Developing anautomatic scale to delirium detection based on the electronic medical record system
10.16571/j.cnki.1008-8199.2020.02.015
- VernacularTitle: 基于电子病历的人工智能谵妄识别量表初步构建
- Author:
Yan-li ZHAO
1
;
Ling CHEN
1
;
Dong-mei XIE
1
;
Nan LI
;
Lang-li GAO
1
;
Ji-rong YUE
1
Author Information
1. National Clinical Research Center for Geriatrics, Center of Gerontology and Geriatrics, 2
- Publication Type:Journal Article
- Keywords:
delirium;
electronic medical records;
automation;
keywords;
scale
- From:
Journal of Medical Postgraduates
2020;33(2):184-187
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveAt present, there are many bedside tools for delirium, but these manual tools are time-consuming and poor feasible. The aim of this study was to establish a delirium screening scale, automatically extracting keywords from electronic medical records (EMR).MethodsWe selected electronic medical records of 779 elderly hospitalized patients in West China Hospital of Sichuan University from 2015 to 2017. Then, R software was used to automatically extract keywords to form a database undercritical ration, correlation coefficient and different analysis methods. Finally, the Delphi method and Analytic Hierarchy Process Weight were carried out to the construct weight coefficient, so as to form the formal scale.ResultsIn the study, we developed a formal scale consisting of 59 items and 11 dimensions. The score of the scale ranged from 0 to 53.4, with a mean value of 6.64, skewness of 2.6 and kurtosis of 8.2.ConclusionThe delirium screening scale based on the EMR can improve the recognition rate of delirium through intelligent and automatic warning, so as to early diagnosis and timely intervention of delirium.
