Learning From Experience and Finding the Right Balance in the Governance of Artificial Intelligence and Digital Health Technologies.
algorithm change protocol
artificial intelligence
health care
implementation
intervention
machine learning
medical tool
patient
performance
regulation
regulatory framework
safety
technology
tool
Journal
Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882
Informations de publication
Date de publication:
14 04 2023
14 04 2023
Historique:
received:
20
10
2022
accepted:
21
02
2023
revised:
17
01
2023
medline:
18
4
2023
entrez:
14
4
2023
pubmed:
15
4
2023
Statut:
epublish
Résumé
Artificial intelligence (AI) and machine learning medical tools have the potential to be transformative in care delivery; however, this change will only be realized if accompanied by effective governance that ensures patient safety and public trust. Recent digital health initiatives have called for tighter governance of digital health. A correct balance must be found between ensuring product safety and performance while also enabling the innovation needed to deliver better approaches for patients and affordable efficient health care for society. This requires innovative, fit-for-purpose approaches to regulation. Digital health technologies, particularly AI-based tools, pose specific challenges to the development and implementation of functional regulation. The approaches of regulatory science and "better regulation" have a critical role in developing and evaluating solutions to these problems and ensuring effective implementation. We describe the divergent approaches of the European Union and the United States in the implementation of new regulatory approaches in digital health, and we consider the United Kingdom as a third example, which is in a unique position of developing a new post-Brexit regulatory framework.
Identifiants
pubmed: 37058329
pii: v25i1e43682
doi: 10.2196/43682
pmc: PMC10148205
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e43682Informations de copyright
©Stephen Gilbert, Stuart Anderson, Martin Daumer, Phoebe Li, Tom Melvin, Robin Williams. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 14.04.2023.
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