THESIS - Context-aware patient alarm prioritization and caregiver routing using knowledge graphs
Izegem, Belgium
About Televic Healthcare
At Televic Healthcare, we are at the forefront of revolutionizing healthcare through cutting-edge communication and information technology. We specialize in designing, developing and manufacturing innovative solutions that enhance patient care, streamline processes and empower healthcare professionals. We work in a channel model through certified partners internationally and our ambition is to become the reference in our niche market through innovation.
Topic Description
Reliable patient monitoring and timely alarming are essential in today's healthcare landscape. Televic Healthcare provides professional solutions for nurse calls, patient localization, and mobile alarming systems. However, hospitals and care facilities currently face increasing pressures: staff shortages, particularly among nurses, rising operational costs, and the ongoing demand for high-quality care. Consequently, optimizing care workflows to enhance efficiency and staff motivation has become critical.
This thesis explores a context-aware communication system designed to optimize how healthcare staff, particularly nurses, handle alerts and tasks. By considering real-time contextual factors — including call triggers, caregiver and patient locations, current caregiver activities, and detailed profiles of both patients and nurses —the proposed system dynamically routes alerts and tasks to the most suitable caregivers.
During this research, the following concrete objectives will be achieved:
* Context Modeling with Knowledge Graphs: Employ multi-modal data aggregation and semantic modeling techniques using ontologies to represent context explicitly. Ontologies will structure and integrate diverse data such as patient conditions, staff capabilities, environmental sensors, and location information.
* Stakeholder Profiling and Proactive Support: Develop comprehensive profiles of nurses and patients, facilitating proactive decision support by anticipating care requirements and adjusting communication strategies accordingly.
* Implementation of a Proof-of-Concept: Build a demonstrative prototype utilizing semantic reasoning methods, such as OWL2 RL ontologies and rule-based reasoning, to automate decision-making and enhance proactive alarm management. This prototype will validate the feasibility and effectiveness of the proposed context-aware solution.
Through leveraging advanced ontology-driven semantic modeling and stream reasoning techniques, this thesis aims to deliver a tangible improvement in healthcare operational efficiency and caregiver responsiveness.
Nature of the work
- Level: Bachelor, Master
- AI
- Location: University and Televic Healthcare (Izegem)
- Number of students: 1 or 2