The usage of healthcare data for analytics and patient applications has increased in recent years opening a number of technical, ethical and scientific challenges. Among these, those related to the management of personal and sensitive health data have been addressed through decentralized solutions for patient data, often implemented and modelled using distributed agents and semantic technologies. In this paper, we present a technical summary of our previous works in this area, comprising efforts to: (i) use ontology models to represent patient trajectories,(ii) employ agent-based architectures to model and employ decentralized patient data exchanges, (iii) define agent cooperation and negotiation strategies for healthcare data interactions, (iv) adopt semantic data models for privacy-aware agents, and (v) implement multi-agent systems for real-time healthcare data processing