A protocol for a Delphi study investigating the ethical and data governance issues of artificial intelligence in surgery
File(s)Lam_Investigating the ethical and data_JMIR.pdf (186.13 KB)
Published version
Author(s)
Lam, Kyle
Iqbal, Fahad
Purkayastha, sanjay
Kinross, james
Type
Journal Article
Abstract
Background: The rapid uptake of digital technology into the operating room has the potential to improve patient outcomes, increase efficiency of the use of operating rooms, and allow surgeons to progress quickly up learning curves. These technologies are, however, dependent on huge amounts of data, and the consequences of their mismanagement are significant. While the field of artificial intelligence ethics is able to provide a broad framework for those designing and implementing these technologies into the operating room, there is a need to determine and address the ethical and data governance challenges of using digital technology in this unique environment.
Objective: The objectives of this study are to define the term digital surgery and gain expert consensus on the key ethical and data governance issues, barriers, and future research goals of the use of artificial intelligence in surgery.
Methods: Experts from the fields of surgery, ethics and law, policy, artificial intelligence, and industry will be invited to participate in a 4-round consensus Delphi exercise. In the first round, participants will supply free-text responses across 4 key domains: ethics, data governance, barriers, and future research goals. They will also be asked to provide their understanding of the term digital surgery. In subsequent rounds, statements will be grouped, and participants will be asked to rate the importance of each issue on a 9-point Likert scale ranging from 1 (not at all important) to 9 (critically important). Consensus is defined a priori as a score of 7 to 9 by 70% of respondents and 1 to 3 by less than 30% of respondents. A final online meeting round will be held to discuss inclusion of statements and draft a consensus document.
Results: Full ethical approval has been obtained for the study by the local research ethics committee at Imperial College, London (20IC6136). We anticipate round 1 to commence in January 2021.
Conclusions: The results of this study will define the term digital surgery, identify the key issues and barriers, and shape future research in this area.
Objective: The objectives of this study are to define the term digital surgery and gain expert consensus on the key ethical and data governance issues, barriers, and future research goals of the use of artificial intelligence in surgery.
Methods: Experts from the fields of surgery, ethics and law, policy, artificial intelligence, and industry will be invited to participate in a 4-round consensus Delphi exercise. In the first round, participants will supply free-text responses across 4 key domains: ethics, data governance, barriers, and future research goals. They will also be asked to provide their understanding of the term digital surgery. In subsequent rounds, statements will be grouped, and participants will be asked to rate the importance of each issue on a 9-point Likert scale ranging from 1 (not at all important) to 9 (critically important). Consensus is defined a priori as a score of 7 to 9 by 70% of respondents and 1 to 3 by less than 30% of respondents. A final online meeting round will be held to discuss inclusion of statements and draft a consensus document.
Results: Full ethical approval has been obtained for the study by the local research ethics committee at Imperial College, London (20IC6136). We anticipate round 1 to commence in January 2021.
Conclusions: The results of this study will define the term digital surgery, identify the key issues and barriers, and shape future research in this area.
Date Issued
2021-02-22
Date Acceptance
2021-01-19
Citation
JMIR Research Protocols, 2021, 10 (2)
ISSN
1929-0748
Publisher
JMIR Publications
Journal / Book Title
JMIR Research Protocols
Volume
10
Issue
2
Copyright Statement
©Kyle Lam, Fahad M Iqbal, Sanjay Purkayastha, James M Kinross. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 22.02.2021.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.
License URL
Subjects
Delphi
artificial intelligence
data governance
digital surgery
digital technology
ethics
operating room
surgery
1103 Clinical Sciences
1117 Public Health and Health Services
Publication Status
Published
Article Number
ARTN e26552