Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions

Nichols, Kameko and Girdwood, Sarah J. and Inglis, Andrew and Ondoa, Pascale and Sy, Karla Therese L. and Benade, Mariet and Tusiime, Aloysius Bingi and Kao, Kekeletso and Carmona, Sergio and Albert, Heidi and Nichols, Brooke E. (2020) Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions. Diagnostics, 11 (1). p. 22. ISSN 2075-4418

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Abstract

Diagnostics services are an essential component of healthcare systems, advancing universal health coverage and ensuring global health security, but are often unavailable or under-resourced in low- and middle-income (LMIC) countries. Typically, diagnostics are delivered at various tiers of the laboratory network based on population needs, and resource and infrastructure constraints. A diagnostic network additionally incorporates screening and includes point-of-care testing that may occur outside of a laboratory in the community and clinic settings; it also emphasizes the importance of supportive network elements, including specimen referral systems, as being critical for the functioning of the diagnostic network. To date, design and planning of diagnostic networks in LMICs has largely been driven by infectious diseases such as TB and HIV, relying on manual methods and expert consensus, with a limited application of data analytics. Recently, there have been efforts to improve diagnostic network planning, including diagnostic network optimization (DNO). The DNO process involves the collection, mapping, and spatial analysis of baseline data; selection and development of scenarios to model and optimize; and lastly, implementing changes and measuring impact. This review outlines the goals of DNO and steps in the process, and provides clarity on commonly used terms.

Item Type: Article
Subjects: Journal Eprints > Medical Science
Depositing User: Managing Editor
Date Deposited: 06 Feb 2023 05:32
Last Modified: 23 Apr 2024 12:23
URI: http://repository.journal4submission.com/id/eprint/537

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