Identifying nurses' concern concepts about patient deterioration using a standard nursing terminology. (January 2020)

• Record Type: Journal Article
• Authors: Kang, Min-Jeoung; Dykes, Patricia C.; Korach, Tom Z.; Zhou, Li; Schnock, Kumiko O.; Thate, Jennifer; Whalen, Kimberly; Jia, Haomiao; Schwartz, Jessica; Garcia, Jose P.; Knaplund, Christopher; Cato, Kenrick D.; Rossetti, Sarah Collins
• Is Part Of: International journal of medical informatics. Volume 133(2020)
• Publication Date: 2020-01
• Subjects: Standardized nursing terminology -- Expression of concern -- Information storage and retrieval; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2019.104016
• Languages: English
• ISSNs: 1386-5056

Abstract

Highlights: Nursing concern can be identified by using a standard nursing terminology. Nurses concern is dependent upon unit types and settings. Engagement with subject-matter experts proved useful to identify nursing concern concepts. The fundamental lexicon offers granular terms that can be identified and processed in an automated fashion. Abstract: Objectives: Nurse concerns documented in nursing notes are important predictors of patient risk of deterioration. Using a standard nursing terminology and inputs from subject-matter experts (SMEs), we aimed to identify and define nurse concern concepts and terms about patient deterioration, which can be used to support subsequent automated tasks, such as natural language processing and risk predication. Methods: Group consensus meetings with nurse SMEs were held to identify nursing concerns by grading Clinical Care Classification (CCC) system concepts based on clinical knowledge. Next, a fundamental lexicon was built placing selected CCC concepts into a framework of entities and seed terms to extend CCC granularity. Results: A total of 29 CCC concepts were selected as reflecting nurse concerns. From these, 111 entities and 586 seed terms were generated into a fundamental lexicon. Nursing concern concepts differed across settings (intensive care units versus non-intensive care units) and unit types (medicine versus surgery units). Conclusions: The CCC concepts were useful for representing nursing concern as they encompass a nursing-centric conceptual framework and are practical in lexicon construction. It enabled the codification of nursing concerns for deteriorating patients at a standardized conceptual level. The boundary of selected CCC concepts and lexicons were determined by the SMEs. The fundamental lexicon offers more granular terms that can be identified and processed in an automated fashion.