Legal concerns in health-related artificial intelligence: A scoping review protocol
Legal concerns in health-related artificial intelligence: A scoping review protocol
Background: Medical innovations offer tremendous hope. Yet, similar innovations in governance (law, policy, ethics) are likely necessary if society is to realize medical innovations’ fruits and avoid their pitfalls. As innovations in artificial intelligence (AI) advance at a rapid pace, scholars across multiple disciplines are articulating concerns in health-related AI that likely require legal responses to ensure the requisite balance. These scholarly perspectives may provide critical insights into the most pressing challenges that will help shape and advance future regulatory reforms. Yet, to the best of our knowledge, there is no comprehensive summary of the literature examining legal concerns in relation to health-related AI. We thus aim to summarize and map the literature examining legal concerns in health-related AI using a scoping review approach. Methods: The scoping review framework developed by (J Soc Res Methodol 8:19-32, 2005) and extended by (Implement Sci 5:69, 2010) and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews (PRISMA-ScR) guided our protocol development. In close consultation with trained librarians, we will develop a highly sensitive search for MEDLINE® (OVID) and adapt it for multiple databases designed to comprehensively capture texts in law, medicine, nursing, pharmacy, other healthcare professions (e.g., dentistry, nutrition), public health, computer science, and engineering. English- and French-language records will be included if they examine health-related AI, describe or prioritize a legal concern in health-related AI or propose a solution thereto, and were published in 2012 or later. Eligibility assessment will be conducted independently and in duplicate at all review stages. Coded data will be analyzed along themes and stratified across discipline-specific literatures. Discussion: This first-of-its-kind scoping review will summarize available literature examining, documenting, or prioritizing legal concerns in health-related AI to advance law and policy reform(s). The review may also reveal discipline-specific concerns, priorities, and proposed solutions to the concerns. It will thereby identify priority areas that should be the focus of future reforms and regulatory options available to stakeholders in reform processes. Trial registration: This protocol was submitted to the Open Science Foundation registration database. See https://osf.io/zav7w.
Artificial Intelligence, Governance, Health Law, Medical Devices, Regulation, Health, Machine learning, Health law, Scoping review, Artificial intelligence
Da Silva, Michael
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Horsley, Tanya
25ae1109-a4aa-4cb8-bd17-12f99a3ae199
Singh, Devin
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Da Silva, Emily
33c8d784-b326-45cb-9e43-77c1f96d84f9
Ly, Valentina
405998c7-6a34-480f-a55e-d3d229bc7874
Thomas, Bryan
22848ac9-0eac-45dc-b14e-d5c760176efc
Daniel, Ryan
ae0bcb86-99c9-4a2f-931a-d19a8e10f48e
Chagal-Feferkorn, Karni
c17436bf-f0b1-4673-8c16-205f15779a44
Iantomasi, Samantha
a07fddd7-f311-4acd-b039-9eee2fae2291
White, Kelli
0950cd56-efb0-4f3d-8449-4cefbe419105
Kent, Arianne
e73ade23-825a-4e32-af7c-28febaee7790
Flood, Colleen
a3853c9e-6bd3-400e-b908-140559d871a0
17 June 2022
Da Silva, Michael
05ad649f-8409-4012-8edc-88709b1a3182
Horsley, Tanya
25ae1109-a4aa-4cb8-bd17-12f99a3ae199
Singh, Devin
5051a0df-d6a5-46a6-9372-4aeadea3f0ca
Da Silva, Emily
33c8d784-b326-45cb-9e43-77c1f96d84f9
Ly, Valentina
405998c7-6a34-480f-a55e-d3d229bc7874
Thomas, Bryan
22848ac9-0eac-45dc-b14e-d5c760176efc
Daniel, Ryan
ae0bcb86-99c9-4a2f-931a-d19a8e10f48e
Chagal-Feferkorn, Karni
c17436bf-f0b1-4673-8c16-205f15779a44
Iantomasi, Samantha
a07fddd7-f311-4acd-b039-9eee2fae2291
White, Kelli
0950cd56-efb0-4f3d-8449-4cefbe419105
Kent, Arianne
e73ade23-825a-4e32-af7c-28febaee7790
Flood, Colleen
a3853c9e-6bd3-400e-b908-140559d871a0
Da Silva, Michael, Horsley, Tanya, Singh, Devin, Da Silva, Emily, Ly, Valentina, Thomas, Bryan, Daniel, Ryan, Chagal-Feferkorn, Karni, Iantomasi, Samantha, White, Kelli, Kent, Arianne and Flood, Colleen
(2022)
Legal concerns in health-related artificial intelligence: A scoping review protocol.
Systematic Reviews, 11 (1), [123].
(doi:10.1186/s13643-022-01939-y).
Abstract
Background: Medical innovations offer tremendous hope. Yet, similar innovations in governance (law, policy, ethics) are likely necessary if society is to realize medical innovations’ fruits and avoid their pitfalls. As innovations in artificial intelligence (AI) advance at a rapid pace, scholars across multiple disciplines are articulating concerns in health-related AI that likely require legal responses to ensure the requisite balance. These scholarly perspectives may provide critical insights into the most pressing challenges that will help shape and advance future regulatory reforms. Yet, to the best of our knowledge, there is no comprehensive summary of the literature examining legal concerns in relation to health-related AI. We thus aim to summarize and map the literature examining legal concerns in health-related AI using a scoping review approach. Methods: The scoping review framework developed by (J Soc Res Methodol 8:19-32, 2005) and extended by (Implement Sci 5:69, 2010) and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews (PRISMA-ScR) guided our protocol development. In close consultation with trained librarians, we will develop a highly sensitive search for MEDLINE® (OVID) and adapt it for multiple databases designed to comprehensively capture texts in law, medicine, nursing, pharmacy, other healthcare professions (e.g., dentistry, nutrition), public health, computer science, and engineering. English- and French-language records will be included if they examine health-related AI, describe or prioritize a legal concern in health-related AI or propose a solution thereto, and were published in 2012 or later. Eligibility assessment will be conducted independently and in duplicate at all review stages. Coded data will be analyzed along themes and stratified across discipline-specific literatures. Discussion: This first-of-its-kind scoping review will summarize available literature examining, documenting, or prioritizing legal concerns in health-related AI to advance law and policy reform(s). The review may also reveal discipline-specific concerns, priorities, and proposed solutions to the concerns. It will thereby identify priority areas that should be the focus of future reforms and regulatory options available to stakeholders in reform processes. Trial registration: This protocol was submitted to the Open Science Foundation registration database. See https://osf.io/zav7w.
Text
Systematic Reviews Da Silva et al AM
- Accepted Manuscript
More information
Accepted/In Press date: 28 March 2022
Published date: 17 June 2022
Additional Information:
Funding Information:
This protocol benefits from a Canadian Institutes of Health Research Project Grant, Machine M.D.: How Should We Regulate AI in Health Care? MD received post-doctoral research funding from the Alex Trebek Forum for Dialogue. KCF received post-doctoral research funding from Scotiabank. None of these funding bodies played a role in the design of this protocol.
Publisher Copyright:
© 2022, The Author(s).
Keywords:
Artificial Intelligence, Governance, Health Law, Medical Devices, Regulation, Health, Machine learning, Health law, Scoping review, Artificial intelligence
Identifiers
Local EPrints ID: 457268
URI: http://eprints.soton.ac.uk/id/eprint/457268
ISSN: 2046-4053
PURE UUID: c0e88f3e-6df2-4b1c-a3dc-9450d75bf334
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Date deposited: 30 May 2022 16:46
Last modified: 17 Mar 2024 04:12
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Contributors
Author:
Michael Da Silva
Author:
Tanya Horsley
Author:
Devin Singh
Author:
Emily Da Silva
Author:
Valentina Ly
Author:
Bryan Thomas
Author:
Ryan Daniel
Author:
Karni Chagal-Feferkorn
Author:
Samantha Iantomasi
Author:
Kelli White
Author:
Arianne Kent
Author:
Colleen Flood
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