title: Automatic generation of nursing narratives from entity-attribute-value triplet for electronic nursing records system.
abstract: The aim of this study is to develop and evaluate a natural language generation system to populate nursing narratives using detailed clinical models. Semantic, contextual, and syntactical knowledges were extracted. A natural language generation system linking these knowledges was developed. The quality of generated nursing narratives was evaluated by the three nurse experts using a five-point rating scale. With 82 detailed clinical models, in total 66,888 nursing narratives in four different types of statement were generated. The mean scores for overall quality was 4.66, for content 4.60, for grammaticality 4.40, for writing style 4.13, and for correctness 4.60. The system developed in this study generated nursing narratives with different levels of granularity. The generated nursing narratives can improve semantic interoperability of nursing data documented in nursing records.
authors.affiliation: College of Nursing, Seoul National University, Seoul, Korea.
authors.forename: Yul Ha
authors.initials: YH
authors.lastname: Min
authors.affiliation: College of Nursing, Seoul National University, Seoul, Korea.
authors.forename: Hyeoun-Ae
authors.initials: HA
authors.lastname: Park
authors.affiliation: College of Nursing, Seoul National University, Seoul, Korea.
authors.forename: Joo Yun
authors.initials: JY
authors.lastname: Lee
authors.affiliation: College of Nursing, Seoul National University, Seoul, Korea.
authors.forename: Soo Jung
authors.initials: SJ
authors.lastname: Jo
authors.affiliation: College of Nursing, Seoul National University, Seoul, Korea.
authors.forename: Eunjoo
authors.initials: E
authors.lastname: Jeon
authors.affiliation: ezCatetech Co., Ltd., Seoul, Korea.
authors.forename: Namsoo
authors.initials: N
authors.lastname: Byeon
authors.affiliation: ezCatetech Co., Ltd., Seoul, Korea.
authors.forename: Seung Yong
authors.initials: SY
authors.lastname: Choi
authors.affiliation: Seoul National University Bundang Hospital, Seongnam, Korea.
authors.forename: Eunja
authors.initials: E
authors.lastname: Chung
mesh_terms: D057286:Electronic Health Records / Q000458:organization & administration*; D016247:Information Storage and Retrieval / Q000379:methods*; D008498:Medical Record Linkage / Q000379:methods*; D009323:Natural Language Processing; D009737:Nursing Records; D010363:Pattern Recognition, Automated / Q000379:methods*; D012660:Semantics; D018875:Vocabulary, Controlled