Trustworthy adoption of AI in healthcare

AI-based tools are entering the healthcare domain helping us improve patient outcomes by utilising data produced both in clinical and research settings. Despite interest from both clinicians and management, the adoption of these tools in healthcare settings are still limited. We aim to facilitate the safe adoption of AI in healthcare by supporting healthcare institutions to have a better understanding of important considerations when adopting AI.
Genome and doctor graphic

It is a prerequisite to explore real-world barriers and challenges for adopting AI in healthcare all the way from the ideation phase to actual implementation and monitoring the use to understand why AI benefits and adoption are not a widespread reality in healthcare today. Closing the gap between what should be done and what realistically can be done is key to unlocking the benefits AI can have for improving patient outcomes.

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Harry Hallock

Harry Hallock

Senior Researcher

In this project, we are gathering lessons learned from key stakeholders in implementing AI into clinical practice. We are engaging with stakeholders and AI adoption pioneers who have been involved in or are starting to implement AI within specialist healthcare, primary healthcare or direct to consumer (patient) solutions. Through workshops, interviews, and literature reviews, we gather and synthesize key findings that are aimed to guide those who are planning to use AI. 

DNV is involved in two Horizon 2020 research projects and a NFR funded PhD all aimed at using artificial intelligence to improve health outcomes. 

REALMENT aims to bring personalized medicine interventions to psychiatry, by developing a real-world data platform and a clinical management platform to improve and optimize treatment of mental disorders through novel artificial intelligence and machine learning tools. DNV is leading exploratory activities identifying and analyzing trust needs for safety, security and transparency as well as assessing regulatory requirements and guidelines to enable lawful and ethical access to data sets and data sharing for further data exploitation by independent parties. 

AI-MIND aims to reduce the burden of dementia by developing novel, AI-based tools to support healthcare professionals in predicting dementia, thus enabling earlier interventions for patients. DNV’s involvement includes, delivering a guideline for legal and ethical data processing; developing a framework for data governance and data management framework; designing and implementing a data model; and developing and implementing methods for continuous data quality assurance. 

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 possible privacy implications.

Contact us:

Harry Hallock

Harry Hallock

Senior Researcher