Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Nov;8(3):e648-e654.
doi: 10.7861/fhj.2020-0258.

Artificial intelligence and the NHS: a qualitative exploration of the factors influencing adoption

Kirsty Morrison  1
Affiliations

Artificial intelligence and the NHS: a qualitative exploration of the factors influencing adoption

Kirsty Morrison. Future Healthc J. 2021 Nov.

Abstract

Background: AI has the potential to improve healthcare. However, there is limited research investigating the factors which influence the adoption of AI within a healthcare system.

Research aims: I aimed to use innovation theory to understand the barriers and facilitators that influence AI adoption in the NHS; and to explore solutions to overcome these barriers, and examine these factors, particularly within radiology, pathology and general practice.

Methodology: Twelve semi-structured, one-to-one interviews were conducted with key informants. Interview data were analysed using thematic analysis.

Findings: A range of barriers and facilitators to the adoption of AI within the NHS were identified, including IT infrastructure and language clarity. Several solutions to overcome the barriers were proposed by participants, including education strategies and innovation champions.

Conclusion: Future research should explore the importance of IT infrastructure in supporting AI adoption, examine the terminology around AI and explore specialty-specific barriers to AI adoption in greater depth.

Keywords: NHS; adoption; artificial intelligence; machine learning.

PubMed Disclaimer

References

    1. Fenech M. AI for physicians: What should you be doing? Royal College of Physicians, 2019. www.rcp.ac.uk/news/ai-physicians-what-should-you-be-doing [Accessed 02 December 2020].
    1. Topol EJ. High-performance medicine: The convergence of human and artificial intelligence. Nat Med 2019;25:44–56. - PubMed
    1. Loh E. Medicine and the rise of the robots: A qualitative review of recent advances of artificial intelligence in health. BMJ Lead 2018;2:59–63.
    1. Minsky ML. Semantic Information Processing. Massachusetts: The MIT Press, 1968.
    1. Ongsulee P. Artificial intelligence, machine learning and deep learning. 15th International Conference on ICT and Knowledge Engineering (ICT&KE) 2017:1–6. https://ieeexplore.ieee.org/document/8259629 [Accessed 02 December 2020].