1.1 Background

Chapter 1: Introduction

The background to this research and its origins.

This research - a collaboration between Health Education England and the NHS Artificial Intelligence (AI) Lab at the NHS Transformation Directorate - has its origins in the Topol Review (2019),3 which explored how to prepare the UK’s healthcare workforce to master digital technologies for patient benefit. The Topol Review recommended the NHS should develop a workforce able and willing to transform it into a world leader in the effective use of healthcare AI and robotics.

The Topol Review was followed by several initiatives in relation to supporting the development of digital, data, technology (DDaT) and clinical informatics skills in the NHS. It is important to note the nomenclature and responsibilities for roles involving these skills vary across these initiatives, and can include ‘DDaT data specialists’, ‘data scientists’, ‘data analysts’, ‘data engineers’, ‘clinical scientists’, ‘clinical informaticians’, ‘clinical bioinformaticians’, ‘digital professionals’, and ‘AI professionals’. Further work is needed to reach consensus on the terminology and clarify links across these roles.

The initiatives include the following.

  • The Health Education England (HEE) report ‘Data driven healthcare in 2030: Transformation requirements of the NHS digital technology and health informatics workforce’ published in March 2021.7 The report was commissioned by HEE’s Digital Readiness programme to identify the capacity and capability challenges facing the NHS digital technology and informatics workforce in the next 10 years. It projected the need for an additional 32,000 whole-time equivalents (WTEs) within the workforce to reach a forecasted size of 78,000 WTEs in 2030. The highest increase has been projected in clinical informatics professionals including data analysts, data scientists, clinical informaticians, statisticians and biostatisticians, health economists and clinical digital service owners.
  • The HEE report ‘The future of clinical bioinformaticians in the NHS’ published in July 2021, which builds a comprehensive understanding of the factors related to the commissioning, training, and employment of clinical bioinformaticians in the NHS.8
  • ‘Putting data, digital and tech at the heart of transforming the NHS’ published in November 2021, sets out recommendations for a shift in culture, operating model, skills, capabilities and processes to put data, digital and technology at the heart of how NHS transforms health services.9
  • The NHS ‘Year of the digital profession 2022’ initiative, which involves a five-year strategy and roadmap to build a sustainable digital and data workforce.10
  • The Goldacre Review (‘Better, broader, safer: Using health data for research and analysis’), published in April 2022, exploring actions for better, broader, and safer use of NHS patient records to drive innovation and save lives. The review made several recommendations for the NHS workforce and needed education to support the efficient and safe use of health data, including a call to expand the workforce of data analysts and promote shared learning across sites. 4
  • The ‘Data saves lives: reshaping health and social care with data’ strategy published in June 2022, which sets out the strategy for using data to bring benefits to all parts of health and social care, including direct patient care, population health, improvement of care services and research and innovation.11
  • The ‘A plan for digital health and social care’ report published in June 2022, which sets out a roadmap for the digital transformation of health and social care. It consolidates national digital goals and investments into one single action plan to equip the system digitally for better care, support independent healthy lives, accelerate adoption of proven tech, and align oversight with accelerating digital transformation.12

Specific to AI technologies, HEE has established the Digital, AI and Robotics Technologies in Education (DART-Ed) programme to understand the impact of advances in AI on education and training needs. This research will build also on the AI Roadmap,13 published by HEE and Unity Insights in January 2022. The Roadmap provides an understanding of the use of AI and data-driven technologies that currently exist in the healthcare system, the uptake of these new technologies, and their impact on the workforce. Box 1 lists the Roadmap’s main findings.

Box 1: AI Roadmap - main findings

The Roadmap involved an extensive horizon scanning exercise to capture information on 240 AI technologies at various stages of deployment in NHS sites.

Distribution of AI technologies: out of the 240 technologies, ‘Diagnostic’ was the most represented type with 34%, closely followed by ‘Automation/Service efficiency’ at 29%. ‘P4 Medicine’ and ‘Remote monitoring’ technologies accounted for 17% and 14% of technologies respectively. Within the ‘Diagnostic’ type, ‘Imaging’ solutions and ‘Cardiorespiratory and neurology’ solutions were at respectively 49% and 27%.

Key clinical areas using AI: the database included 67 clinical areas. After ‘Multiple clinical areas’ (selected for 23% of technologies), the most selected options were ‘Clinical Radiology’ (11%), ‘Cardiology’ (9%) and ‘General Practice’ (8%). The percentage of Automation/service efficiency technologies can explain why ‘Multiple clinical areas’ was so often selected, as they can be used in a multitude of settings.

Most affected workforce groups: 155 workforce groups (developed based on the occupational codes) were used to describe the NHS workforce. The top five workforce groups who have been identified as direct users of AI technologies are ‘Medic, Clinical Radiology’ (with 15% of technologies), ‘Medic, General Practice’ (13%), ‘Non Clinical, Admin’ (10%), ‘Diagnostic Radiographer’ (8%) and ‘Medic, Cardiology’ (8%).

Supporting healthcare workers to feel confident in identifying when and how to use AI is a main objective of the NHS AI Lab, and a key component of its vision for the safe, effective, and ethical adoption of AI technologies across health and care. This research will support the Lab’s commitment to empower healthcare workers to make the most of AI, including making the best of their expertise, informing their decisions, and saving them time to focus on patient care.

References

3 Topol E. The Topol Review: Preparing the Healthcare Workforce to Deliver the Digital Future. 2019. https://topol.hee.nhs.uk/the-topol-review/  Accessed February 28, 2022.

7 Health Education England. Data Driven Healthcare in 2030: Transformation Requirements of the NHS Digital Technology and Health Informatics Workforce. 2021. https://www.hee.nhs.uk/our-work/building-our-future-digital-workforce/data-driven-healthcare-2030 Accessed May 24, 2022.

8 Health Education England. The Future of Clinical Bioinformaticians in the NHS. 2021. https://www.hee.nhs.uk/our-work/building-our-future-digital-workforce/future-clinical-bioinformaticians-nhs Accessed May 24, 2022.

9 Wade-Gery L. Putting data, digital and tech at the heart of transforming the NHS.2021. https://www.gov.uk/government/publications/putting-data-digital-and-tech-at-the-heart-of-transforming-the-nhs Accessed May 24, 2022.

10 NHS. The Year of the Digital Profession 2022. https://www.nhsx.nhs.uk/digitise-connect-transform/the-year-of-the-digital-profession-2022/ Accessed May 24, 2022.

4 Goldacre B, Morley J. Better, Broader, Safer: Using health data for research and analysis. A review commissioned by the Secretary of State for Health and Social Care. Department of Health and Social Care. 2022. https://www.goldacrereview.org/ Accessed May 24, 2022.

11 Data saves lives: reshaping health and social care with data. Department of health and Social Care. 2022. https://www.gov.uk/government/publications/data-saves-lives-reshaping-health-and-social-care-with-data/data-saves-lives-reshaping-health-and-social-care-with-data Accessed June 15,2022.

12 A plan for digital health and social care. Department of health and Social Care. 2022. https://www.gov.uk/government/publications/a-plan-for-digital-health-and-social-care/a-plan-for-digital-health-and-social-care Accessed June 29, 2022.

13 Unity insights. AI Roadmap. Health Education England. 2022. https://digital-transformation.hee.nhs.uk/binaries/content/assets/digital-transformation/dart-ed/ai-roadmap-march-2022-edit.pdf Accessed February 28, 2022.

Page last reviewed: 18 April 2023
Next review due: 18 April 2024