  As electronic data becomes the lifeline of modern society, privacy concerns
increase. These concerns are reflected by the European Union's enactment of the
General Data Protection Regulation (GDPR), one of the most comprehensive and
robust privacy regulations globally. This project aims to evaluate and
highlight associations between eHealth systems' policies and personal data
privacy regulations. Using bias-corrected Cramer's V and Thiel's U tests, we
found weak and zero associations between e-health systems' rules and
protections for data privacy. A simple decision tree model is trained, which
validates the association scores obtained
