Novel Visualization of Clostridium difficile Infections in Intensive Care Units.
Novel Visualization of Clostridium difficile Infections in Intensive Care Units.
复制标题
重症监护病房中艰难梭菌感染的新颖可视化。
DOI：
10.1055/s-0039-1693651
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Hebert,CourtneyL
中科院分区：
文献类型：
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作者：
Yu,SeanC;Lai,AlbertM;Smyer,Justin;Flaherty,Jennifer;Mangino,JulieE;McAlearney,AnnScheck;Yen,Po-Yin;Moffatt-Bruce,Susan;Hebert,CourtneyL
BackgroundAccurate and timely surveillance and diagnosis of health care facility onsetClostridium difficileinfection (HO-CDI) is vital to controlling infections within the hospital, but there are limited tools to assist with timely outbreak investigations.ObjectivesThe objective of this study was to integrate spatiotemporal factors with HO-CDI cases and to develop a map-based dashboard to support infection preventionists (IPs) in performing surveillance and outbreak investigations for HO-CDI.MethodsClinical laboratory results and Admit-Transfer-Discharge data for admitted patients over 2 years were extracted from the information warehouse of a large academic medical center (AMC) and processed according to the Center for Disease Control National Healthcare Safety Network definitions to classify CDI cases by onset date. Results were validated against the internal infection surveillance database maintained by IPs in Clinical Epidemiology of this AMC. Hospital floor plans were combined with HO-CDI case data, to create a dashboard of intensive care units. Usability testing was performed with a think-aloud session and a survey.ResultsThe simple classification algorithm identified all 265 HO-CDI cases from January 1, 2015 to November 30, 2015 with a positive predictive value (PPV) of 96.3%. When applied to data from 2014, the PPV was 94.6%. All users “strongly agreed” that the dashboard would be a positive addition to Clinical Epidemiology and would enable them to present hospital-acquired infection information to others more efficiently.ConclusionThe CDI dashboard demonstrates the feasibility of mapping clinical data to hospital patient care units for more efficient surveillance and potential outbreak investigations.
