Abstract Details

Title Programming of Electronic Medical Record for ACNS Standardized Critical Care EEG Terminology

Topic Epilepsy/Clinical Neurophysiology (EEG)

Presentation(s) P1 - Poster Session 1 (9:00 AM-5:00 PM)

Poster/Presentation
Number 162

Objective We developed a programming system to implement American Clinical Neurophysiology Society (ACNS) Standardized Critical Care EEG (CCEEG) Terminology in an Electronic Medical Record (EMR) Epic.

Background In 2012 ACNS has published CCEEG Terminology for use in critically ill patients undergoing continuous EEG monitoring with the goal to provide guidance and improve interrater reliability in description of frequently encountered EEG patterns unique to critically ill patients. The updated in 2021 document included new concepts and terms. This project was focused on the practical implementation of the updated CCEEG Terminology within University of Rochester’s EMR to maintain compliance with changes in nomenclature

Design/Methods Previously published in 2012 ACNS CCEEG Terminology was reviewed by the author (OS) and outlined for individual categories and their subcategories. Subsequent appropriate either single or multiple selection options were provided in accordance with the ACNS Terminology outline. Each coded selection was assigned a unique numerical value that could later be found via EMR search. Following an update in 2021, the platform from 2012 version was expanded to include both major and minor changes. In addition, by instituting branching logic we were able to program multiple coexisting rhythmic and periodic patterns in a single set. Lastly, we retained unique numerical identifier from the 2012 to 2021 version.

Results By incorporating existing 2012 version as a basis for 2021 update we were able to retain the infrastructure of the coded material and ease of transition for clinical providers. Retention of the numerical identifiers allowed smooth transition without a compromise or loss of previously encoded material.

Conclusions Programming CCEEG ACNS terminology in EMR improved ease of documentation, expanded EMR utilization and simplified future data retrieval for quality improvement and research purposes as well as training of qualified EEG interpreters. Similar platform can be adopted in any institution or EMR system.

Authors/Disclosures
Olga Selioutski, DO PRESENTER	The institution of Dr. Selioutski has received research support from NIH.
Anne C. Van Cott, MD, FAAN (VA Pittsburgh Healthcare System/University of Pittsburgh)	Dr. Van Cott has nothing to disclose.

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