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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

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Published on: September 20, 2018

Natural Language Processing of Nursing Notes: An Integrative Review.

Shazia Mitha¹, Jessica Schwartz, Mollie Hobensack

¹Author Affiliations : Columbia University School of Nursing, New York.

Computers, Informatics, Nursing : CIN

|February 2, 2023

Summary

This study reviewed natural language processing (NLP) in nursing notes, finding limited use of nursing-specific terminologies and performance metrics. Future research should focus on standardized terminology and robust evaluation for advancing NLP in nursing.

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Area of Science:

Nursing Informatics
Health Informatics
Computational Linguistics

Background:

Medical Natural Language Processing (NLP) is advancing, but its application in nursing is under-explored.
A systematic review identified 43 studies on NLP in nursing notes, primarily from 2015-2021, with most using inpatient data.

Approach:

Searched PubMed, EMBASE, and CINAHL for studies on NLP in nursing notes.
Extracted data on study purpose, patient population, methodology, performance metrics, and quality indicators.
Analyzed the use of standard terminologies and reporting of performance evaluation.

Key Points:

Most studies (86%) were published between 2015-2021, with 58% utilizing inpatient data.
Commonly used terminologies included Unified Medical Language System and Systematized Nomenclature of Medicine; nursing-specific terminologies were rare.
Performance metrics like F-score were reported in only 61% of applicable studies.

Conclusions:

The volume of nursing NLP research is small compared to broader medical literature.
Future research should prioritize using standard nursing terminologies and reporting comprehensive performance metrics for scalability and comparability.