{"title":"Understanding the complex knowledge economy toward antimicrobial stewardship in West Bengal, India","authors":"Ayako Ebata , Meenakshi Gautham , Anne-Sophie Jung , Mathew Hennessey , Sanghita Bhattacharyya , Gerald Bloom","doi":"10.1016/j.ssmhs.2025.100063","DOIUrl":null,"url":null,"abstract":"<div><div>Knowledge dissemination and awareness raising is a common strategy for fostering antimicrobial stewardship and tackling antimicrobial resistance (AMR). However, empirical evidence suggests that the dissemination of technical/biomedical information about AMR, alone, is insufficient to improve antibiotic use in resource-poor settings. This is because antibiotic users’ decisions are based not only on biomedical knowledge but also on social and clinical information that is specific to local healthcare realities, and healthcare providers’ clinical knowledge and judgement. In this article, we propose a framework that identifies knowledge critical to deciding a course of antibiotic treatment for possible infection in resource-poor settings, and how to improve the knowledge flow to improve antibiotic use. Specifically, we focus on understanding three domains of knowledge that guide antibiotic users’ decisions: 1) scientific evidence, and evidence-based treatment guidelines; 2) local knowledge of infection patterns and risks, and the susceptibility of organisms causing infection to different antibiotics; and 3) personal and social characteristics of the patient. Drawing from the theory of information asymmetry and empirical data from West Bengal, India, we show that all three domains of knowledge demonstrated degrees of asymmetry, and community-level practitioners’ knowledge was not effectively taken into account in clinical guidance. We conclude that interventions targeting AMR need to reflect all three knowledge domains to be effective in clinical settings.</div></div>","PeriodicalId":101183,"journal":{"name":"SSM - Health Systems","volume":"4 ","pages":"Article 100063"},"PeriodicalIF":0.0000,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SSM - Health Systems","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949856225000157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
Knowledge dissemination and awareness raising is a common strategy for fostering antimicrobial stewardship and tackling antimicrobial resistance (AMR). However, empirical evidence suggests that the dissemination of technical/biomedical information about AMR, alone, is insufficient to improve antibiotic use in resource-poor settings. This is because antibiotic users’ decisions are based not only on biomedical knowledge but also on social and clinical information that is specific to local healthcare realities, and healthcare providers’ clinical knowledge and judgement. In this article, we propose a framework that identifies knowledge critical to deciding a course of antibiotic treatment for possible infection in resource-poor settings, and how to improve the knowledge flow to improve antibiotic use. Specifically, we focus on understanding three domains of knowledge that guide antibiotic users’ decisions: 1) scientific evidence, and evidence-based treatment guidelines; 2) local knowledge of infection patterns and risks, and the susceptibility of organisms causing infection to different antibiotics; and 3) personal and social characteristics of the patient. Drawing from the theory of information asymmetry and empirical data from West Bengal, India, we show that all three domains of knowledge demonstrated degrees of asymmetry, and community-level practitioners’ knowledge was not effectively taken into account in clinical guidance. We conclude that interventions targeting AMR need to reflect all three knowledge domains to be effective in clinical settings.