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Diagnostics
Volume 11
Issue 1
10.3390/diagnostics11010022
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Review

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

by
Kameko Nichols
1,†,
Sarah J. Girdwood
2,*,†,
Andrew Inglis
3,
Pascale Ondoa
4,5,6,
Karla Therese L. Sy
7,8,
Mariet Benade
7,
Aloysius Bingi Tusiime
9,
Kekeletso Kao
1,
Sergio Carmona
1,
Heidi Albert
10,‡ and
Brooke E. Nichols
2,7,11,*,‡
1
FIND, 1202 Geneva, Switzerland
2
Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2193, South Africa
3
USAID Global Health Supply Chain Programme, Procurement and Supply Management, International Business Machines, Arlington, VA 22202, USA
4
African Society for Laboratory Medicine, Addis Ababa 5487, Ethiopia
5
Amsterdam Institute for Global Health and Development, 1105 BP Amsterdam, The Netherlands
6
Department of Global Health, Amsterdam University Medical Center, 1105 AZ Amsterdam, The Netherlands
7
Department of Global Health, Boston University School of Public Health, Boston, MA 02118, USA
8
Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
9
USAID Global Health Supply Chain Programme, Procurement and Supply Management, Chemonics International, Arlington, VA 22202, USA
10
FIND, Cape Town 7925, South Africa
11
Department of Medical Microbiology, Amsterdam University Medical Center, 1105 AZ Amsterdam, The Netherlands
 
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*
Authors to whom correspondence should be addressed.
†
Equal contribution.
‡
Equal contribution.
Diagnostics 2021, 11(1), 22; https://doi.org/10.3390/diagnostics11010022
Received: 30 November 2020 / Revised: 19 December 2020 / Accepted: 21 December 2020 / Published: 24 December 2020
(This article belongs to the Special Issue HIV Diagnosis, Treatment, and Care)
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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. View Full-Text
Keywords: diagnostic network optimization; data analytics; low- and middle-income countries diagnostic network optimization; data analytics; low- and middle-income countries
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MDPI and ACS Style

Nichols, K.; Girdwood, S.J.; Inglis, A.; Ondoa, P.; Sy, K.T.L.; Benade, M.; Tusiime, A.B.; Kao, K.; Carmona, S.; Albert, H.; Nichols, B.E. Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions. Diagnostics 2021, 11, 22. https://doi.org/10.3390/diagnostics11010022

AMA Style

Nichols K, Girdwood SJ, Inglis A, Ondoa P, Sy KTL, Benade M, Tusiime AB, Kao K, Carmona S, Albert H, Nichols BE. Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions. Diagnostics. 2021; 11(1):22. https://doi.org/10.3390/diagnostics11010022

Chicago/Turabian Style

Nichols, Kameko, Sarah J. Girdwood, Andrew Inglis, Pascale Ondoa, Karla T.L. Sy, Mariet Benade, Aloysius B. Tusiime, Kekeletso Kao, Sergio Carmona, Heidi Albert, and Brooke E. Nichols. 2021. "Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions" Diagnostics 11, no. 1: 22. https://doi.org/10.3390/diagnostics11010022

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