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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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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. |
format | Online Article Text |
id | pubmed-9531378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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