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。

IF 3 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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引用次数: 0

摘要

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%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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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来源期刊

Infection Control and Hospital Epidemiology 医学-传染病学

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.