Data Analytics for Diagnosis and Prediction of Central Line-Associated Bloodstream Infections in Critical Care Units
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Author Information
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Mary A. Hooshmand, PhD, MS, BS, RN; Christine Toledo, BSN -- School of Nursing and Health Studies, University of Miami, Coral Gables, Florida, USA; Ramin Moghaddass, PhD, Department of Industrial Engineering, University of Miami, College of Engineering, Coral Gables, Florida, USA; Erotokritos Skordilis, BS, College of Engineering, Department of Industrial Engineering, University of Miami, Coral Gables, Florida, USA
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- Non-member
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Abstract
Central line-associated bloodstream infections (CLABSI) are among leading causes of in-hospital deaths in the US and are a significant factor for increased morbidity, mortality and health care costs. This study examined significant attributes for CLABSI positive cases within intensive care units to develop a CLABSI hazard rate and risk score.
Description
45th Biennial Convention 2019 Theme: Connect. Collaborate. Catalyze.
Repository Posting Date
2019-10-04T20:25:59Z
Type Information
| Type | Presentation |
| Acquisition | Proxy-submission |
| Review Type | Abstract Review Only: Reviewed by Event Host |
| Format | Text-based Document |
Category Information
| Evidence Level | N/A |
| Research Approach | N/A |
| Keywords | Central Line Associated Bloodstream Infections (CLABSI); Data Analytics; Early Warning Systems |
Conference Information
| Name | 45th Biennial Convention |
| Host | Sigma Theta Tau International |
| Location | Washington, DC, USA |
| Date | 2019 |
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