Using digital health technologies to optimise antimicrobial use globally
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Author(s)
Type
Journal Article
Abstract
Digital health technology (DHT) describes tools and devices that generate or process health data. The application of
DHTs could improve the diagnosis, treatment, and surveillance of bacterial infection and the prevention of
antimicrobial resistance (AMR). DHTs to optimise antimicrobial use are rapidly being developed. To support the
global adoption of DHTs and the opportunities offered to optimise antimicrobial use consensus is needed on what
data are required to support antimicrobial decision making. This Series paper will explore bacterial AMR in humans
and the need to optimise antimicrobial use in response to this global threat. It will also describe state-of-the-art DHTs
to optimise antimicrobial prescribing in high-income and low-income and middle-income countries, and consider
what fundamental data are ideally required for and from such technologies to support optimised antimicrobial use.
DHTs could improve the diagnosis, treatment, and surveillance of bacterial infection and the prevention of
antimicrobial resistance (AMR). DHTs to optimise antimicrobial use are rapidly being developed. To support the
global adoption of DHTs and the opportunities offered to optimise antimicrobial use consensus is needed on what
data are required to support antimicrobial decision making. This Series paper will explore bacterial AMR in humans
and the need to optimise antimicrobial use in response to this global threat. It will also describe state-of-the-art DHTs
to optimise antimicrobial prescribing in high-income and low-income and middle-income countries, and consider
what fundamental data are ideally required for and from such technologies to support optimised antimicrobial use.
Date Issued
2024-12
Date Acceptance
2024-11-01
Citation
The Lancet Digital Health, 2024, 6 (12), pp.e914-e925
ISSN
2589-7500
Publisher
Elsevier BV
Start Page
e914
End Page
e925
Journal / Book Title
The Lancet Digital Health
Volume
6
Issue
12
Copyright Statement
© 2024 The Author(s). Published by Elsevier Ltd. This is an
Open Access article under the CC BY 4.0 license.
Open Access article under the CC BY 4.0 license.
License URL
Identifier
http://dx.doi.org/10.1016/s2589-7500(24)00198-5
Publication Status
Published
Date Publish Online
2024-11-14