Article
Implementation of a digital data management tool for intraoperative neuromonitoring
Entwicklung eines digitalen Datenmanagement-Tools für das intraoperative Neuromonitoring
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Authors
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Chantal Zbinden
- Inselspital, Universitätsspital Bern, Department of Neurosurgery, Neurocenter and Regenerative Neuroscience Cluster, Bern, Schweiz; Bern University of Applied Sciences, Bern, Schweiz
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Moritz Strickler
- Bern University of Applied Sciences, Bern, Schweiz
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Murat Sariyar
- Bern University of Applied Sciences, Bern, Schweiz
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Thomas Bürkle
- Bern University of Applied Sciences, Bern, Schweiz
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Andreas Raabe
- Inselspital, Universitätsspital Bern, Department of Neurosurgery, Neurocenter and Regenerative Neuroscience Cluster, Bern, Schweiz
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Kathleen Seidel
- Inselspital, Universitätsspital Bern, Department of Neurosurgery, Neurocenter and Regenerative Neuroscience Cluster, Bern, Schweiz
| Published: | June 4, 2021 |
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Outline
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Objective: During intraoperative neurophysiological monitoring (IOM), data are captured together with clinical events. Classically, IOM is documented paper based. This leads to redundant data, which increases the susceptibility to errors and makes it difficult to query the data. The goal of this project was to increase data management by digitizing the whole documentation workflow.
Methods: Using systems analysis methods, covering data flow modeling, process and variant analysis, we developed a concept for digitized IOM data management. The concept was realized as a web application, called IOM-Manager, which was implemented with the MEVN technology stack.
As data input option for the IOM documentation, we used a web form with dropdown menus for selecting event descriptions from a restricted number of possibilities. Thus, the event catalog was developed in an iterative way, by manually reviewing the latest 100 paper protocols searching for recurring entries. Then standard expressions were defined, which were assessed to refine the catalog.
Results: A software application to record IOM data (IOM-Manager) has been developed as a prototype to support recording of events on a timeline and to store measurements in a common database. A protocol entry catalog was developed, which divides predefined clinical events into 25 subcategories for neurophysiological measurements, surgical steps, anesthesia changes and an others. The dropdown lists allowed that an event is stored with a time stamp corresponding to the signal curves and thus enabled rapid data entry for each clinical event.
In a user survey the IOM-Manger achieved a score of 94.5 out of 100 points in the SUS score (System Usability Scale), which corresponds to a very good usability rating.
Figure 1 [Fig. 1]
Conclusion: The IOM-Manager may replace the previous paper based IOM protocols. Systematic documentation of IOM events is essential for efficient analyses of events-outcome relations. A future ontology will facilitate benchmarking among centers, multicenter studies and big data registries.
