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The paper aims to describe a new technological and organizational approach in order to manage teleconsultation and telemonitoring processes involving a Physician, who remotely interacts with one or more Specialists, in order to evaluate and discuss the specific clinical conditions of a patient, based primarily on the sharing of digital clinical data, reports and diagnostic images. In the HINT project (Healthcare INtegration in Telemedicine), a teleconsultation and telemonitoring cloud platform has been developed using a Hub and Spoke architecture, based on a Business Process Management System (BPMS). The specialized clinical centres (Hubs) operate in connection with the territorial hospital centres (Spokes), which receive specific diagnostic consultations and telemonitoring data from the appropriate Specialist, supported by advanced AI systems. The developed platform overcomes the concepts of a traditional and fragmented teleconsultation and consequently the static organization of Hubs and Spokes, evolving towards an integrated clinical workflow management. The project platform adopts international healthcare standards, such as HL7 FHIR, IHE (XDS and XDW) and DICOM for the acquisition and management of healthcare data and diagnostic images. A Workflow Management System implemented in the platform allows to manage multiple and contemporaneous processes through a single platform, correctly associating the tasks to the Physicians responsible for their execution, monitoring the status of the health activities and managing possible clinical issues.

The main purpose of this work is to describe the process of design and implementation of a novel e-Learning platform, named Digital Brick, intended to enhance the students’ experience in obtaining formal certifications of their competencies. The research method we followed starts form a deep study of the state of the art that showed us the need to invest more research effort on delivering open and flexible online environments to enable students in finding and passing courses with final formal certifications of learning. To reach this goal, we (i) designed a complete system architecture around a standard (SCORM compliant) learning management system in order the approach should be reusable as much as possible. We (ii) introduced specific modules to separate responsibilities on the definition and issuing of formal certifications using digital badges according to the IMS Open Badges standard. We (iii) exploited blockchain technology to make the sharing of badges among actors more secure, transparent and open. Finally, we (iv) introduced a new recommendation algorithm based on machine learning techniques to give advice to students about study materials and learning paths. We spent a significant part of our effort carrying out both a functional and quantitative validation of our proposal. The obtained results are presented through a laboratory case study that involves all the components of the architecture, and the outcomes are discussed providing numerical performance indicators. In conclusion, the resulting platform introduces digital badges and blockchain as tools to share recognized achievements among earners and issuers, and machine learning algorithms to provide students with recommendations on the learning material, learning objects, courses and learning paths more suitable for their learning styles.