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An ontology-based nurse call management system (oNCS) with probabilistic priority assessment
Femke Ongenae1, Dries Myny, Tom Dhaene
1Ghent University-IBBT, Department of Information Technology (INTEC), Gaston Crommenlaan 8, bus 201, 9050 Ghent, Belgium. Femke.Ongenae@intec.ugent.be
The ontology-based Nurse Call System (oNCS) enhances patient care by enabling mobile nurse call buttons and a smart algorithm. This system improves nurse response times and workload distribution for better healthcare.
Area of Science:
- Healthcare technology
- Computer science
- Artificial intelligence
Background:
- Current nurse call systems are static and place-based, limiting patient mobility and situational context.
- Future systems require mobile, person-oriented solutions that leverage contextual information for efficient nurse allocation.
Purpose of the Study:
- Design a software platform for mobile, wireless nurse call buttons in healthcare settings.
- Develop a sophisticated nurse call algorithm that dynamically adapts to patient and staff profiles and risk factors.
Main Methods:
- Developed the ontology-based Nurse Call System (oNCS) as an extension of a Context-Aware Service Platform.
- Utilized ontologies for profile management and rule-based systems for the nurse call algorithm.
- Employed probabilistic reasoning to determine call priority based on patient risk factors.
Main Results:
- Evaluated oNCS via prototype and simulations using data from Ghent University Hospital.
- Compared nurse arrival times, workload distribution, and priority assignment against traditional systems.
- Demonstrated significant improvements in nurse assignment efficiency and call handling.
Conclusions:
- The oNCS nurse call algorithm executes in an average of 50.333 ms.
- oNCS significantly enhances nurse assignment, leading to faster response times.
- The system improves workload distribution among nursing staff, optimizing resource allocation.
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