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A GDPR-Compliant Dynamic Consent Mobile Application for the Australasian Type-1 Diabetes Data Network
Zhe Wang1, Anthony Stell1, Richard O Sinnott1
1School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC 3010, Australia.
Healthcare (Basel, Switzerland)
|February 25, 2023
Summary
Australia
Area of Science:
- Diabetes research
- Health informatics
- Data privacy
Background:
- Australia faces a high prevalence of diabetes, impacting 1.2 million individuals.
- The Australasian Diabetes Data Network (ADDN) registry collects longitudinal data on type-1 diabetes (T1D).
- Increasing demand for identifiable patient data necessitates enhanced privacy and consent mechanisms.
Purpose of the Study:
- To present a mobile application designed to align ADDN data collection with GDPR.
- To implement Dynamic Consent for patient control over research data usage.
- To support dynamic opt-in consent for both the registry and sub-projects.
Main Methods:
- Development of a mobile application for ADDN data management.
- Integration of a Dynamic Consent model for informed, specific participant consent.
- Focus on GDPR compliance for data security and privacy.
Main Results:
- The designed app facilitates dynamic opt-in consent for registry participation.
- Participants can view and modify their consent preferences via an interactive interface.
- The application aims to enhance GDPR alignment for ADDN data handling.
Conclusions:
- The mobile application offers a GDPR-compliant solution for managing patient consent in diabetes research.
- Dynamic Consent empowers individuals with control over their health data.
- This approach supports ethical data sharing for research while prioritizing patient privacy.
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