Zhao Yanli, Chen Ling, Yue Jirong
National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, P.R.China;Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2020 Feb 25;37(1):185-188. doi: 10.7507/1001-5515.201909048.
Delirium is a common complication in elderly inpatients which could result in cognitive impairment, and increase the risk of disability, fall and mortality. Moreover, it could cause heavy social burden. Even with multiple bedside screening scales to detect delirium, the rate of missed diagnosis is still high. Maybe it is associated with the acute fluctuation and nocturnal onset of delirium. With the development of the intelligence and automation of the electronic medical record (EMR), previous studies have explored the use of EMR to identify delirium patients, and this method provides help for delirium diagnosis and prevention. In this paper, we reviewed and summarized the current situation of research on delirium recognition by EMR, and put forward the development prospect in this method in order to provide basis and lay a foundation for intelligent diagnosis of delirium.
谵妄是老年住院患者常见的并发症，可导致认知障碍，增加残疾、跌倒和死亡风险。此外，它还会造成沉重的社会负担。即便有多种床边筛查量表用于检测谵妄，但漏诊率仍然很高。这可能与谵妄的急性波动和夜间发作有关。随着电子病历（EMR）智能化和自动化的发展，以往研究探索了利用EMR识别谵妄患者，该方法为谵妄的诊断和预防提供了帮助。本文回顾并总结了目前利用EMR识别谵妄的研究现状，并提出该方法的发展前景，以期为谵妄的智能诊断提供依据和奠定基础。
