Reform: improving productivity by working and training in different ways, building broader teams with flexible skills, changing education and training to deliver more staff in roles and services where they are needed most, and ensuring staff have the right skills to take advantage of new technology that frees up clinicians’ time to care, increases flexibility in deployment, and provides the care patients need more effectively and efficiently.
A key theme in the plan is to capitalise on developments in science, research, technology, digital and data. It notes the requirement to “build digital skills and capabilities and change ways of working” and adds “to meet the changing healthcare needs of the population in a cost-effective way, the NHS workforce will need to take full advantage of digital and technological innovations”. It states that “widespread safe, effective and ethical adoption of these innovations will be one of the most important ways of delivering the stretching productivity ambitions in this plan”.
With investment, education and recruitment highlighted as key areas, the plan notes that action is required for “improving culture and retention, training the workforce differently, evolving the skills mix and delivering productivity”. Here, it states this “ambition requires a combination of delivering care closer to home while avoiding costly admissions, achieving operational excellence, reducing administrative burden through better technology and infrastructure, and capturing the benefits appropriately in productivity measurement.”
To achieve this productivity ambition, the plans says it “will require continued and sustained investment in the NHS infrastructure, a significant increase in funding for technology and innovation, and the delivery of the broader proposals in this plan.”
It goes on to highlight the role of different aspects of health tech, including the NHS AI Lab, which is supporting 86 projects at the moment across 99 hospitals, showing promising results. It notes the impact AI could have in the short and longer term, where AI could be used for predictive health analytics, patient triage and preventive healthcare. It also pays reference to the potential of foundational AI models such as “generative AI or large language models, which can understand and produce an image, text and audio”, and “are predicted to transform work across all sectors”.
NHS England notes a number of actions to achieve improvements with AI, including:
- Reviewing initial evaluations from the AI Award – to be completed by the end of 2024.
- Supporting the government’s Foundation Model Taskforce, which is set to support the next generation of AI, to support and optimise implementation across the NHS.
- Ongoing investment in the Fellows in Clinical Artificial Intelligence programme.
- Building the workforce’s confidence in AI, by establishing governance and robust implementation of AI technologies and driving AI-related education training including fundamentals for the full workforce and advanced training where it is required.
- Leading workforce development in AI and digital healthcare technologies as informed by the AI and Digital Healthcare Technologies Capability framework.
- Developing understanding of the implications for the workforce and working with partners, including royal colleges, to plan for these – including considerations for specialist roles and teams as well as the wider workforce – and on system efficiencies, as technology continues to develop.
The next area of focus is administrative functions, and the opportunity for using AI and speech recognition, where it highlights an example in general practice where 44% of administrative work could be automated. Here, the plan also covers the use of robotic process automation to automate back-office tasks in the NHS, and states: “All 42 ICSs now use RPA, including 38% of community or mental health trusts and 61% of acute trusts, but there are opportunities for further uptake”. Here it projects that: “If all trusts implemented processes that have been ‘time validated’, this could save more than 7.2 million hours annually, equivalent to over 965,000 working days released. Over the next 10 years, this could be nearer 22 million hours saved, equivalent to more than 2.9 million working days released”.
