Chapter 4: Workforce Transformation

Chapter 4: Workforce Transformation

An overview of Chapter 4.

As discussed in the first report,1 the safe, efficient, and effective implementation of artificial intelligence (AI) technologies in healthcare settings will involve strategic, organisational, and cultural considerations. A key insight of the report involves the need for workforce transformation through developing specialised roles and teams, supported by resourcing and training opportunities.

This chapter considers how novel team structures, the recruitment, training and retaining of individuals with specialist AI skills, and new leadership roles can support health settings to deploy AI technologies.

Workforce transformation, as defined by Health Education England (HEE), is a process to improve the recruitment, retainment, deployment, development and ongoing support of the healthcare workforce, to meet the growing and changing needs of local populations - ensuring high quality care for the patients of today and the future.

Workforce transformation efforts to support AI-related education and training can be grouped against the five enablers of the HEE Star framework,6 as illustrated in Figure 5.

Figure 5

Supply
  • Establish clear job roles and career pathways for digital, data and technology specialists (see section 4.2.1).
  • Expand the specialist DDaT data family and clinical informatics workforce through targeted recruitment, increased education and training opportunities, competitive renumeration and flexible equivalence pathways for those with skills from experience outside the NHS (sections 4.2.1 and 4.2.2).
  • Support professionalisation and accreditation of the DDaT data family and clinical informatics workforce through recognised and trustworthy national bodies (section 4.2.1).
Upskilling
  • Maximise the potential of the workforce through recognised and accredited digital career and education pathways (section 4.2.1).
  • Support ongoing CPD (Continuing Professional Development) frameworks for development and validation of digital professionals (section 4.2.1).
  • Provide protected education time for digital skill development supported by flexible hybrid training pathways for digital specialist clinicians (section 4.2.1).
  • Provide equitable access to training and support, including special efforts to engage and support the digitally unengaged or unconvinced (section 4.2.1).
New roles
  • Identify gaps that may be filled by development or implementation of new roles (section 4.2.1).
New ways of working
  • Establish and support AI multi-disciplinary teams (MDTs) involving clinical and technical roles to lead the evaluation, deployment and product-specific user training for AI technologies. A diverse team and a flat organisational structure should be encouraged to avoid hierarchy and minimise bias (section 4.1).
  • Through innovative placements and recruitment, promote an integrated workforce that creates new relationships and networks and a working environment that embraces intrapreneurship and collaboration (section 4.2.1).
Leadership
  • Develop a new cadre of digital leadership roles with recognition of the value of specialist skills at a senior level for individuals with DDaT data and clinical informatics skills (section 4.2.3).
  • Set out clear training pathways and career trajectories to achieve a specific set of competencies required for digital leadership (section 4.2.3).

These elements can complement the educational and training pathways suggested in Chapter 3.

Specific considerations when developing Integrated Care System (ICS) workforce plans can include:

  • establishment of AI multidisciplinary teams (MDTs)
  • development of a plan to increase the digital, data and technical (DDaT) data family workforce to meet future demand. This can include new clinical informatics specialist roles, supported training opportunities, upskilling existing staff into technical roles and joint digital/clinical training opportunities for clinical staff. If deemed necessary, it could also include routes for external expertise to be brought into the healthcare sector
  • creation of senior (non-managerial) technical roles with expert AI-related knowledge and skills
  • expansion of professional digital leadership positions to lead AI development and deployment

References

1 Nix M, Onisiforou G, Painter A. Understanding healthcare workers’ confidence in AI. Health Education England & NHS AI Lab. 2022. https://digital-transformation.hee.nhs.uk/binaries/content/assets/digital-transformation/dart-ed/understandingconfidenceinai-may22.pdf Accessed 29 June, 2022.

6 Health Education England. HEE Star: Accelerating workforce design. https://www.hee.nhs.uk/our-work/hee-star Accessed May 24, 2022.

Page last reviewed: 19 April 2023
Next review due: 19 April 2024