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Open Access Research article

An ontology-based nurse call management system (oNCS) with probabilistic priority assessment

Femke Ongenae1*, Dries Myny2, Tom Dhaene1, Tom Defloor3, Dirk Van Goubergen4, Piet Verhoeve5, Johan Decruyenaere6 and Filip De Turck1

Author Affiliations

1 Ghent University - IBBT, Department of Information Technology (INTEC), Gaston Crommenlaan 8, bus 201, 9050 Ghent, Belgium

2 Ghent University Hospital, Nursing department, De Pintelaan 185, 9000 Ghent, Belgium

3 Ghent University, Faculty of Medicine and Health Sciences, Nursing Science, Ghent, Belgium, Pintelaan 185, 9000 Ghent, Belgium

4 Ghent University, Department of Industrial Management, Technology Park 903, 9052 Zwijnaarde, Belgium

5 Televic R&D, Leo Bekaertlaan 1, 8870 Izegem, Belgium

6 Ghent University Hospital, Intensive Care Department, De Pintelaan 185, 9000 Ghent, Belgium

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BMC Health Services Research 2011, 11:26  doi:10.1186/1472-6963-11-26

Published: 4 February 2011

Abstract

Background

The current, place-oriented nurse call systems are very static. A patient can only make calls with a button which is fixed to a wall of a room. Moreover, the system does not take into account various factors specific to a situation. In the future, there will be an evolution to a mobile button for each patient so that they can walk around freely and still make calls. The system would become person-oriented and the available context information should be taken into account to assign the correct nurse to a call.

The aim of this research is (1) the design of a software platform that supports the transition to mobile and wireless nurse call buttons in hospitals and residential care and (2) the design of a sophisticated nurse call algorithm. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff members and patients into account. Additionally, the priority of a call probabilistically depends on the risk factors, assigned to a patient.

Methods

The ontology-based Nurse Call System (oNCS) was developed as an extension of a Context-Aware Service Platform. An ontology is used to manage the profile information. Rules implement the novel nurse call algorithm that takes all this information into account. Probabilistic reasoning algorithms are designed to determine the priority of a call based on the risk factors of the patient.

Results

The oNCS system is evaluated through a prototype implementation and simulations, based on a detailed dataset obtained from Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls amongst nurses and the assignment of priorities to calls are compared for the oNCS system and the current, place-oriented nurse call system. Additionally, the performance of the system is discussed.

Conclusions

The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the oNCS system significantly improves the assignment of nurses to calls. Calls generally have a nurse present faster and the workload-distribution amongst the nurses improves.