Validation of electronic health record data to identify hospital-associated Clostridioides difficile infections for retrospective research.

IF 2.9 4区 医学 Q2 INFECTIOUS DISEASES Infection Control and Hospital Epidemiology Pub Date : 2024-10-16 DOI:10.1017/ice.2024.140
Michael J Ray, Kathleen L Lacanilao, Maela Robyne Lazaro, Luke C Strnad, Jon P Furuno, Kelly Royster, Jessina C McGregor
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Abstract

Clostridioides difficile infection (CDI) research relies upon accurate identification of cases when using electronic health record (EHR) data. We developed and validated a multi-component algorithm to identify hospital-associated CDI using EHR data and determined that the tandem of CDI-specific treatment and laboratory testing has 97% accuracy in identifying HA-CDI cases.

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验证电子健康记录数据,识别医院相关艰难梭菌感染,进行回顾性研究。
艰难梭菌感染(CDI)研究有赖于使用电子健康记录(EHR)数据准确识别病例。我们开发并验证了使用 EHR 数据识别医院相关 CDI 的多组件算法,并确定 CDI 特异性治疗和实验室检测串联在一起在识别 HA-CDI 病例方面的准确率为 97%。
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来源期刊
CiteScore
6.40
自引率
6.70%
发文量
289
审稿时长
3-8 weeks
期刊介绍: Infection Control and Hospital Epidemiology provides original, peer-reviewed scientific articles for anyone involved with an infection control or epidemiology program in a hospital or healthcare facility. Written by infection control practitioners and epidemiologists and guided by an editorial board composed of the nation''s leaders in the field, ICHE provides a critical forum for this vital information.
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