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A Web-Based, Hospital-Wide Health Care-Associated Bloodstream Infection Surveillance and Classification System: Development and Evaluation

BACKGROUND: Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent. OBJECTIVE: To develop an automatic surveillance and classification system for health care-associated blood...

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Detalles Bibliográficos
Autores principales: Tseng, Yi-Ju, Wu, Jung-Hsuan, Lin, Hui-Chi, Chen, Ming-Yuan, Ping, Xiao-Ou, Sun, Chun-Chuan, Shang, Rung-Ji, Sheng, Wang-Huei, Chen, Yee-Chun, Lai, Feipei, Chang, Shan-Chwen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Gunther Eysenbach 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4705006/
https://www.ncbi.nlm.nih.gov/pubmed/26392229
http://dx.doi.org/10.2196/medinform.4171
Descripción
Sumario:BACKGROUND: Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent. OBJECTIVE: To develop an automatic surveillance and classification system for health care-associated bloodstream infection (HABSI), and to evaluate its performance by comparing it with a conventional infection control personnel (ICP)-based surveillance system. METHODS: We developed a Web-based system that was integrated into the medical information system of a 2200-bed teaching hospital in Taiwan. The system automatically detects and classifies HABSIs. RESULTS: In this study, the number of computer-detected HABSIs correlated closely with the number of HABSIs detected by ICP by department (n=20; r=.999 P<.001) and by time (n=14; r=.941; P<.001). Compared with reference standards, this system performed excellently with regard to sensitivity (98.16%), specificity (99.96%), positive predictive value (95.81%), and negative predictive value (99.98%). The system enabled decreasing the delay in confirmation of HABSI cases, on average, by 29 days. CONCLUSIONS: This system provides reliable and objective HABSI data for quality indicators, improving the delay caused by a conventional surveillance system.