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A roadmap for using DHIS2 data to track progress in key health indicators in the Global South: experience from sub-saharan Africa

High quality health data as collected by health management information systems (HMIS) is an important building block of national health systems. District Health Information System 2 (DHIS2) software is an innovation in data management and monitoring for strengthening HMIS that has been widely implem...

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Detalles Bibliográficos
Autores principales: Farnham, Andrea, Loss, Georg, Lyatuu, Isaac, Cossa, Herminio, Kulinkina, Alexandra V., Winkler, Mirko S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10230132/
https://www.ncbi.nlm.nih.gov/pubmed/37259137
http://dx.doi.org/10.1186/s12889-023-15979-z
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author Farnham, Andrea
Loss, Georg
Lyatuu, Isaac
Cossa, Herminio
Kulinkina, Alexandra V.
Winkler, Mirko S.
author_facet Farnham, Andrea
Loss, Georg
Lyatuu, Isaac
Cossa, Herminio
Kulinkina, Alexandra V.
Winkler, Mirko S.
author_sort Farnham, Andrea
collection PubMed
description High quality health data as collected by health management information systems (HMIS) is an important building block of national health systems. District Health Information System 2 (DHIS2) software is an innovation in data management and monitoring for strengthening HMIS that has been widely implemented in low and middle-income countries in the last decade. However, analysts and decision-makers still face significant challenges in fully utilizing the capabilities of DHIS2 data to pursue national and international health agendas. We aimed to (i) identify the most relevant health indicators captured by DHIS2 for tracking progress towards the Sustainable Development goals in sub-Saharan African countries and (ii) present a clear roadmap for improving DHIS2 data quality and consistency, with a special focus on immediately actionable solutions. We identified that key indicators in child and maternal health (e.g. vaccine coverage, maternal deaths) are currently being tracked in the DHIS2 of most countries, while other indicators (e.g. HIV/AIDS) would benefit from streamlining the number of indicators collected and standardizing case definitions. Common data issues included unreliable denominators for calculation of incidence, differences in reporting among health facilities, and programmatic differences in data quality. We proposed solutions for many common data pitfalls at the analysis level, including standardized data cleaning pipelines, k-means clustering to identify high performing health facilities in terms of data quality, and imputation methods. While we focus on immediately actionable solutions for DHIS2 analysts, improvements at the point of data collection are the most rigorous. By investing in improving data quality and monitoring, countries can leverage the current global attention on health data to strengthen HMIS and progress towards national and international health priorities.
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spelling pubmed-102301322023-06-01 A roadmap for using DHIS2 data to track progress in key health indicators in the Global South: experience from sub-saharan Africa Farnham, Andrea Loss, Georg Lyatuu, Isaac Cossa, Herminio Kulinkina, Alexandra V. Winkler, Mirko S. BMC Public Health Research in Practice High quality health data as collected by health management information systems (HMIS) is an important building block of national health systems. District Health Information System 2 (DHIS2) software is an innovation in data management and monitoring for strengthening HMIS that has been widely implemented in low and middle-income countries in the last decade. However, analysts and decision-makers still face significant challenges in fully utilizing the capabilities of DHIS2 data to pursue national and international health agendas. We aimed to (i) identify the most relevant health indicators captured by DHIS2 for tracking progress towards the Sustainable Development goals in sub-Saharan African countries and (ii) present a clear roadmap for improving DHIS2 data quality and consistency, with a special focus on immediately actionable solutions. We identified that key indicators in child and maternal health (e.g. vaccine coverage, maternal deaths) are currently being tracked in the DHIS2 of most countries, while other indicators (e.g. HIV/AIDS) would benefit from streamlining the number of indicators collected and standardizing case definitions. Common data issues included unreliable denominators for calculation of incidence, differences in reporting among health facilities, and programmatic differences in data quality. We proposed solutions for many common data pitfalls at the analysis level, including standardized data cleaning pipelines, k-means clustering to identify high performing health facilities in terms of data quality, and imputation methods. While we focus on immediately actionable solutions for DHIS2 analysts, improvements at the point of data collection are the most rigorous. By investing in improving data quality and monitoring, countries can leverage the current global attention on health data to strengthen HMIS and progress towards national and international health priorities. BioMed Central 2023-05-31 /pmc/articles/PMC10230132/ /pubmed/37259137 http://dx.doi.org/10.1186/s12889-023-15979-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research in Practice
Farnham, Andrea
Loss, Georg
Lyatuu, Isaac
Cossa, Herminio
Kulinkina, Alexandra V.
Winkler, Mirko S.
A roadmap for using DHIS2 data to track progress in key health indicators in the Global South: experience from sub-saharan Africa
title A roadmap for using DHIS2 data to track progress in key health indicators in the Global South: experience from sub-saharan Africa
title_full A roadmap for using DHIS2 data to track progress in key health indicators in the Global South: experience from sub-saharan Africa
title_fullStr A roadmap for using DHIS2 data to track progress in key health indicators in the Global South: experience from sub-saharan Africa
title_full_unstemmed A roadmap for using DHIS2 data to track progress in key health indicators in the Global South: experience from sub-saharan Africa
title_short A roadmap for using DHIS2 data to track progress in key health indicators in the Global South: experience from sub-saharan Africa
title_sort roadmap for using dhis2 data to track progress in key health indicators in the global south: experience from sub-saharan africa
topic Research in Practice
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10230132/
https://www.ncbi.nlm.nih.gov/pubmed/37259137
http://dx.doi.org/10.1186/s12889-023-15979-z
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