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Understanding performance data: health management information system data accuracy in Southern Nations Nationalities and People’s Region, Ethiopia

BACKGROUND: Health management information system (HMIS) is a system whereby health data are recorded, stored, retrieved and processed to improve decision-making. HMIS data quality should be monitored routinely as production of high quality statistics depends on assessment of data quality and actions...

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Autores principales: Endriyas, Misganu, Alano, Abraham, Mekonnen, Emebet, Ayele, Sinafikish, Kelaye, Temesgen, Shiferaw, Mekonnen, Misganaw, Tebeje, Samuel, Teka, Hailemariam, Tesfahun, Hailu, Samuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423785/
https://www.ncbi.nlm.nih.gov/pubmed/30885204
http://dx.doi.org/10.1186/s12913-019-3991-7
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author Endriyas, Misganu
Alano, Abraham
Mekonnen, Emebet
Ayele, Sinafikish
Kelaye, Temesgen
Shiferaw, Mekonnen
Misganaw, Tebeje
Samuel, Teka
Hailemariam, Tesfahun
Hailu, Samuel
author_facet Endriyas, Misganu
Alano, Abraham
Mekonnen, Emebet
Ayele, Sinafikish
Kelaye, Temesgen
Shiferaw, Mekonnen
Misganaw, Tebeje
Samuel, Teka
Hailemariam, Tesfahun
Hailu, Samuel
author_sort Endriyas, Misganu
collection PubMed
description BACKGROUND: Health management information system (HMIS) is a system whereby health data are recorded, stored, retrieved and processed to improve decision-making. HMIS data quality should be monitored routinely as production of high quality statistics depends on assessment of data quality and actions taken to improve it. Thus, this study assessed accuracy of the routine HMIS data. METHODS: Facility based cross-sectional study was conducted in Southern Nations Nationalities and People’s region in 2017. Document review was done in 163 facilities of different levels. Statistical Package for the Social Sciences (SPSS) for windows version 20 was used to perform data analysis. Data accuracy was presented in terms of mean and standard deviation of data verification factor. RESULTS: Though inaccuracy was noted for all data elements, 96.9 and 84.7% of facilities reported institutional maternal death and skilled birth attendance within acceptable range respectively while confirmed malaria (45.4%), antenatal care fourth visit (46.6%), postnatal care (55.2%), fully immunized (55.8%), severe acute malnutrition (54.6%) and total malaria (50.3%) were reported accurately only by about half of facilities. Antenatal care fourth visit was over reported by 24% while total malaria was under reported by 28%. Reasons for variations included technical, behavioral and organizational factors. CONCLUSIONS: Majority of facilities over reported services while under reporting diseases. Data quality should be monitored routinely against data quality parameters quantitatively and/or qualitatively to catch-up country’s information revolution agenda.
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spelling pubmed-64237852019-03-28 Understanding performance data: health management information system data accuracy in Southern Nations Nationalities and People’s Region, Ethiopia Endriyas, Misganu Alano, Abraham Mekonnen, Emebet Ayele, Sinafikish Kelaye, Temesgen Shiferaw, Mekonnen Misganaw, Tebeje Samuel, Teka Hailemariam, Tesfahun Hailu, Samuel BMC Health Serv Res Research Article BACKGROUND: Health management information system (HMIS) is a system whereby health data are recorded, stored, retrieved and processed to improve decision-making. HMIS data quality should be monitored routinely as production of high quality statistics depends on assessment of data quality and actions taken to improve it. Thus, this study assessed accuracy of the routine HMIS data. METHODS: Facility based cross-sectional study was conducted in Southern Nations Nationalities and People’s region in 2017. Document review was done in 163 facilities of different levels. Statistical Package for the Social Sciences (SPSS) for windows version 20 was used to perform data analysis. Data accuracy was presented in terms of mean and standard deviation of data verification factor. RESULTS: Though inaccuracy was noted for all data elements, 96.9 and 84.7% of facilities reported institutional maternal death and skilled birth attendance within acceptable range respectively while confirmed malaria (45.4%), antenatal care fourth visit (46.6%), postnatal care (55.2%), fully immunized (55.8%), severe acute malnutrition (54.6%) and total malaria (50.3%) were reported accurately only by about half of facilities. Antenatal care fourth visit was over reported by 24% while total malaria was under reported by 28%. Reasons for variations included technical, behavioral and organizational factors. CONCLUSIONS: Majority of facilities over reported services while under reporting diseases. Data quality should be monitored routinely against data quality parameters quantitatively and/or qualitatively to catch-up country’s information revolution agenda. BioMed Central 2019-03-18 /pmc/articles/PMC6423785/ /pubmed/30885204 http://dx.doi.org/10.1186/s12913-019-3991-7 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Endriyas, Misganu
Alano, Abraham
Mekonnen, Emebet
Ayele, Sinafikish
Kelaye, Temesgen
Shiferaw, Mekonnen
Misganaw, Tebeje
Samuel, Teka
Hailemariam, Tesfahun
Hailu, Samuel
Understanding performance data: health management information system data accuracy in Southern Nations Nationalities and People’s Region, Ethiopia
title Understanding performance data: health management information system data accuracy in Southern Nations Nationalities and People’s Region, Ethiopia
title_full Understanding performance data: health management information system data accuracy in Southern Nations Nationalities and People’s Region, Ethiopia
title_fullStr Understanding performance data: health management information system data accuracy in Southern Nations Nationalities and People’s Region, Ethiopia
title_full_unstemmed Understanding performance data: health management information system data accuracy in Southern Nations Nationalities and People’s Region, Ethiopia
title_short Understanding performance data: health management information system data accuracy in Southern Nations Nationalities and People’s Region, Ethiopia
title_sort understanding performance data: health management information system data accuracy in southern nations nationalities and people’s region, ethiopia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423785/
https://www.ncbi.nlm.nih.gov/pubmed/30885204
http://dx.doi.org/10.1186/s12913-019-3991-7
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