Predicting and reducing “hospital‐acquired infections” using a knowledge‐based e‐surveillance system-Reference-Cited by-同舟云学术

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Predicting and reducing “hospital‐acquired infections” using a knowledge‐based e‐surveillance system

Published:2019-04-07 Issue:1 Volume:37 Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Noaman Amin Y.¹,Ragab Abdul Hamid M.²^ORCID,Al‐Abdullah Nabeela³,Jamjoom Arwa²,Nadeem Farrukh²,Ali Anser G.²

Affiliation:

1. Department of Computer Science, Faculty of Computing and Information TechnologyKing Abdulaziz University Jeddah Saudi Arabia

2. Department of Information Systems, Faculty of Computing and Information TechnologyKing Abdulaziz University Jeddah Saudi Arabia

3. Clinical Epidemiology and Infection Control, Faculty of NursingKing Abdulaziz University Jeddah Saudi Arabia

Funder

National Plan for Science, Technology and Innovation

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.12402

Reference39 articles.

1. A multitiered strategy of simulation training, kit consolidation, and electronic documentation is associated with a reduction in central line–associated bloodstream infections

2. Decreasing Central Line-associated Bloodstream Infections Through Quality Improvement Initiative

3. Retrospective Cohort Analysis of Central Line Associated Blood Stream Infection following Introduction of a Central Line Bundle in a Neonatal Intensive Care Unit

4. Use of Simulation-Based Education to Reduce Catheter-Related Bloodstream Infections

5. Comparison of Automated Strategies for Surveillance of Nosocomial Bacteremia

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1. Development of a knowledge-based healthcare-associated infections surveillance system in China;BMC Medical Informatics and Decision Making;2023-10-10

2. Factors Influencing Clinicians’ Use of Hospital Information Systems for Infection Prevention and Control: Cross-Sectional Study Based on the Extended DeLone and McLean Model;Journal of Medical Internet Research;2023-06-22

3. Factors Influencing Clinicians’ Use of Hospital Information Systems for Infection Prevention and Control: Cross-Sectional Study Based on the Extended DeLone and McLean Model (Preprint);2022-12-08

4. Predicting healthcare-associated infections, length of stay, and mortality with the nursing intensity of care index;Infection Control & Hospital Epidemiology;2021-04-16

5. How does innovative technology impact nursing in infectious diseases and infection control? A scoping review;Nursing Open;2021-03-25

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