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Health management information system (HMIS) data quality and associated factors in Massaguet district, Chad

BACKGROUND: Quality data from Health Management Information Systems (HMIS) are important for tracking the effectiveness of malaria control interventions. However, HMIS data in many resource-limited settings do not currently meet standards set by the World Health Organization (WHO). We aimed to asses...

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Autores principales: Moukénet, Azoukalné, de Cola, Monica Anna, Ward, Charlotte, Beakgoubé, Honoré, Baker, Kevin, Donovan, Laura, Laoukolé, Jean, Richardson, Sol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8609810/
https://www.ncbi.nlm.nih.gov/pubmed/34809622
http://dx.doi.org/10.1186/s12911-021-01684-7
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author Moukénet, Azoukalné
de Cola, Monica Anna
Ward, Charlotte
Beakgoubé, Honoré
Baker, Kevin
Donovan, Laura
Laoukolé, Jean
Richardson, Sol
author_facet Moukénet, Azoukalné
de Cola, Monica Anna
Ward, Charlotte
Beakgoubé, Honoré
Baker, Kevin
Donovan, Laura
Laoukolé, Jean
Richardson, Sol
author_sort Moukénet, Azoukalné
collection PubMed
description BACKGROUND: Quality data from Health Management Information Systems (HMIS) are important for tracking the effectiveness of malaria control interventions. However, HMIS data in many resource-limited settings do not currently meet standards set by the World Health Organization (WHO). We aimed to assess HMIS data quality and associated factors in Chad. METHODS: A cross-sectional study was conducted in 14 health facilities in Massaguet district. Data on children under 15 years were obtained from the HMIS and from the external patient register covering the period January–December 2018. An additional questionnaire was administered to 16 health centre managers to collect data on contextual variables. Patient registry data were aggregated and compared with the HMIS database at district and health centre level. Completeness and accuracy indicators were calculated as per WHO guidelines. Multivariate logistic regressions were performed on the Verification Factor for attendance, suspected and confirmed malaria cases for three age groups (1 to < 12 months, 1 to < 5 years and 5 to < 15 years) to identify associations between health centre characteristics and data accuracy. RESULTS: Health centres achieved a high level of data completeness in HMIS. Malaria data were over-reported in HMIS for children aged under 15 years. There was an association between workload and higher odds of inaccuracy in reporting of attendance among children aged 1 to < 5 years (Odds ratio [OR]: 10.57, 95% CI 2.32–48.19) and 5– < 15 years (OR: 6.64, 95% CI 1.38–32.04). Similar association was found between workload and stock-outs in register books, and inaccuracy in reporting of malaria confirmed cases. Meanwhile, we found that presence of a health technician, and of dedicated staff for data management, were associated with lower inaccuracy in reporting of clinic attendance in children aged under five years. CONCLUSION: Data completeness was high while the accuracy was low. Factors associated with data inaccuracy included high workload and the unavailability of required data collection tools. The results suggest that improvement in working conditions for clinic personnel may improve HMIS data quality. Upgrading from paper-based forms to a web-based HMIS may provide a solution for improving data accuracy and its utility for future evaluations of health interventions. Results from this study can inform the Ministry of Health and it partners on the precautions to be taken in the use of HMIS data and inform initiatives for improving its quality. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-021-01684-7.
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spelling pubmed-86098102021-11-23 Health management information system (HMIS) data quality and associated factors in Massaguet district, Chad Moukénet, Azoukalné de Cola, Monica Anna Ward, Charlotte Beakgoubé, Honoré Baker, Kevin Donovan, Laura Laoukolé, Jean Richardson, Sol BMC Med Inform Decis Mak Research BACKGROUND: Quality data from Health Management Information Systems (HMIS) are important for tracking the effectiveness of malaria control interventions. However, HMIS data in many resource-limited settings do not currently meet standards set by the World Health Organization (WHO). We aimed to assess HMIS data quality and associated factors in Chad. METHODS: A cross-sectional study was conducted in 14 health facilities in Massaguet district. Data on children under 15 years were obtained from the HMIS and from the external patient register covering the period January–December 2018. An additional questionnaire was administered to 16 health centre managers to collect data on contextual variables. Patient registry data were aggregated and compared with the HMIS database at district and health centre level. Completeness and accuracy indicators were calculated as per WHO guidelines. Multivariate logistic regressions were performed on the Verification Factor for attendance, suspected and confirmed malaria cases for three age groups (1 to < 12 months, 1 to < 5 years and 5 to < 15 years) to identify associations between health centre characteristics and data accuracy. RESULTS: Health centres achieved a high level of data completeness in HMIS. Malaria data were over-reported in HMIS for children aged under 15 years. There was an association between workload and higher odds of inaccuracy in reporting of attendance among children aged 1 to < 5 years (Odds ratio [OR]: 10.57, 95% CI 2.32–48.19) and 5– < 15 years (OR: 6.64, 95% CI 1.38–32.04). Similar association was found between workload and stock-outs in register books, and inaccuracy in reporting of malaria confirmed cases. Meanwhile, we found that presence of a health technician, and of dedicated staff for data management, were associated with lower inaccuracy in reporting of clinic attendance in children aged under five years. CONCLUSION: Data completeness was high while the accuracy was low. Factors associated with data inaccuracy included high workload and the unavailability of required data collection tools. The results suggest that improvement in working conditions for clinic personnel may improve HMIS data quality. Upgrading from paper-based forms to a web-based HMIS may provide a solution for improving data accuracy and its utility for future evaluations of health interventions. Results from this study can inform the Ministry of Health and it partners on the precautions to be taken in the use of HMIS data and inform initiatives for improving its quality. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-021-01684-7. BioMed Central 2021-11-22 /pmc/articles/PMC8609810/ /pubmed/34809622 http://dx.doi.org/10.1186/s12911-021-01684-7 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
Moukénet, Azoukalné
de Cola, Monica Anna
Ward, Charlotte
Beakgoubé, Honoré
Baker, Kevin
Donovan, Laura
Laoukolé, Jean
Richardson, Sol
Health management information system (HMIS) data quality and associated factors in Massaguet district, Chad
title Health management information system (HMIS) data quality and associated factors in Massaguet district, Chad
title_full Health management information system (HMIS) data quality and associated factors in Massaguet district, Chad
title_fullStr Health management information system (HMIS) data quality and associated factors in Massaguet district, Chad
title_full_unstemmed Health management information system (HMIS) data quality and associated factors in Massaguet district, Chad
title_short Health management information system (HMIS) data quality and associated factors in Massaguet district, Chad
title_sort health management information system (hmis) data quality and associated factors in massaguet district, chad
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8609810/
https://www.ncbi.nlm.nih.gov/pubmed/34809622
http://dx.doi.org/10.1186/s12911-021-01684-7
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