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A novel semiautomatic Chinese keywords instrument screening delirium based on electronic medical records

BACKGROUND: Delirium is frequently unrecognized due to the absence of regular screening. In addition to validated bedside tools, the computer-assisted instrument based on clinical notes from electronic medical records may be useful. AIMS: To assess the psychometric properties of a Chinese-chart-base...

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Autores principales: Chen, Ling, Li, Nan, Zheng, Yuxia, Gao, Langli, Ge, Ning, Xie, Dongmei, Yue, Jirong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531378/
https://www.ncbi.nlm.nih.gov/pubmed/36192690
http://dx.doi.org/10.1186/s12877-022-03474-w
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author Chen, Ling
Li, Nan
Zheng, Yuxia
Gao, Langli
Ge, Ning
Xie, Dongmei
Yue, Jirong
author_facet Chen, Ling
Li, Nan
Zheng, Yuxia
Gao, Langli
Ge, Ning
Xie, Dongmei
Yue, Jirong
author_sort Chen, Ling
collection PubMed
description BACKGROUND: Delirium is frequently unrecognized due to the absence of regular screening. In addition to validated bedside tools, the computer-assisted instrument based on clinical notes from electronic medical records may be useful. AIMS: To assess the psychometric properties of a Chinese-chart-based keyword instrument for semiautomatically screening delirium using Natural language processing (NLP) based on clinical notes from electronic medical records. METHODS: The patients were admitted to West China Hospital from January 2015 to December 2017. Grouping patients based on the medical notes, those with accessible physician documents but no nurse documents were classified as the physician & no-nurse (PNN) group, while those with accessible physician and nurse documents were classified as the physician & nurse (PN) group. The psychometric properties, test–retest reliability, internal consistency reliability (Cronbach's α), and criterion validity were calculated. Using receiver operating characteristic (ROC) analysis, the criterion validity of delirium was evaluated in comparison to the results of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. RESULTS: A total of 779 patients were enrolled in the study. Their ages ranged from 65 to 103 years (82.5 ± 6.5), with men accounting for 71.9% of the total. A total of 312 patients had access to only physician documents in the physician & no-nurse (PNN) group, whereas 467 patients had access to both physician and nurse documents in the physician & nurse (PN) group. All 779 patients had a Cronbach's alpha of 0.728 in terms of reliability, with 100% test–retest reliability. The area under the ROC curve (AUC) values of the delirium screening instrument for criterion validity were 0.76 (all patients, n = 779), 0.72 (PNN, n = 312), and 0.79 (PN, n = 467), respectively. CONCLUSION: A delirium screening instrument composed of Chinese keywords that can be easily and quickly obtained from electronic medical records was developed, which improved delirium detection in older people. TRIAL REGISTRATION: Not applicable. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-022-03474-w.
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spelling pubmed-95313782022-10-05 A novel semiautomatic Chinese keywords instrument screening delirium based on electronic medical records Chen, Ling Li, Nan Zheng, Yuxia Gao, Langli Ge, Ning Xie, Dongmei Yue, Jirong BMC Geriatr Research BACKGROUND: Delirium is frequently unrecognized due to the absence of regular screening. In addition to validated bedside tools, the computer-assisted instrument based on clinical notes from electronic medical records may be useful. AIMS: To assess the psychometric properties of a Chinese-chart-based keyword instrument for semiautomatically screening delirium using Natural language processing (NLP) based on clinical notes from electronic medical records. METHODS: The patients were admitted to West China Hospital from January 2015 to December 2017. Grouping patients based on the medical notes, those with accessible physician documents but no nurse documents were classified as the physician & no-nurse (PNN) group, while those with accessible physician and nurse documents were classified as the physician & nurse (PN) group. The psychometric properties, test–retest reliability, internal consistency reliability (Cronbach's α), and criterion validity were calculated. Using receiver operating characteristic (ROC) analysis, the criterion validity of delirium was evaluated in comparison to the results of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. RESULTS: A total of 779 patients were enrolled in the study. Their ages ranged from 65 to 103 years (82.5 ± 6.5), with men accounting for 71.9% of the total. A total of 312 patients had access to only physician documents in the physician & no-nurse (PNN) group, whereas 467 patients had access to both physician and nurse documents in the physician & nurse (PN) group. All 779 patients had a Cronbach's alpha of 0.728 in terms of reliability, with 100% test–retest reliability. The area under the ROC curve (AUC) values of the delirium screening instrument for criterion validity were 0.76 (all patients, n = 779), 0.72 (PNN, n = 312), and 0.79 (PN, n = 467), respectively. CONCLUSION: A delirium screening instrument composed of Chinese keywords that can be easily and quickly obtained from electronic medical records was developed, which improved delirium detection in older people. TRIAL REGISTRATION: Not applicable. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-022-03474-w. BioMed Central 2022-10-04 /pmc/articles/PMC9531378/ /pubmed/36192690 http://dx.doi.org/10.1186/s12877-022-03474-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Ling
Li, Nan
Zheng, Yuxia
Gao, Langli
Ge, Ning
Xie, Dongmei
Yue, Jirong
A novel semiautomatic Chinese keywords instrument screening delirium based on electronic medical records
title A novel semiautomatic Chinese keywords instrument screening delirium based on electronic medical records
title_full A novel semiautomatic Chinese keywords instrument screening delirium based on electronic medical records
title_fullStr A novel semiautomatic Chinese keywords instrument screening delirium based on electronic medical records
title_full_unstemmed A novel semiautomatic Chinese keywords instrument screening delirium based on electronic medical records
title_short A novel semiautomatic Chinese keywords instrument screening delirium based on electronic medical records
title_sort novel semiautomatic chinese keywords instrument screening delirium based on electronic medical records
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531378/
https://www.ncbi.nlm.nih.gov/pubmed/36192690
http://dx.doi.org/10.1186/s12877-022-03474-w
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