Natural Language Processing of Nursing Notes An Integrative Review

被引:15
作者
Mitha, Shazia [1 ]
Schwartz, Jessica [1 ]
Hobensack, Mollie [1 ]
Cato, Kenrick [1 ]
Woo, Kyungmi [1 ]
Smaldone, Arlene [1 ]
Topaz, Maxim [1 ,2 ]
机构
[1] Columbia Univ, Sch Nursing, New York, NY USA
[2] Columbia Univ, Sch Nursing, 560 W 168th St, New York, NY 10032 USA
关键词
Natural language processing; Nursing documentation; Nursing notes; Text mining; CLINICAL NOTES; CARE; PREDICTION; RISK; INFORMATION; PATIENT; HOSPITALIZATION; VISITS; TRIAGE; NURSES;
D O I
10.1097/CIN.0000000000000967
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Natural language processing includes a variety of techniques that help to extract meaning from narrative data. In healthcare, medical natural language processing has been a growing field of study; however, little is known about its use in nursing. We searched PubMed, EMBASE, and CINAHL and found 689 studies, narrowed to 43 eligible studies using natural language processing in nursing notes. Data related to the study purpose, patient population, methodology, performance evaluation metrics, and quality indicators were extracted for each study. The majority (86%) of the studies were conducted from 2015 to 2021. Most of the studies (58%) used inpatient data. One of four studies used data from open-source databases. The most common standard terminologies used were the Unified Medical Language System and Systematized Nomenclature of Medicine, whereas nursing-specific standard terminologies were used only in eight studies. Full system performance metrics (eg, F score) were reported for 61% of applicable studies. The overall number of nursing natural language processing publications remains relatively small compared with the other medical literature. Future studies should evaluate and report appropriate performance metrics and use existing standard nursing terminologies to enable future scalability of the methods and findings.
引用
收藏
页码:377 / 384
页数:8
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