Validation framework for the use of AI in healthcare: overview of the new British standard BS30440

[...]the landscape of guidance on how to develop safe and effective AI systems for healthcare is fragmented across hundreds of documents, largely with a focus on products that would be regulated as medical devices. [...]BS30440 represents a fully auditable standard for the assessment of healthcare A...

Full description

Saved in:
Bibliographic Details
Published in:BMJ health & care informatics 2023-06, Vol.30 (1), p.e100749
Main Authors: Sujan, Mark, Smith-Frazer, Cassius, Malamateniou, Christina, Connor, Joseph, Gardner, Allison, Unsworth, Harriet, Husain, Haider
Format: Article
Language:English
Subjects:
Artificial Intelligence
Communication
Conformity
Delivery of Health Care
Design
health care sector
Health Facilities
Humans
Internal auditors
machine learning
Medical equipment
medical informatics
Medical technology
Patients
Standardization
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:[...]the landscape of guidance on how to develop safe and effective AI systems for healthcare is fragmented across hundreds of documents, largely with a focus on products that would be regulated as medical devices. [...]BS30440 represents a fully auditable standard for the assessment of healthcare AI products. Structure and assessment criteria BS30440 is structured around a product life-cycle for healthcare AI, described in five phases: inception, development, validation, deployment and monitoring. While international committees including International Organization for Standardization (ISO) / International Electrotechnical Commission Subcommittee (IEC SC) 42 and European Committee for Standardization (CEN) / European Committee for Electrotechnical Standardization (CENELECT) Joint Technical Committee 21 (JTC21) have published standards and are in the process of developing their future work programmes, these initiatives are not specific to healthcare AI.
ISSN:2632-1009
2632-1009
DOI:10.1136/bmjhci-2023-100749