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

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 labora...

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Autores principales: Nichols, Kameko, Girdwood, Sarah J., Inglis, Andrew, Ondoa, Pascale, Sy, Karla Therese L., Benade, Mariet, Tusiime, Aloysius Bingi, Kao, Kekeletso, Carmona, Sergio, Albert, Heidi, Nichols, Brooke E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7823670/
https://www.ncbi.nlm.nih.gov/pubmed/33374315
http://dx.doi.org/10.3390/diagnostics11010022
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author Nichols, Kameko
Girdwood, Sarah J.
Inglis, Andrew
Ondoa, Pascale
Sy, Karla Therese L.
Benade, Mariet
Tusiime, Aloysius Bingi
Kao, Kekeletso
Carmona, Sergio
Albert, Heidi
Nichols, Brooke E.
author_facet Nichols, Kameko
Girdwood, Sarah J.
Inglis, Andrew
Ondoa, Pascale
Sy, Karla Therese L.
Benade, Mariet
Tusiime, Aloysius Bingi
Kao, Kekeletso
Carmona, Sergio
Albert, Heidi
Nichols, Brooke E.
author_sort Nichols, Kameko
collection PubMed
description 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.
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spelling pubmed-78236702021-01-24 Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions Nichols, Kameko Girdwood, Sarah J. Inglis, Andrew Ondoa, Pascale Sy, Karla Therese L. Benade, Mariet Tusiime, Aloysius Bingi Kao, Kekeletso Carmona, Sergio Albert, Heidi Nichols, Brooke E. Diagnostics (Basel) Review 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. MDPI 2020-12-24 /pmc/articles/PMC7823670/ /pubmed/33374315 http://dx.doi.org/10.3390/diagnostics11010022 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Nichols, Kameko
Girdwood, Sarah J.
Inglis, Andrew
Ondoa, Pascale
Sy, Karla Therese L.
Benade, Mariet
Tusiime, Aloysius Bingi
Kao, Kekeletso
Carmona, Sergio
Albert, Heidi
Nichols, Brooke E.
Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions
title Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions
title_full Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions
title_fullStr Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions
title_full_unstemmed Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions
title_short Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions
title_sort bringing data analytics to the design of optimized diagnostic networks in low- and middle-income countries: process, terms and definitions
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7823670/
https://www.ncbi.nlm.nih.gov/pubmed/33374315
http://dx.doi.org/10.3390/diagnostics11010022
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