ArticleBMC geriatrics2022
A novel semiautomatic Chinese keywords instrument screening delirium based on electronic medical records.
Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.
- Natural language processing for geriatric syndromes: a systematic review of methods, applications, and challenges.BMC medical informatics and decision making · 2026Pooled it
- The use of natural language processing for the identification of ageing syndromes including sarcopenia, frailty and falls in electronic healthcare records: a systematic review.Age and ageing · 2024Pooled it
- Development and Usability Testing of a Mobile App-Based Clinical Decision Support System for Delirium: Randomized Crossover Trial.JMIR aging · 2024Trial
- Natural language processing techniques to detect delirium in hospitalized patients from clinical notes: a systematic review.NPJ digital medicine · 2025Article
- Improving Surgical Outcomes for Older Adults with Adoption of Technological Advances in Comprehensive Geriatric Assessment.Seminars in colon & rectal surgery · 2024Article
- Identification of risk factors for the onset of delirium associated with COVID-19 by mining nursing records.PloS one · 2024Article
- Artificial intelligence in cardiovascular diseases: diagnostic and therapeutic perspectives.European journal of medical research · 2023Review
- Use of Electronic Medical Records (EMR) in Gerontology: Benefits, Considerations and a Promising Future.Clinical interventions in aging · 2023Review
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDelirium 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.
aimsTo 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.
methodsThe 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.
resultsA 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.
conclusionA 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 registrationNot applicable.
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