Routine health management information system data in Ethiopia: consistency, trends, and challenges
Background: Ethiopia is investing in the routine Health Management Information System. Improved routine data are needed for decision-making in the health sector. Objective: To analyse the quality of the routine Health Management Information System data and triangulate with other sources, such as the...
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Online Access: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833046/ http://www.ncbi.nlm.nih.gov/pubmed/33446081 https://doi.org/10.1080/16549716.2020.1868961 |
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ftpubmed:oai:pubmedcentral.nih.gov:7833046 2023-05-15T17:53:59+02:00 Routine health management information system data in Ethiopia: consistency, trends, and challenges Adane, Abyot Adege, Tewabe M. Ahmed, Mesoud M. Anteneh, Habtamu A. Ayalew, Emiamrew S. Berhanu, Della Berhanu, Netsanet Beyene, Misrak G. Bhattacharya, Antoinette Bishaw, Tesfahun Cherinet, Eshetu Dereje, Mamo Desta, Tsega H. Dibabe, Abera Firew, Heven S. Gebrehiwot, Freweini Gebreyohannes, Etenesh Gella, Zenebech Girma, Addis Halefom, Zuriash Jama, Sorsa F. Kemal, Binyam Kiflom, Abyi Källestål, Carina Lemma, Seblewengel Mazengiya, Yidnekachew D. Mekete, Kalkidan Mengesha, Magdelawit Nega, Meresha W. Otoro, Israel A. Schellenberg, Joanna Taddele, Tefera Tefera, Gulilat Teketel, Admasu Tesfaye, Miraf Tsegaye, Tsion Woldesenbet, Kidist Wondarad, Yakob Yosuf, Zemzem M. Zealiyas, Kidist Zeweli, Mebratom H. Persson, Lars Åke Janson, Annika 2021-01-15 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833046/ http://www.ncbi.nlm.nih.gov/pubmed/33446081 https://doi.org/10.1080/16549716.2020.1868961 en eng Taylor & Francis http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833046/ http://www.ncbi.nlm.nih.gov/pubmed/33446081 http://dx.doi.org/10.1080/16549716.2020.1868961 © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. CC-BY Glob Health Action Methods Forum Text 2021 ftpubmed https://doi.org/10.1080/16549716.2020.1868961 2021-02-07T01:36:14Z Background: Ethiopia is investing in the routine Health Management Information System. Improved routine data are needed for decision-making in the health sector. Objective: To analyse the quality of the routine Health Management Information System data and triangulate with other sources, such as the Demographic and Health Surveys. Methods: We analysed national Health Management Information System data on 19 indicators of maternal health, neonatal survival, immunization, child nutrition, malaria, and tuberculosis over the 2012–2018 time period. The analyses were conducted by 38 analysts from the Ministry of Health, Ethiopia, and two government agencies who participated in the Operational Research and Coaching for Analysts (ORCA) project between June 2018 and June 2020. Using a World Health Organization Data Quality Review toolkit, we assessed indicator definitions, completeness, internal consistency over time and between related indicators, and external consistency compared with other data sources. Results: Several services reported coverage of above 100%. For many indicators, denominators were based on poor-quality population data estimates. Data on individual vaccinations had relatively good internal consistency. In contrast, there was low external consistency for data on fully vaccinated children, with the routine Health Management Information System showing 89% coverage but the Demographic and Health Survey estimate at 39%. Maternal health indicators displayed increasing coverage over time. Indicators on child nutrition, malaria, and tuberculosis were less consistent. Data on neonatal mortality were incomplete and operationalised as mortality on day 0–6. Our comparisons with survey and population projections indicated that one in eight early neonatal deaths were reported in the routine Health Management Information System. Data quality varied between regions. Conclusions: The quality of routine data gathered in the health system needs further attention. We suggest regular triangulation with data from other ... Text Orca PubMed Central (PMC) Global Health Action 14 1 1868961 |
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Methods Forum Adane, Abyot Adege, Tewabe M. Ahmed, Mesoud M. Anteneh, Habtamu A. Ayalew, Emiamrew S. Berhanu, Della Berhanu, Netsanet Beyene, Misrak G. Bhattacharya, Antoinette Bishaw, Tesfahun Cherinet, Eshetu Dereje, Mamo Desta, Tsega H. Dibabe, Abera Firew, Heven S. Gebrehiwot, Freweini Gebreyohannes, Etenesh Gella, Zenebech Girma, Addis Halefom, Zuriash Jama, Sorsa F. Kemal, Binyam Kiflom, Abyi Källestål, Carina Lemma, Seblewengel Mazengiya, Yidnekachew D. Mekete, Kalkidan Mengesha, Magdelawit Nega, Meresha W. Otoro, Israel A. Schellenberg, Joanna Taddele, Tefera Tefera, Gulilat Teketel, Admasu Tesfaye, Miraf Tsegaye, Tsion Woldesenbet, Kidist Wondarad, Yakob Yosuf, Zemzem M. Zealiyas, Kidist Zeweli, Mebratom H. Persson, Lars Åke Janson, Annika Routine health management information system data in Ethiopia: consistency, trends, and challenges |
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Background: Ethiopia is investing in the routine Health Management Information System. Improved routine data are needed for decision-making in the health sector. Objective: To analyse the quality of the routine Health Management Information System data and triangulate with other sources, such as the Demographic and Health Surveys. Methods: We analysed national Health Management Information System data on 19 indicators of maternal health, neonatal survival, immunization, child nutrition, malaria, and tuberculosis over the 2012–2018 time period. The analyses were conducted by 38 analysts from the Ministry of Health, Ethiopia, and two government agencies who participated in the Operational Research and Coaching for Analysts (ORCA) project between June 2018 and June 2020. Using a World Health Organization Data Quality Review toolkit, we assessed indicator definitions, completeness, internal consistency over time and between related indicators, and external consistency compared with other data sources. Results: Several services reported coverage of above 100%. For many indicators, denominators were based on poor-quality population data estimates. Data on individual vaccinations had relatively good internal consistency. In contrast, there was low external consistency for data on fully vaccinated children, with the routine Health Management Information System showing 89% coverage but the Demographic and Health Survey estimate at 39%. Maternal health indicators displayed increasing coverage over time. Indicators on child nutrition, malaria, and tuberculosis were less consistent. Data on neonatal mortality were incomplete and operationalised as mortality on day 0–6. Our comparisons with survey and population projections indicated that one in eight early neonatal deaths were reported in the routine Health Management Information System. Data quality varied between regions. Conclusions: The quality of routine data gathered in the health system needs further attention. We suggest regular triangulation with data from other ... |
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Adane, Abyot Adege, Tewabe M. Ahmed, Mesoud M. Anteneh, Habtamu A. Ayalew, Emiamrew S. Berhanu, Della Berhanu, Netsanet Beyene, Misrak G. Bhattacharya, Antoinette Bishaw, Tesfahun Cherinet, Eshetu Dereje, Mamo Desta, Tsega H. Dibabe, Abera Firew, Heven S. Gebrehiwot, Freweini Gebreyohannes, Etenesh Gella, Zenebech Girma, Addis Halefom, Zuriash Jama, Sorsa F. Kemal, Binyam Kiflom, Abyi Källestål, Carina Lemma, Seblewengel Mazengiya, Yidnekachew D. Mekete, Kalkidan Mengesha, Magdelawit Nega, Meresha W. Otoro, Israel A. Schellenberg, Joanna Taddele, Tefera Tefera, Gulilat Teketel, Admasu Tesfaye, Miraf Tsegaye, Tsion Woldesenbet, Kidist Wondarad, Yakob Yosuf, Zemzem M. Zealiyas, Kidist Zeweli, Mebratom H. Persson, Lars Åke Janson, Annika |
author_facet |
Adane, Abyot Adege, Tewabe M. Ahmed, Mesoud M. Anteneh, Habtamu A. Ayalew, Emiamrew S. Berhanu, Della Berhanu, Netsanet Beyene, Misrak G. Bhattacharya, Antoinette Bishaw, Tesfahun Cherinet, Eshetu Dereje, Mamo Desta, Tsega H. Dibabe, Abera Firew, Heven S. Gebrehiwot, Freweini Gebreyohannes, Etenesh Gella, Zenebech Girma, Addis Halefom, Zuriash Jama, Sorsa F. Kemal, Binyam Kiflom, Abyi Källestål, Carina Lemma, Seblewengel Mazengiya, Yidnekachew D. Mekete, Kalkidan Mengesha, Magdelawit Nega, Meresha W. Otoro, Israel A. Schellenberg, Joanna Taddele, Tefera Tefera, Gulilat Teketel, Admasu Tesfaye, Miraf Tsegaye, Tsion Woldesenbet, Kidist Wondarad, Yakob Yosuf, Zemzem M. Zealiyas, Kidist Zeweli, Mebratom H. Persson, Lars Åke Janson, Annika |
author_sort |
Adane, Abyot |
title |
Routine health management information system data in Ethiopia: consistency, trends, and challenges |
title_short |
Routine health management information system data in Ethiopia: consistency, trends, and challenges |
title_full |
Routine health management information system data in Ethiopia: consistency, trends, and challenges |
title_fullStr |
Routine health management information system data in Ethiopia: consistency, trends, and challenges |
title_full_unstemmed |
Routine health management information system data in Ethiopia: consistency, trends, and challenges |
title_sort |
routine health management information system data in ethiopia: consistency, trends, and challenges |
publisher |
Taylor & Francis |
publishDate |
2021 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833046/ http://www.ncbi.nlm.nih.gov/pubmed/33446081 https://doi.org/10.1080/16549716.2020.1868961 |
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Orca |
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Orca |
op_source |
Glob Health Action |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833046/ http://www.ncbi.nlm.nih.gov/pubmed/33446081 http://dx.doi.org/10.1080/16549716.2020.1868961 |
op_rights |
© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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CC-BY |
op_doi |
https://doi.org/10.1080/16549716.2020.1868961 |
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