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Moja L, Zanichelli V, Mertz D, Gandra S, Cappello B, Cooke GS, Chuki P, Harbarth S, Pulcini C, Mendelson M, Tacconelli E, Ombajo LA, Chitatanga R, Zeng M, Imi M, Elias C, Ashorn P, Marata A, Paulin S, Muller A, Aidara-Kane A, Wi TE, Were WM, Tayler E, Figueras A, Da Silva CP, Van Weezenbeek C, Magrini N, Sharland M, Huttner B, Loeb M. WHO's essential medicines and AWaRe: recommendations on first- and second-choice antibiotics for empiric treatment of clinical infections. Clin Microbiol Infect 2024; 30 Suppl 2:S1-S51. [PMID: 38342438 DOI: 10.1016/j.cmi.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/26/2024] [Accepted: 02/04/2024] [Indexed: 02/13/2024]
Abstract
The WHO Model List of Essential Medicines (EML) prioritizes medicines that have significant global public health value. The EML can also deliver important messages on appropriate medicine use. Since 2017, in response to the growing challenge of antimicrobial resistance, antibiotics on the EML have been reviewed and categorized into three groups: Access, Watch, and Reserve, leading to a new categorization called AWaRe. These categories were developed taking into account the impact of different antibiotics and classes on antimicrobial resistance and the implications for their appropriate use. The 2023 AWaRe classification provides empirical guidance on 41 essential antibiotics for over 30 clinical infections targeting both the primary health care and hospital facility setting. A further 257 antibiotics not included on the EML have been allocated an AWaRe group for stewardship and monitoring purposes. This article describes the development of AWaRe, focussing on the clinical evidence base that guided the selection of Access, Watch, or Reserve antibiotics as first and second choices for each infection. The overarching objective was to offer a tool for optimizing the quality of global antibiotic prescribing and reduce inappropriate use by encouraging the use of Access antibiotics (or no antibiotics) where appropriate. This clinical evidence evaluation and subsequent EML recommendations are the basis for the AWaRe antibiotic book and related smartphone applications. By providing guidance on antibiotic prioritization, AWaRe aims to facilitate the revision of national lists of essential medicines, update national prescribing guidelines, and supervise antibiotic use. Adherence to AWaRe would extend the effectiveness of current antibiotics while helping countries expand access to these life-saving medicines for the benefit of current and future patients, health professionals, and the environment.
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Affiliation(s)
- Lorenzo Moja
- Health Products Policy and Standards, World Health Organization, Geneva, Switzerland.
| | - Veronica Zanichelli
- Health Products Policy and Standards, World Health Organization, Geneva, Switzerland
| | - Dominik Mertz
- Department of Medicine, McMaster University, Hamilton, Canada; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada; World Health Organization Collaborating Centre for Infectious Diseases, Research Methods and Recommendations, McMaster University, Hamilton, Canada
| | - Sumanth Gandra
- Division of Infectious Diseases, Department of Internal Medicine, Washington University School of Medicine in St. Louis, Missouri, United States
| | - Bernadette Cappello
- Health Products Policy and Standards, World Health Organization, Geneva, Switzerland
| | - Graham S Cooke
- Department of Infectious Diseases, Imperial College London, London, UK
| | - Pem Chuki
- Antimicrobial Stewardship Unit, Jigme Dorji Wangchuck National Referral Hospital, Thimphu, Bhutan
| | - Stephan Harbarth
- Infection Control Programme, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland; World Health Organization Collaborating Centre on Infection Prevention and Control and Antimicrobial Resistance, Geneva, Switzerland
| | - Celine Pulcini
- APEMAC, and Centre régional en antibiothérapie du Grand Est AntibioEst, Université de Lorraine, CHRU-Nancy, Nancy, France
| | - Marc Mendelson
- Division of Infectious Diseases and HIV Medicine, Department of Medicine, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa
| | - Evelina Tacconelli
- Infectious Diseases Unit, Department of Diagnostics and Public Health, University of Verona, Verona, Italy
| | - Loice Achieng Ombajo
- Department of Clinical Medicine and Therapeutics, University of Nairobi, Nairobi, Kenya; Center for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya
| | - Ronald Chitatanga
- Antimicrobial Resistance National Coordinating Centre, Public Health Institute of Malawi, Blantyre, Malawi
| | - Mei Zeng
- Department of Infectious Diseases, Children's Hospital of Fudan University, Shanghai, China
| | | | - Christelle Elias
- Service Hygiène et Epidémiologie, Hospices Civils de Lyon, Lyon, France; Centre International de Recherche en Infectiologie, Institut National de la Santé et de la Recherche Médicale U1111, Centre National de la Recherche Scientifique Unité Mixte de Recherche 5308, École Nationale Supérieure de Lyon, Université Claude Bernard Lyon 1, Lyon, France
| | - Per Ashorn
- Center for Child, Adolescent and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University and Tampere University Hospital, Tampere, Finland
| | | | - Sarah Paulin
- Antimicrobial Resistance Division, World Health Organization, Geneva, Switzerland
| | - Arno Muller
- Antimicrobial Resistance Division, World Health Organization, Geneva, Switzerland
| | | | - Teodora Elvira Wi
- Department of Global HIV, Hepatitis and STIs Programme, World Health Organization, Geneva, Switzerland
| | - Wilson Milton Were
- Department of Maternal, Newborn, Child and Adolescent Health and Ageing, World Health Organization, Geneva, Switzerland
| | - Elizabeth Tayler
- WHO Regional Office for the Eastern Mediterranean (EMRO), World Health Organisation, Cairo, Egypt
| | | | - Carmem Pessoa Da Silva
- Antimicrobial Resistance Division, World Health Organization, Geneva, Switzerland; Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Nicola Magrini
- NHS Clinical Governance, Romagna Health Authority, Ravenna, Italy; World Health Organization Collaborating Centre for Evidence Synthesis and Guideline Development, Bologna, Italy
| | - Mike Sharland
- Centre for Neonatal and Paediatric Infections, Institute for Infection and Immunity, St George's University of London, London, UK
| | - Benedikt Huttner
- Health Products Policy and Standards, World Health Organization, Geneva, Switzerland
| | - Mark Loeb
- Department of Medicine, McMaster University, Hamilton, Canada; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada; World Health Organization Collaborating Centre for Infectious Diseases, Research Methods and Recommendations, McMaster University, Hamilton, Canada
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Application of DMAIC Cycle and Modeling as Tools for Health Technology Assessment in a University Hospital. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:8826048. [PMID: 34457223 PMCID: PMC8387173 DOI: 10.1155/2021/8826048] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 08/10/2021] [Indexed: 11/23/2022]
Abstract
Background The Health Technology Assessment (HTA) is used to evaluate health services, manage healthcare processes more efficiently, and compare medical technologies. The aim of this paper is to carry out an HTA study that compares two pharmacological therapies and provides the clinicians with two models to predict the length of hospital stay (LOS) of patients undergoing oral cavity cancer surgery on the bone tissue. Methods The six Sigma method was used as a tool of HTA; it is a technique of quality management and process improvement that combines the use of statistics with a five-step procedure: “Define, Measure, Analyze, Improve, Control” referred to in the acronym DMAIC. Subsequently, multiple linear regression has been used to create two models. Two groups of patients were analyzed: 45 were treated with ceftriaxone while 48 were treated with the combination of cefazolin and clindamycin. Results A reduction of the overall mean LOS of patients undergoing oral cavity cancer surgery on bone was observed of 40.9% in the group treated with ceftriaxone. Its reduction was observed in all the variables of the ceftriaxone group. The best results are obtained in younger patients (−54.1%) and in patients with low oral hygiene (−52.4%) treated. The regression results showed that the best LOS predictors for cefazolin/clindamycin are ASA score and flap while for ceftriaxone, in addition to these two, oral hygiene and lymphadenectomy are the best predictors. In addition, the adjusted R squared showed that the variables considered explain most of the variance of LOS. Conclusion SS methodology, used as an HTA tool, allowed us to understand the performance of the antibiotics and provided variables that mostly influence postoperative LOS. The obtained models can improve the outcome of patients, reducing the postoperative LOS and the relative costs, consequently increasing patient safety, and improving the quality of care provided.
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