Advanced search
2 files | 5.79 MB Add to list

Probabilistic priority assessment of nurse calls

(2014) MEDICAL DECISION MAKING. 34(4). p.485-502
Author
Organization
Abstract
Current nurse call systems are very static. Call buttons are fixed to the wall, and systems do not account for various factors specific to a situation. We have developed a software platform, the ontology-based Nurse Call System (oNCS), which supports the transition to mobile and wireless nurse call buttons and uses an intelligent algorithm to address nurse calls. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff and patients into account by using an ontology. This article describes a probabilistic extension of the oNCS that supports a more sophisticated nurse call algorithm by dynamically assigning priorities to calls based on the risk factors of the patient and the kind of call. The probabilistic oNCS is evaluated through implementation of a prototype and simulations, based on a detailed dataset obtained from 3 nursing departments of Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls among nurses, and the assignment of priorities to calls are compared for the oNCS and the current nurse call system. Additionally, the performance of the system and the parameters of the priority assignment algorithm are explored. The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the probabilistic oNCS significantly improves the assignment of nurses to calls. Calls generally result in a nurse being present more quickly, the workload distribution among the nurses improves, and the priorities and kinds of calls are taken into account.
Keywords
MANAGEMENT-SYSTEM, IBCN, SATISFACTION, nurse call assignment, probabilistic, priority assignment, reasoning, ontology

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 4.44 MB
  • 6185 i.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 1.35 MB

Citation

Please use this url to cite or link to this publication:

MLA
Ongenae, Femke et al. “Probabilistic Priority Assessment of Nurse Calls.” MEDICAL DECISION MAKING 34.4 (2014): 485–502. Print.
APA
Ongenae, F., Myny, D., Dhaene, T., Defloor, T., Van Goubergen, D., Verhoeve, P., Decruyenaere, J., et al. (2014). Probabilistic priority assessment of nurse calls. MEDICAL DECISION MAKING, 34(4), 485–502.
Chicago author-date
Ongenae, Femke, Dries Myny, Tom Dhaene, Tom Defloor, Dirk Van Goubergen, Piet Verhoeve, Johan Decruyenaere, and Filip De Turck. 2014. “Probabilistic Priority Assessment of Nurse Calls.” Medical Decision Making 34 (4): 485–502.
Chicago author-date (all authors)
Ongenae, Femke, Dries Myny, Tom Dhaene, Tom Defloor, Dirk Van Goubergen, Piet Verhoeve, Johan Decruyenaere, and Filip De Turck. 2014. “Probabilistic Priority Assessment of Nurse Calls.” Medical Decision Making 34 (4): 485–502.
Vancouver
1.
Ongenae F, Myny D, Dhaene T, Defloor T, Van Goubergen D, Verhoeve P, et al. Probabilistic priority assessment of nurse calls. MEDICAL DECISION MAKING. 2014;34(4):485–502.
IEEE
[1]
F. Ongenae et al., “Probabilistic priority assessment of nurse calls,” MEDICAL DECISION MAKING, vol. 34, no. 4, pp. 485–502, 2014.
@article{5782399,
  abstract     = {Current nurse call systems are very static. Call buttons are fixed to the wall, and systems do not account for various factors specific to a situation. We have developed a software platform, the ontology-based Nurse Call System (oNCS), which supports the transition to mobile and wireless nurse call buttons and uses an intelligent algorithm to address nurse calls. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff and patients into account by using an ontology. This article describes a probabilistic extension of the oNCS that supports a more sophisticated nurse call algorithm by dynamically assigning priorities to calls based on the risk factors of the patient and the kind of call. The probabilistic oNCS is evaluated through implementation of a prototype and simulations, based on a detailed dataset obtained from 3 nursing departments of Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls among nurses, and the assignment of priorities to calls are compared for the oNCS and the current nurse call system. Additionally, the performance of the system and the parameters of the priority assignment algorithm are explored. The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the probabilistic oNCS significantly improves the assignment of nurses to calls. Calls generally result in a nurse being present more quickly, the workload distribution among the nurses improves, and the priorities and kinds of calls are taken into account.},
  author       = {Ongenae, Femke and Myny, Dries and Dhaene, Tom and Defloor, Tom and Van Goubergen, Dirk and Verhoeve, Piet and Decruyenaere, Johan and De Turck, Filip},
  issn         = {0272-989X},
  journal      = {MEDICAL DECISION MAKING},
  keywords     = {MANAGEMENT-SYSTEM,IBCN,SATISFACTION,nurse call assignment,probabilistic,priority assignment,reasoning,ontology},
  language     = {eng},
  number       = {4},
  pages        = {485--502},
  title        = {Probabilistic priority assessment of nurse calls},
  url          = {http://dx.doi.org/10.1177/0272989X13517179},
  volume       = {34},
  year         = {2014},
}

Altmetric
View in Altmetric
Web of Science
Times cited: