Identifying nurses' concern concepts about patient deterioration using a standard nursing terminology

Min-Jeoung Kang; Patricia C Dykes; Tom Z Korach; Li Zhou; Kumiko O Schnock; Jennifer Thate; Kimberly Whalen; Haomiao Jia; Jessica Schwartz; Jose P Garcia; Christopher Knaplund; Kenrick D Cato; Sarah Collins Rossetti

doi:10.1016/j.ijmedinf.2019.104016

Identifying nurses' concern concepts about patient deterioration using a standard nursing terminology

Int J Med Inform. 2020 Jan:133:104016. doi: 10.1016/j.ijmedinf.2019.104016. Epub 2019 Oct 31.

Authors

Affiliations

¹ Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Boston, USA; Harvard Medical School, Boston, USA. Electronic address: mkang6@bwh.harvard.edu.
² Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Boston, USA; Harvard Medical School, Boston, USA.
³ Siena College, Albany, USA.
⁴ Massachusetts General Hospital, Boston, USA.
⁵ Columbia University, Department of Biostatistics, New York, USA; Columbia University, School of Nursing, New York, USA.
⁶ Columbia University, School of Nursing, New York, USA.
⁷ Columbia University, School of Nursing, New York, USA; Columbia University, Department of Biomedical Informatics, New York, USA.

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.

Keywords: Expression of concern; Information storage and retrieval; Standardized nursing terminology.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Humans
Intensive Care Units
Natural Language Processing
Nurses
Standardized Nursing Terminology*

Abstract

Publication types

MeSH terms

Grants and funding