The 'Hippocratic Oath' for AI-based clinical decision support systems
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Background
The implementation of Artificial Intelligence assisted Clinical Decision Support Systems (AI-CDSS) shows significant potential to improve healthcare. However, implementing AI-CDSS has many associated challenges. This article introduces the ‘Hippocratic Oath’ for AI which promotes safe and effective AI-CDSS development and implementation.
Methods
This paper summarises discussions which took place during the Turing-Roche Clinical AI Interest Group Joint Workshop. The workshop began with scoping lectures from AI experts, leading into focus group discussions of key themes surrounding AI-CDSS implementation. These include the ethics, trust, evaluation, regulation, human factors and challenges involved with implementing AI-CDSS into healthcare settings. Focus group outcomes, alongside insight from lectures, were used to formulate the arguments in this paper.
Results
This article presents a consensus definition of AI-CDSS and outlines a comprehensive table of implementation challenges alongside mitigation measures. It introduces the ‘Hippocratic Oath for AI’ and discusses its potential to promote safe and effective AI-CDSS implementation through addressing human factors and explainability.
Conclusions
The ‘Hippocratic Oath for AI’, can be used by AI-CDSS implementers and developers as a framework to mitigate challenges involved with implementing AI-CDSS into healthcare settings. This framework is likely to promote safe and effective implementation and maximise HCP uptake of the AI-CDSS. Through facilitating AI-CDSS use, this oath can transform health care practice via reducing medical errors, healthcare costs and improving patient outcomes.
The implementation of Artificial Intelligence assisted Clinical Decision Support Systems (AI-CDSS) shows significant potential to improve healthcare. However, implementing AI-CDSS has many associated challenges. This article introduces the ‘Hippocratic Oath’ for AI which promotes safe and effective AI-CDSS development and implementation.
Methods
This paper summarises discussions which took place during the Turing-Roche Clinical AI Interest Group Joint Workshop. The workshop began with scoping lectures from AI experts, leading into focus group discussions of key themes surrounding AI-CDSS implementation. These include the ethics, trust, evaluation, regulation, human factors and challenges involved with implementing AI-CDSS into healthcare settings. Focus group outcomes, alongside insight from lectures, were used to formulate the arguments in this paper.
Results
This article presents a consensus definition of AI-CDSS and outlines a comprehensive table of implementation challenges alongside mitigation measures. It introduces the ‘Hippocratic Oath for AI’ and discusses its potential to promote safe and effective AI-CDSS implementation through addressing human factors and explainability.
Conclusions
The ‘Hippocratic Oath for AI’, can be used by AI-CDSS implementers and developers as a framework to mitigate challenges involved with implementing AI-CDSS into healthcare settings. This framework is likely to promote safe and effective implementation and maximise HCP uptake of the AI-CDSS. Through facilitating AI-CDSS use, this oath can transform health care practice via reducing medical errors, healthcare costs and improving patient outcomes.
Date Issued
2026-12-01
Date Acceptance
2026-03-31
Citation
BMC Medical Informatics and Decision Making, 2026, 26 (1)
ISSN
1472-6947
Publisher
BMC
Journal / Book Title
BMC Medical Informatics and Decision Making
Volume
26
Issue
1
Copyright Statement
© The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/42063107
PII: 10.1186/s12911-026-03474-5
Subjects
Artificial intelligence
Clinical decision support systems
Ethics
Healthcare
Hippocratic Oath
Publication Status
Published
Coverage Spatial
England
Article Number
ARTN 292
Date Publish Online
2026-04-30