Trustworthy adoption of AI in healthcare

The healthcare research programme has a strategic focus to support the assurance based adoption of AI in healthcare - building on knowledge we gained through our whitepaper How do I turn this on? What to consider when adopting AI-based tools into clinical practice.

DNV is exploring assurance, cybersecurity, quality, privacy, regulatory and digitalisation across projects related to federated health networks, synthetic data, EHR exchange and HTA of digital health technologies through involvement in a Nordic Innovation Project, two Horizon Europe research projects and an NFR funded PhD.

FederatedHealth aims to harness the potential of unstructured data in Electronic Health Record (EHR) systems by developing a federated health data network in the Nordics, using distributed machine learning to ensure data privacy while processing multilingual clinical text from several languages. DNV is leading the identification and analysis of barriers for implementing the federated learning approach and mapping solutions to overcome these. DNV is also assessing the data and model security chosen for the federated learning infrastructure. 

EDiHTA aims to create the first flexible, inclusive, validated and ready-for-use European health technology assessment (HTA) framework allowing the systematic assessment of different Digital Health Technologies to inform healthcare decision-makers of the rationale for their implementation. DNV will contribute to the creation of the framework with cybersecurity and regulatory expertise. DNV will also lead the development of the digital solution for operationalization of the EDiHTA framework in the EU.

xShare aims to enable the European population to share their health data in EEHRxF with a click-of-a-button through co-design of a standards and policy hub and creation of the xShare industry label. DNV will contribute to the development of recommendations for European Electronic Health Record eXchange Format (EEHRxF) testing and assurance and capacity building on eID, security and privacy in health. 

In an NFR funded PhD project, DNV with partners Oslo University Hospital, the Cancer Registry of Norway and the University of Oslo is exploring how the use of synthetic data for AI development and validation can be assessed to ensure safe implementation of AI in healthcare. As healthcare data, with its inherently sensitive nature, is often challenging to share and process, synthetic data is increasingly seen as a practical way to speed up the development process while protecting patient privacy. The project will also investigate reidentification risk and their legal consequences for different use case scenarios.