Literature DB >> 33616543

Investigating the Ethical and Data Governance Issues of Artificial Intelligence in Surgery: Protocol for a Delphi Study.

Kyle Lam1, Fahad M Iqbal1, Sanjay Purkayastha1, James M Kinross1.   

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. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/26552. ©Kyle Lam, Fahad M Iqbal, Sanjay Purkayastha, James M Kinross. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 22.02.2021.

Entities:  

Keywords:  Delphi; artificial intelligence; data governance; digital surgery; digital technology; ethics; operating room; surgery

Year:  2021        PMID: 33616543     DOI: 10.2196/26552

Source DB:  PubMed          Journal:  JMIR Res Protoc        ISSN: 1929-0748


  5 in total

Review 1.  Machine learning for technical skill assessment in surgery: a systematic review.

Authors:  Kyle Lam; Junhong Chen; Zeyu Wang; Fahad M Iqbal; Ara Darzi; Benny Lo; Sanjay Purkayastha; James M Kinross
Journal:  NPJ Digit Med       Date:  2022-03-03

Review 2.  Implementation Frameworks for Artificial Intelligence Translation Into Health Care Practice: Scoping Review.

Authors:  Fábio Gama; Daniel Tyskbo; Jens Nygren; James Barlow; Julie Reed; Petra Svedberg
Journal:  J Med Internet Res       Date:  2022-01-27       Impact factor: 5.428

3.  A Delphi consensus statement for digital surgery.

Authors:  Kyle Lam; Michael D Abràmoff; José M Balibrea; Steven M Bishop; Richard R Brady; Rachael A Callcut; Manish Chand; Justin W Collins; Markus K Diener; Matthias Eisenmann; Kelly Fermont; Manoel Galvao Neto; Gregory D Hager; Robert J Hinchliffe; Alan Horgan; Pierre Jannin; Alexander Langerman; Kartik Logishetty; Amit Mahadik; Lena Maier-Hein; Esteban Martín Antona; Pietro Mascagni; Ryan K Mathew; Beat P Müller-Stich; Thomas Neumuth; Felix Nickel; Adrian Park; Gianluca Pellino; Frank Rudzicz; Sam Shah; Mark Slack; Myles J Smith; Naeem Soomro; Stefanie Speidel; Danail Stoyanov; Henry S Tilney; Martin Wagner; Ara Darzi; James M Kinross; Sanjay Purkayastha
Journal:  NPJ Digit Med       Date:  2022-07-19

4.  Identifying essential factors that influence user engagement with digital mental health tools in clinical care settings: Protocol for a Delphi study.

Authors:  Brian Lo; Quynh Pham; Sanjeev Sockalingam; David Wiljer; Gillian Strudwick
Journal:  Digit Health       Date:  2022-10-11

5.  Investigating the Implementation of SMS and Mobile Messaging in Population Screening (the SIPS Study): Protocol for a Delphi Study.

Authors:  Amish Acharya; Gaby Judah; Hutan Ashrafian; Viknesh Sounderajah; Nick Johnstone-Waddell; Anne Stevenson; Ara Darzi
Journal:  JMIR Res Protoc       Date:  2021-12-22
  5 in total

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