Electronic information systems for One Health surveillance of antimicrobial resistance: a systematic scoping review. Issue 1 (4th January 2022)

• Record Type: Journal Article
• Authors: Oberin, Madalene; Badger, Skye; Faverjon, Céline; Cameron, Angus; Bannister-Tyrrell, Melanie
• Is Part Of: BMJ global health. Volume 7:Issue 1(2022)
• Publication Date: 2022-01-04
• Subjects: epidemiology -- health systems -- public health -- systematic review; World health -- Periodicals; 362.105
• DOI: 10.1136/bmjgh-2021-007388
• Languages: English
• ISSNs: 2059-7908

Abstract

Abstract : Introduction: Electronic information systems (EIS) that implement a 'One Health' approach by integrating antimicrobial resistance (AMR) data across the human, animal and environmental health sectors, have been identified as a global priority. However, evidence on the availability, technical capacities and effectiveness of such EIS is scarce. Methods: Through a qualitative synthesis of evidence, this systematic scoping review aims to: identify EIS for AMR surveillance that operate across human, animal and environmental health sectors; describe their technical characteristics and capabilities; and assess whether there is evidence for the effectiveness of the various EIS for AMR surveillance. Studies and reports between 1 January 2000 and 21 July 2021 from peer-reviewed and grey literature in the English language were included. Results: 26 studies and reports were included in the final review, of which 27 EIS were described. None of the EIS integrated AMR data in a One Health approach across all three sectors. While there was a lack of evidence of thorough evaluations of the effectiveness of the identified EIS, several surveillance system effectiveness indicators were reported for most EIS. Standardised reporting of the effectiveness of EIS is recommended for future publications. The capabilities of the EIS varied in their technical design features, in terms of usability, data display tools and desired outputs. EIS that included interactive features, and geospatial maps are increasingly relevant for future trends in AMR data analytics. Conclusion: No EIS for AMR surveillance was identified that was designed to integrate a broad range of AMR data from humans, animals and the environment, representing a major gap in global efforts to implement One Health approaches to address AMR.