Meta-analysis of privacy legal framework: revising the various approaches for balancing privacy risks and usability of healthcare information systems | Meta-analisi del quadro normativo sulla privacy: revisione dei differenti approcci per bilanciare i rischi per la privacy e l'usabilità dei sistemi informativi sanitari - Matjaž Drev; Dalibor Stanimirović; Boštjan Delak (European Journal of Privacy Law & Technologies)
The integration of information and communication technologies with advanced machine learning, or artificial intelligence, brings both benefits and risks. These risks are particularly relevant in the context of personal data protection in healthcare, where non-compliance with legal requirements can lead to severe consequences for patients and substantial fines for healthcare institutions. A proactive approach to managing these risks involves the use of privacy by design frameworks and conceptual tools. This paper presents an overview of key privacy framework, highlighting their potential to deepen theoretical understanding and support the development of conceptual models that may enhance data protection in healthcare. Using qualitative and comparative research focused on content analysis, this study examines the role of these frameworks in embedding privacy principles within organizations. While primarily theoretical, the findings provide deeper insights into the principles underlying information privacy and lay a foundation for practical applications, such as testing frameworks through case studies to improve privacy compliance.