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A data quality assessment of the first four years of malaria reporting in the Senegal DHIS2, 2014–2017
BACKGROUND: As the global burden of malaria decreases, routine health information systems (RHIS) have become invaluable for monitoring progress towards elimination. The District Health Information System, version 2 (DHIS2) has been widely adopted across countries and is expected to increase the qual...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8722300/ https://www.ncbi.nlm.nih.gov/pubmed/34974837 http://dx.doi.org/10.1186/s12913-021-07364-6 |
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author | Muhoza, Pierre Tine, Roger Faye, Adama Gaye, Ibrahima Zeger, Scott L. Diaw, Abdoulaye Gueye, Alioune Badara Kante, Almamy Malick Ruff, Andrea Marx, Melissa A. |
author_facet | Muhoza, Pierre Tine, Roger Faye, Adama Gaye, Ibrahima Zeger, Scott L. Diaw, Abdoulaye Gueye, Alioune Badara Kante, Almamy Malick Ruff, Andrea Marx, Melissa A. |
author_sort | Muhoza, Pierre |
collection | PubMed |
description | BACKGROUND: As the global burden of malaria decreases, routine health information systems (RHIS) have become invaluable for monitoring progress towards elimination. The District Health Information System, version 2 (DHIS2) has been widely adopted across countries and is expected to increase the quality of reporting of RHIS. In this study, we evaluated the quality of reporting of key indicators of childhood malaria from January 2014 through December 2017, the first 4 years of DHIS2 implementation in Senegal. METHODS: Monthly data on the number of confirmed and suspected malaria cases as well as tests done were extracted from the Senegal DHIS2. Reporting completeness was measured as the number of monthly reports received divided by the expected number of reports in a given year. Completeness of indicator data was measured as the percentage of non-missing indicator values. We used a quasi-Poisson model with natural cubic spline terms of month of reporting to impute values missing at the facility level. We used the imputed values to take into account the percentage of malaria cases that were missed due to lack of reporting. Consistency was measured as the absence of moderate and extreme outliers, internal consistency between related indicators, and consistency of indicators over time. RESULTS: In contrast to public facilities of which 92.7% reported data in the DHIS2 system during the study period, only 15.3% of the private facilities used the reporting system. At the national level, completeness of facility reporting increased from 84.5% in 2014 to 97.5% in 2017. The percentage of expected malaria cases reported increased from 76.5% in 2014 to 94.7% in 2017. Over the study period, the percentage of malaria cases reported across all districts was on average 7.5% higher (P < 0.01) during the rainy season relative to the dry season. Reporting completeness rates were lower among hospitals compared to health centers and health posts. The incidence of moderate and extreme outlier values was 5.2 and 2.3%, respectively. The number of confirmed malaria cases increased by 15% whereas the numbers of suspected cases and tests conducted more than doubled from 2014 to 2017 likely due to a policy shift towards universal testing of pediatric febrile cases. CONCLUSIONS: The quality of reporting for malaria indicators in the Senegal DHIS2 has improved over time and the data are suitable for use to monitor progress in malaria programs, with an understanding of their limitations. Senegalese health authorities should maintain the focus on broader adoption of DHIS2 reporting by private facilities, the sustainability of district-level data quality reviews, facility-level supervision and feedback mechanisms at all levels of the health system. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-07364-6. |
format | Online Article Text |
id | pubmed-8722300 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-87223002022-01-06 A data quality assessment of the first four years of malaria reporting in the Senegal DHIS2, 2014–2017 Muhoza, Pierre Tine, Roger Faye, Adama Gaye, Ibrahima Zeger, Scott L. Diaw, Abdoulaye Gueye, Alioune Badara Kante, Almamy Malick Ruff, Andrea Marx, Melissa A. BMC Health Serv Res Research BACKGROUND: As the global burden of malaria decreases, routine health information systems (RHIS) have become invaluable for monitoring progress towards elimination. The District Health Information System, version 2 (DHIS2) has been widely adopted across countries and is expected to increase the quality of reporting of RHIS. In this study, we evaluated the quality of reporting of key indicators of childhood malaria from January 2014 through December 2017, the first 4 years of DHIS2 implementation in Senegal. METHODS: Monthly data on the number of confirmed and suspected malaria cases as well as tests done were extracted from the Senegal DHIS2. Reporting completeness was measured as the number of monthly reports received divided by the expected number of reports in a given year. Completeness of indicator data was measured as the percentage of non-missing indicator values. We used a quasi-Poisson model with natural cubic spline terms of month of reporting to impute values missing at the facility level. We used the imputed values to take into account the percentage of malaria cases that were missed due to lack of reporting. Consistency was measured as the absence of moderate and extreme outliers, internal consistency between related indicators, and consistency of indicators over time. RESULTS: In contrast to public facilities of which 92.7% reported data in the DHIS2 system during the study period, only 15.3% of the private facilities used the reporting system. At the national level, completeness of facility reporting increased from 84.5% in 2014 to 97.5% in 2017. The percentage of expected malaria cases reported increased from 76.5% in 2014 to 94.7% in 2017. Over the study period, the percentage of malaria cases reported across all districts was on average 7.5% higher (P < 0.01) during the rainy season relative to the dry season. Reporting completeness rates were lower among hospitals compared to health centers and health posts. The incidence of moderate and extreme outlier values was 5.2 and 2.3%, respectively. The number of confirmed malaria cases increased by 15% whereas the numbers of suspected cases and tests conducted more than doubled from 2014 to 2017 likely due to a policy shift towards universal testing of pediatric febrile cases. CONCLUSIONS: The quality of reporting for malaria indicators in the Senegal DHIS2 has improved over time and the data are suitable for use to monitor progress in malaria programs, with an understanding of their limitations. Senegalese health authorities should maintain the focus on broader adoption of DHIS2 reporting by private facilities, the sustainability of district-level data quality reviews, facility-level supervision and feedback mechanisms at all levels of the health system. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-07364-6. BioMed Central 2022-01-02 /pmc/articles/PMC8722300/ /pubmed/34974837 http://dx.doi.org/10.1186/s12913-021-07364-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Muhoza, Pierre Tine, Roger Faye, Adama Gaye, Ibrahima Zeger, Scott L. Diaw, Abdoulaye Gueye, Alioune Badara Kante, Almamy Malick Ruff, Andrea Marx, Melissa A. A data quality assessment of the first four years of malaria reporting in the Senegal DHIS2, 2014–2017 |
title | A data quality assessment of the first four years of malaria reporting in the Senegal DHIS2, 2014–2017 |
title_full | A data quality assessment of the first four years of malaria reporting in the Senegal DHIS2, 2014–2017 |
title_fullStr | A data quality assessment of the first four years of malaria reporting in the Senegal DHIS2, 2014–2017 |
title_full_unstemmed | A data quality assessment of the first four years of malaria reporting in the Senegal DHIS2, 2014–2017 |
title_short | A data quality assessment of the first four years of malaria reporting in the Senegal DHIS2, 2014–2017 |
title_sort | data quality assessment of the first four years of malaria reporting in the senegal dhis2, 2014–2017 |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8722300/ https://www.ncbi.nlm.nih.gov/pubmed/34974837 http://dx.doi.org/10.1186/s12913-021-07364-6 |
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