Nursing Implementation of Pupillometry in a Pediatric Epilepsy Monitoring Unit
INTRODUCTION: In pediatric epilepsy monitoring units (EMU), nurses are essential in assessing seizure activity and neurological status. One critical element of neurological evaluation is the pupillary light reflex (PLR), traditionally assessed manually with low interrater reliability. Quantitative pupillometry offers a more accurate and reliable method for evaluating PLR, yet its use in EMUs has not been well described. The objective is to describe the implementation of quantitative pupillometry in a pediatric EMU through a nurse-led initiative. METHODS: A collaborative effort between nursing and physician leadership introduced the NPi-200 pupillometer in a pediatric EMU. Nurses received hands-on training, and a standardized electronic order was developed to integrate the tool into clinical workflows. Accessibility issues were addressed by relocating the device to a central nursing station. RESULTS: Over the pilot period, 40 patients underwent pupillometry assessments, with 88% yielding complete data. No adverse events occurred. Nurses reported the device was easy to use and successfully incorporated it into their routine care, even for children with developmental delay. CONCLUSION: Pupillometry can be effectively and safely implemented in the pediatric EMU setting through a nurse-driven process. This initiative demonstrated high usability, safety, and integration into clinical practice, supporting its broader use for neurological monitoring in epilepsy care.
Authors
- DaiWai M. Olson (ORCID: https://orcid.org/0000-0002-9280-078X)
- Afsaneh Talai (ORCID: https://orcid.org/0000-0001-6478-325X)
- Meagan Hainlen
- Jennifer L. Watt
Institutions
- Center For Children With Special Needs (US)
- Southwestern Medical Center (US)
- The University of Texas Southwestern Medical Center (US)
Publication Details
- Journal
- Journal of Neuroscience Nursing
- Published
- 2025-12-30
- DOI
- https://doi.org/10.1097/jnn.0000000000000863
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00