A Protocol Entry Catalog for Intraoperative Neuromonitoring - Steps Towards an Ontology.

Zbinden, Chantal; Strickler, Moritz; Sariyar, Murat; Bürkle, Thomas; Seidel, Kathleen (2020). A Protocol Entry Catalog for Intraoperative Neuromonitoring - Steps Towards an Ontology. Studies in Health Technology and Informatics, 272, pp. 318-321. IOS Press 10.3233/SHTI200559

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In neurosurgery, intraoperative neurophysiological monitoring (IOM) with continuous measurements of neural electrical activity may reduce the risk of postoperative deficits. During an IOM, surgical information as well as neurophysiological, surgical and anesthesia events have to be recorded. So far, there is no common standard for this task available. In this paper, such a standardization with the aim of facilitating the data input and making the protocols data available for different sorts of analyses is described. We developed a protocol entry catalog with 200 standard expressions, which were divided into four categories: IOM, surgical procedure, anesthesia and others. An empirical assessment of the catalog by the IOM team showed the need for subcategories. In the final version of the catalog, the standard terms were grouped into 25 subcategories. The catalog is a first step to support systematic research into the occurrence of clinical events during the IOM and their association with postoperative neurological deficits that could enable improved surgical procedures in the future.

Item Type:

Journal Article (Original Article)

Division/Institute:

School of Engineering and Computer Science > Institut für Medizininformatik I4MI

Name:

Zbinden, Chantal;
Strickler, Moritz;
Sariyar, Murat;
Bürkle, Thomas and
Seidel, Kathleen

ISSN:

1879-8365

Publisher:

IOS Press

Language:

English

Submitter:

Murat Sariyar

Date Deposited:

09 Nov 2020 10:39

Last Modified:

15 Jan 2024 15:22

Publisher DOI:

10.3233/SHTI200559

PubMed ID:

32604666

Uncontrolled Keywords:

Intraoperative Neuromonitoring Intraoperative Neurophysiology Ontology Protocol Entries Standardized Data

ARBOR DOI:

10.24451/arbor.13256

URI:

https://arbor.bfh.ch/id/eprint/13256

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