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Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya
BACKGROUND: Target 3.2 of the United Nations Sustainable Development Goals (SDGs) is to reduce neonatal mortality. In low-income and middle-income countries (LMICs), the District Health Information Software, V.2 (DHIS2) is widely used to help improve indicator data reporting. There are few reports o...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7170465/ https://www.ncbi.nlm.nih.gov/pubmed/32337080 http://dx.doi.org/10.1136/bmjgh-2019-002108 |
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author | Hagel, Christiane Paton, Chris Mbevi, George English, Mike |
author_facet | Hagel, Christiane Paton, Chris Mbevi, George English, Mike |
author_sort | Hagel, Christiane |
collection | PubMed |
description | BACKGROUND: Target 3.2 of the United Nations Sustainable Development Goals (SDGs) is to reduce neonatal mortality. In low-income and middle-income countries (LMICs), the District Health Information Software, V.2 (DHIS2) is widely used to help improve indicator data reporting. There are few reports on its use for collecting neonatal hospital data that are of increasing importance as births within facilities increase. To address this gap, we investigated implementation experiences of DHIS2 in LMICs and mapped the information flow relevant for neonatal data reporting in Kenyan hospitals. METHODS: A narrative review of published literature and policy documents from LMICs was conducted. Information gathered was used to identify the challenges around DHIS2 and to map information flows from healthcare facilities to the national level. Two use cases explore how newborn data collection and reporting happens in hospitals. The results were validated, adjusted and system challenges identified. RESULTS: Literature and policy documents report that DHIS2 is a useful tool with strong technical capabilities, but significant challenges can emerge with the implementation. Visualisations of information flows highlight how a complex, people-based and paper-based subsystem for inpatient information capture precedes digitisation. Use cases point to major challenges in these subsystems in accurately identifying newborn deaths and appropriate data for the calculation of mortality even in hospitals. CONCLUSIONS: DHIS2 is a tool with potential to improve availability of health information that is key to health systems, but it critically depends on people-based and paper-based subsystems. In hospitals, the subsystems are subject to multiple micro level challenges. Work is needed to design and implement better standardised information processes, recording and reporting tools, and to strengthen the information system workforce. If the challenges are addressed and data quality improved, DHIS2 can support countries to track progress towards the SDG target of improving neonatal mortality. |
format | Online Article Text |
id | pubmed-7170465 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-71704652020-04-24 Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya Hagel, Christiane Paton, Chris Mbevi, George English, Mike BMJ Glob Health Original Research BACKGROUND: Target 3.2 of the United Nations Sustainable Development Goals (SDGs) is to reduce neonatal mortality. In low-income and middle-income countries (LMICs), the District Health Information Software, V.2 (DHIS2) is widely used to help improve indicator data reporting. There are few reports on its use for collecting neonatal hospital data that are of increasing importance as births within facilities increase. To address this gap, we investigated implementation experiences of DHIS2 in LMICs and mapped the information flow relevant for neonatal data reporting in Kenyan hospitals. METHODS: A narrative review of published literature and policy documents from LMICs was conducted. Information gathered was used to identify the challenges around DHIS2 and to map information flows from healthcare facilities to the national level. Two use cases explore how newborn data collection and reporting happens in hospitals. The results were validated, adjusted and system challenges identified. RESULTS: Literature and policy documents report that DHIS2 is a useful tool with strong technical capabilities, but significant challenges can emerge with the implementation. Visualisations of information flows highlight how a complex, people-based and paper-based subsystem for inpatient information capture precedes digitisation. Use cases point to major challenges in these subsystems in accurately identifying newborn deaths and appropriate data for the calculation of mortality even in hospitals. CONCLUSIONS: DHIS2 is a tool with potential to improve availability of health information that is key to health systems, but it critically depends on people-based and paper-based subsystems. In hospitals, the subsystems are subject to multiple micro level challenges. Work is needed to design and implement better standardised information processes, recording and reporting tools, and to strengthen the information system workforce. If the challenges are addressed and data quality improved, DHIS2 can support countries to track progress towards the SDG target of improving neonatal mortality. BMJ Publishing Group 2020-03-31 /pmc/articles/PMC7170465/ /pubmed/32337080 http://dx.doi.org/10.1136/bmjgh-2019-002108 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Research Hagel, Christiane Paton, Chris Mbevi, George English, Mike Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya |
title | Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya |
title_full | Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya |
title_fullStr | Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya |
title_full_unstemmed | Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya |
title_short | Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya |
title_sort | data for tracking sdgs: challenges in capturing neonatal data from hospitals in kenya |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7170465/ https://www.ncbi.nlm.nih.gov/pubmed/32337080 http://dx.doi.org/10.1136/bmjgh-2019-002108 |
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