[Ludovica Durst]

 
Collaborative Notes Link: https://docs.google.com/document/d/146kqGG1WhnSdGmcUd10PQ9mOqpAHelCNH7rP…
 

Brief introduction to the HDIG
Presentation on pseudonymisation and anonymisation issues and general recommendations for

facilitating the usage of big data and artificial intelligence
improving transparency of scientific work with health data

Q&A and discussion on topics presented
Next steps

Additional links to informative material
• Group page: https://rd-alliance.org/groups/health-data.html
• Case statement: https://www.rd-alliance.org/group/health-data/case-statement/health-data.html  
• HDIG Sessions Presentations @RDA Plenaries (HDIG File Repository): https://www.rd-alliance.org/node/50708/repository
 

Are you willing to hold your session at multiple times to accommodate various time zones?
No

Avoid conflict with the following group (1)
Blockchain Applications in Health WG

Avoid conflict with the following group (3)
Life Science Data Infrastructures IG

Group chair serving as contact person
Ludovica Durst

Meeting objectives
This session intends to re-propose the themes scheduled for the last plenary, which could not be discussed due to the difficulties caused by the pandemic, and which appear still and even more relevant in the light of the Covid-19 emergency.
While open data sharing practices have moved to the forefront of many scientific disciplines, there is still much to define when it comes to sharing health data due to pressing privacy concerns. Yet, the boundaries for effective and secure data sharing are now set clearly in many jurisdictions, and and especially in the EU GDPR, and can be met with vigilant practices and appropriate privacy-preserving solutions.
A particular area of interest is the distinction in the GDPR between pseudonymisation and anonymisation of health data. The first relates to the processing of health data ways by which they can no longer be attributed to a specific data subject without the use of additional information, provided that such additional information is kept separately and is subject to technical and organisational measures to ensure that the personal data are not attributed to an identified or identifiable natural person. The second, i.e. anonymisation, is the process by which health data are irreversibly altered in such a way that a data subject can no longer be identified directly or indirectly, either by the data controller alone or in collaboration with any other party.
There is a well-known risk of trade-off between information richness of health data and their re-identifiability, though there are also advanced ways for decoupling the link between private information and the health data’s information content.
Current difficulties in knowing how to concretely address data sharing restrict the possibility of adequately applying big data and artificial intelligence to the healthcare domain. Furthermore, bio-medical researchers and pharma companies are often hindered in transparently reporting their findings due to privacy concerns.
The Health Data Interest Group will use the session to discuss what can and should be implemented when presenting work/research on health data to maintain individuals’ privacy and trust in the scientific integrity of the performed work.

Please indicate the breakout slot (s) that would suit your meeting
Breakout 1, Breakout 3, Breakout 5

Privacy Policy
1

Discussion