Nurses' experiences and perspectives on aEEG monitoring in neonatal care: A qualitative study
Authors/Creators
- 1. Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, the Netherlands
- 2. Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Reykjavík, Iceland
- 3. Kvikna Medical ehf., Reykjavík, Iceland
- 4. Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
Description
Purpose
This study aimed to gather nurses’ experiences and perspectives regarding the amplitude-integrated electroencephalogram (aEEG) monitoring system in neonatal intensive care units (NICUs) and to explore potential avenues for future improvements.
Design and Methods
This study employed a descriptive qualitative design. Semi-structured interviews were conducted with 20 nurses from the level-III NICU of a Dutch medical center. The collected interview data were analyzed using thematic analysis.
Results
Seven main themes emerged: training in aEEG monitoring, proficiency in aEEG electrode placement and pattern interpretation, usual practices of using aEEG, neonatologist-nurse cooperation on aEEG, the performance of the automated seizure detection software, the usefulness of aEEG monitoring in the NICU, and feedback about the current aEEG monitoring system.
Conclusions
Nurses confirmed that aEEG is a valuable tool for cerebral function monitoring in the NICU; however, improvements are necessary. For better utilization of aEEG in the NICU, it is recommended to enhance nurses’ aEEG knowledge and skills and apply state-of-art techniques to improve the monitoring system.
Practice implications
To enhance the aEEG knowledge of NICU nurses, we suggest introducing structured training programs, conducting routine case-centered discussions, and creating readily available reference resources. To optimize the aEEG monitoring system, it is essential to incorporate innovative electrodes, provide remote accessibility, integrate advanced algorithms, and develop an intuitive graphical user interface.
Files
1-s2.0-S1355184123001503-main.pdf
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