Associating eHealth Policies and National Data Privacy Regulations

TL;DR

This paper investigates the relationship between eHealth policies and national data privacy regulations, finding weak or no associations through statistical tests and validating results with a decision tree model.

Contribution

It introduces a quantitative analysis of the correlation between eHealth policies and privacy regulations using statistical tests and machine learning validation.

Findings

Weak or zero association between eHealth policies and privacy protections

Statistical tests confirm low correlation levels

Decision tree model validates association scores

Abstract

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