Imperial College London
Alternate

ProfessorJustinCobb

Faculty of Medicine, Department of Surgery & Cancer

Chair in Orthopaedic Surgery
 
 
 
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Contact

 

+44 (0)20 7594 5534j.cobb Website

 
 
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Assistant

 

Miss Colinette Hazel +44 (0)20 7594 2725

 
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Location

 

c/oSir Michael Uren HubWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Musbahi:2021:10.1177/20552076211063682,
author = {Musbahi, O and Syed, L and Le, Feuvre P and Cobb, J and Jones, G},
doi = {10.1177/20552076211063682},
journal = {Digital Health},
pages = {1--11},
title = {Public patient views of artificial intelligence in healthcare: A nominal group technique study},
url = {http://dx.doi.org/10.1177/20552076211063682},
volume = {7},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Objectives: The beliefs of laypeople and medical professionals often diverge with regards to disease, and technology has had a positive impact on how research is conducted. Surprisingly, given the expanding worldwide funding and research into Artificial Intelligence (AI) applications in healthcare, there is a paucity of research exploring the public patient perspective on this technology. Our study sets out to address this knowledge gap, by applying the Nominal Group Technique (NGT) to explore patient public views on AI. Methods: A Nominal Group Technique (NGT) was used involving four study groups with seven participants in each group. This started with a silent generation of ideas regarding the benefits and concerns of AI in Healthcare. This was followed by a group discussion. Then a round-robin process was conducted until no new ideas were generated. Participants then ranked their top five benefits and top five concerns regarding the use of AI in healthcare. A final group consensus was reached. Results: Twenty-Eight participants were recruited with the mean age of 47 years. The top five benefits were: Faster health services, Greater accuracy in management, AI systems available 24/7, reducing workforce burden, and equality in healthcare decision making. The top five concerns were: Data cybersecurity, bias and quality of AI data, less human interaction, algorithm errors and responsibility, and limitation in technology. Conclusion: This is the first formal qualitative study exploring patient public views on the use of AI in healthcare, and highlights that there is a clear understanding of the potential benefits delivered by this technology. Greater patient public group involvement, and a strong regulatory framework is recommended.
AU  - Musbahi,O
AU  - Syed,L
AU  - Le,Feuvre P
AU  - Cobb,J
AU  - Jones,G
DO  - 10.1177/20552076211063682
EP  - 11
PY  - 2021///
SN  - 2055-2076
SP  - 1
TI  - Public patient views of artificial intelligence in healthcare: A nominal group technique study
T2  - Digital Health
UR  - http://dx.doi.org/10.1177/20552076211063682
UR  - https://journals.sagepub.com/doi/10.1177/20552076211063682
UR  - http://hdl.handle.net/10044/1/92985
VL  - 7
ER  -
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