Cognitive biases like confirmation bias and rejection bias are common challenges during clinical reasoning and decision making (CRDM) – the process involving a clinician assessing various types of information like test results, imaging and reports to make a decision on a specific patient and case.

It is important to consider and understand these biases when new and unfamiliar tools or information sources, such as AI-decision support tools, are introduced into CRDM. Cognitive biases may either be reinforced, or mitigated, by the inclusion of AI-derived information in the CRDM process, which suggest the importance of clinicians understanding how their current decision-making process could be influenced by the introduction of AI technologies.

We ask applicants to respond to the following challenge:

  • How can clinicians and healthcare settings address the risks and opportunities involved with cognitive biases in CRDM when introducing AI-derived information? We invite research proposals that aim to capture existing evidence, conduct research to address any evidence gaps, and develop educational tools or other types of artefacts that can increase awareness of the influence of cognitive biases during CRDM when using AI-derived information, and how to mitigate against related risks.

Additional Context

The NHS Workforce, Training and Education Directorate includes teams previously at Health Education England responsible for planning, recruiting, educating and training the health workforce to ensure the right skills in place to support the delivery of excellent healthcare and health improvement to patients and the public.

The NHS Digital Academy provides access to learning products to support the uplift of digital skills, knowledge, understanding, and awareness to new ways of working.

As part of broader work to build a digital-ready healthcare workforce, the teams collaborated with  the NHS AI Lab to publish two reports on factors influencing healthcare workers’ confidence in AI-driven technologies, and how such confidence can be developed through education and training.

The fellow will be expected to expand on this published work and other evidence, and to work collaboratively with the teams at the NHS Digital Academy and NHS Workforce, Training and Education Directorate as part of broader efforts to develop workforce confidence in AI.

We invite research proposals that

  • draw on expert knowledge of the health system and health policy in the UK;
  • call for regular contact and engagement with the teams at NHS Digital Academy and NHS Workforce, Training and Education Directorate;
  • consider the involvement of the various stakeholders – including healthcare professionals, innovators and related educational and training providers; and
  • consider the development of education and training materials.

Working Arrangements

As a BRAID-NHS England fellow you will be hosted by a team within the Workforce, Training and Education Directorate. You will also be steered to liaise with relevant teams within the NHS Transformation Directorate and joint units with the Department of Health and Social Care.

How it will work

  • If successful, the NHS Digital Academy and NHS Workforce, Training and Education Directorate teams will work with the fellow to refine the project plan and agree on shared goals and outcomes.
  • The NHS Workforce, Training and Education Directorate will support the fellow in terms of onboarding, providing a research contact and main collaborator, and engaging in regular meetings.
  • The NHS Workforce, Training and Education Directorate is set up for remote or hybrid working with offices in London and Leeds.
  • Fellows are not required to attend the NHS Workforce, Training and Education Directorate offices in person, unless it is their preference, in which case office space can be provided.
  • Fellows are asked to factor into their budget proposal any travel, accommodation and subsistence costs and any specific research costs they envision.
  • We ask that applicants specific any reliance on accessing specific NHS resources (for example, data) or specific settings, and that they include considerations for seeking related approvals for using these resources.
Scroll to Top