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Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study

BACKGROUND: There are limited existing approaches to generate estimates from Routine Health Information Systems (RHIS) data, despite the growing interest to these data. We calculated and assessed the consistency of maternal and child health service coverage estimates from RHIS data, using census-bas...

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Autores principales: Maïga, Abdoulaye, Amouzou, Agbessi, Bagayoko, Moussa, Faye, Cheikh M., Jiwani, Safia S., Kamara, Dauda, Koroma, Ibrahim B., Sankoh, Osman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8435364/
https://www.ncbi.nlm.nih.gov/pubmed/34511135
http://dx.doi.org/10.1186/s12913-021-06529-7
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author Maïga, Abdoulaye
Amouzou, Agbessi
Bagayoko, Moussa
Faye, Cheikh M.
Jiwani, Safia S.
Kamara, Dauda
Koroma, Ibrahim B.
Sankoh, Osman
author_facet Maïga, Abdoulaye
Amouzou, Agbessi
Bagayoko, Moussa
Faye, Cheikh M.
Jiwani, Safia S.
Kamara, Dauda
Koroma, Ibrahim B.
Sankoh, Osman
author_sort Maïga, Abdoulaye
collection PubMed
description BACKGROUND: There are limited existing approaches to generate estimates from Routine Health Information Systems (RHIS) data, despite the growing interest to these data. We calculated and assessed the consistency of maternal and child health service coverage estimates from RHIS data, using census-based and health service-based denominators in Sierra Leone. METHODS: We used Sierra Leone 2016 RHIS data to calculate coverage of first antenatal care contact (ANC1), institutional delivery and diphtheria-pertussis-tetanus 3 (DPT3) immunization service provision. For each indicator, national and district level coverages were calculated using denominators derived from two census-based and three health service-based methods. We compared the coverage estimates from RHIS data to estimates from MICS 2017. We considered the agreement adequate when estimates from RHIS fell within the 95% confidence interval of the survey estimate. RESULTS: We found an overall poor consistency of the coverage estimates calculated from the census-based methods. ANC1 and institutional delivery coverage estimates from these methods were greater than 100% in about half of the fourteen districts, and only 3 of the 14 districts had estimates consistent with the survey data. Health service-based methods generated better estimates. For institutional delivery coverage, five districts met the agreement criteria using BCG service-based method. We found better agreement for DPT3 coverage estimates using DPT1 service-based method as national coverage was close to survey data, and estimates were consistent for 8 out of 14 districts. DPT3 estimates were consistent in almost half of the districts (6/14) using ANC1 service-based method. CONCLUSION: The study highlighted the challenge in determining an appropriate denominator for RHIS-based coverage estimates. Systematic and transparent data quality check and correction, as well as rigorous approaches to determining denominators are key considerations to generate accurate coverage statistics using RHIS data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06529-7.
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spelling pubmed-84353642021-09-13 Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study Maïga, Abdoulaye Amouzou, Agbessi Bagayoko, Moussa Faye, Cheikh M. Jiwani, Safia S. Kamara, Dauda Koroma, Ibrahim B. Sankoh, Osman BMC Health Serv Res Research BACKGROUND: There are limited existing approaches to generate estimates from Routine Health Information Systems (RHIS) data, despite the growing interest to these data. We calculated and assessed the consistency of maternal and child health service coverage estimates from RHIS data, using census-based and health service-based denominators in Sierra Leone. METHODS: We used Sierra Leone 2016 RHIS data to calculate coverage of first antenatal care contact (ANC1), institutional delivery and diphtheria-pertussis-tetanus 3 (DPT3) immunization service provision. For each indicator, national and district level coverages were calculated using denominators derived from two census-based and three health service-based methods. We compared the coverage estimates from RHIS data to estimates from MICS 2017. We considered the agreement adequate when estimates from RHIS fell within the 95% confidence interval of the survey estimate. RESULTS: We found an overall poor consistency of the coverage estimates calculated from the census-based methods. ANC1 and institutional delivery coverage estimates from these methods were greater than 100% in about half of the fourteen districts, and only 3 of the 14 districts had estimates consistent with the survey data. Health service-based methods generated better estimates. For institutional delivery coverage, five districts met the agreement criteria using BCG service-based method. We found better agreement for DPT3 coverage estimates using DPT1 service-based method as national coverage was close to survey data, and estimates were consistent for 8 out of 14 districts. DPT3 estimates were consistent in almost half of the districts (6/14) using ANC1 service-based method. CONCLUSION: The study highlighted the challenge in determining an appropriate denominator for RHIS-based coverage estimates. Systematic and transparent data quality check and correction, as well as rigorous approaches to determining denominators are key considerations to generate accurate coverage statistics using RHIS data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06529-7. BioMed Central 2021-09-13 /pmc/articles/PMC8435364/ /pubmed/34511135 http://dx.doi.org/10.1186/s12913-021-06529-7 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
Maïga, Abdoulaye
Amouzou, Agbessi
Bagayoko, Moussa
Faye, Cheikh M.
Jiwani, Safia S.
Kamara, Dauda
Koroma, Ibrahim B.
Sankoh, Osman
Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study
title Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study
title_full Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study
title_fullStr Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study
title_full_unstemmed Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study
title_short Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study
title_sort measuring coverage of maternal and child health services using routine health facility data: a sierra leone case study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8435364/
https://www.ncbi.nlm.nih.gov/pubmed/34511135
http://dx.doi.org/10.1186/s12913-021-06529-7
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