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Antimicrobial Stewardship & Healthcare Epidemiology is a peer-reviewed journal published by Cambridge University Press, covering Antibiotic Use and Resistance, Nosocomial Infections in ICU, Bacterial Identification and Susceptibility Testing. Over its lifetime it has published 2,830 papers, which have received 4,615 citations.
| Publisher | Cambridge University Press |
|---|---|
| Reference style | Numbered Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, A representative article title, Antimicrobial Stewardship & Healthcare Epidemiology 12 (2023) 45–58.
Formats any DOI in the closest standard style — Antimicrobial Stewardship & Healthcare Epidemiology has no published style definition, so this is an approximation. No sign-up. |
| Publishes research in | Antibiotic Use and Resistance Nosocomial Infections in ICU Bacterial Identification and Susceptibility Testing Infection Control in Healthcare Urinary Tract Infections Management |
| ISSN | 2732-494X |
| Citation impact (2-yr) | 0.58 |
| h-index | 24 |
| i10-index | 111 |
| Article processing charge | $2,000 |
| Open access | Yes — indexed in DOAJ |
| Top institutions publishing here | University of Utah |
| Journal website | www.cambridge.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
The AWaRe classification categorizes antibiotics and is a tool for antimicrobial stewardship. To combat antimicrobial resistance, prescribers must adhere to the AWaRe framework, which promotes the rational use of antibiotics. Therefore, increasing political will, dedicating resources, building capacity, and improving awareness and sensitization campaigns may promote adherence to the framework.
Artificial intelligence (AI) refers to the performance of tasks by machines ordinarily associated with human intelligence. Machine learning (ML) is a subtype of AI; it refers to the ability of computers to draw conclusions (ie, learn) from data without being directly programmed. ML builds from traditional statistical methods and has drawn significant interest in healthcare…
Clinical pharmacist-driven antimicrobial stewardship programs (ASPs) have been successfully implemented. Although relevant guidance and several studies suggest that clinical pharmacists be integrated into the current ASP team model, barriers still exist in Asia, primarily due to lack of dedicated personnel and lack of career advancement. We review the effectiveness and the ideal role of clinical…
Implementation of antimicrobial stewardship programs (ASPs) in well-resourced countries has been associated with reductions in antibiotic-resistant infections and improved patient outcomes. Several guidance documents providing recommendations on how to structure antimicrobial stewardship activities at the national and hospital level in resource-limited settings have been published. However, few hospitals in Latin America report having a structure…
Infection surveillance is one of the cornerstones of infection prevention and control. Measurement of process metrics and clinical outcomes, such as detection of healthcare-associated infections (HAIs), can be used to support continuous quality improvement. HAI metrics are reported as part of the CMS Hospital-Acquired Conditions Program, and they influence facility reputation and financial outcomes.
