Paper Info
Title
Faster and Active Surveillance of Hospital-Acquired Infections: A Model for Settings with High Sensitivity Predictors
Abstract
Background: At present, passive alarm system from culture reports and announced from groups outbreak events make cases investigate delayed. Is there any predict factor can be used to suggest active high capture sensitivity surveillance and alarm outbreak early? Objectives: Is there any predict factor can be used to get active high capture sensitivity surveillance of hospital-acquired infections (HAI) in acute hospitals. Can it give alarm of outbreak early? Can it decrease the number for direct patient examination or chart review. Methods : We performed three months retrospective study to identify predictors(urine routine, device as catheter or cystoscope, antibiotics, culture, etc.) about major HAI (urinary tract infections), as defined by the Centers for Disease Control and Prevention (CDC) criteria in a medical center (733 beds). We compared patients list of predictor(s) positive collected from electronic medical record by medical information department members with confirmed nosocomial UTI cases list given from infection control department. Results: 5533 admission patients were screened. The overall prevalence of HAI was 2.5% (141/5533); 1.4% (77/5533) of patients was nosocomial UTI. At presence of urine routine examination and devices guarantees 100% capture sensitivity in detecting nosocomial UTI but requires an assessment of 2763 patients (49.9%) of the population. At presence of antibiotics and devices guarantees 98.7% capture sensitivity and requires an assessment of 1921 patients (34.7%) of the population, whereas presence of antibiotics and urine routine examination has 98.7% capture sensitivity but requires an assessment of 3019 patients (54.7%) of the population. Conclusion: A capture system based on daily list of newly order about antibiotics, devices, urine routine examination, urine culture, blood culture, infection control department of hospital can decide which high predict value criteria suggesting checklist from medical information department for infection control department member to perform active patient examination and decrease the number of direct patient examination and chart review, but still keep high capture sensitivity
Year
DOI
Venue
2009
10.1109/BIBE.2009.39
BIBE
Keywords
Field
DocType
infection control,retrospective study,bioinformatics,real time systems,sensitivity,antibiotics,predictive models,control systems
Checklist,Catheter,Population,Hospital-acquired infection,Emergency medicine,Infection control,Computer science,Blood culture,Medical record,Retrospective cohort study,Bioinformatics
Conference
ISSN
Citations 
PageRank 
2471-7819
0
0.34
References 
Authors
1
5
Name
Order
Citations
PageRank
Yao-wen Chung100.68
Yu-Sheng Lo2933.49
Wen-sen Lee3902.56
Min-Huei Hsu4347.51
Chien-Tsai Liu520231.64