Experiences of using artificial intelligence in healthcare: a qualitative study of UK clinician and key stakeholder perspectives

BMJ Open. 2023 Dec 11;13(12):e076950. doi: 10.1136/bmjopen-2023-076950.

Abstract

Objectives: Artificial intelligence (AI) is a rapidly developing field in healthcare, with tools being developed across various specialties to support healthcare professionals and reduce workloads. It is important to understand the experiences of professionals working in healthcare to ensure that future AI tools are acceptable and effectively implemented. The aim of this study was to gain an in-depth understanding of the experiences and perceptions of UK healthcare workers and other key stakeholders about the use of AI in the National Health Service (NHS).

Design: A qualitative study using semistructured interviews conducted remotely via MS Teams. Thematic analysis was carried out.

Setting: NHS and UK higher education institutes.

Participants: Thirteen participants were recruited, including clinical and non-clinical participants working for the NHS and researchers working to develop AI tools for healthcare settings.

Results: Four core themes were identified: positive perceptions of AI; potential barriers to using AI in healthcare; concerns regarding AI use and steps needed to ensure the acceptability of future AI tools. Overall, we found that those working in healthcare were generally open to the use of AI and expected it to have many benefits for patients and facilitate access to care. However, concerns were raised regarding the security of patient data, the potential for misdiagnosis and that AI could increase the burden on already strained healthcare staff.

Conclusion: This study found that healthcare staff are willing to engage with AI research and incorporate AI tools into care pathways. Going forward, the NHS and AI developers will need to collaborate closely to ensure that future tools are suitable for their intended use and do not negatively impact workloads or patient trust. Future AI studies should continue to incorporate the views of key stakeholders to improve tool acceptability.

Trial registration number: NCT05028179; ISRCTN15113915; IRAS ref: 293515.

Keywords: clinical decision-making; qualitative research; quality in health care.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Academies and Institutes
  • Artificial Intelligence*
  • Humans
  • Qualitative Research
  • State Medicine*
  • United Kingdom

Associated data

  • ClinicalTrials.gov/NCT05028179