Effect of data quality improvement intervention on health management information system data accuracy: An interrupted time series analysis.
BACKGROUND:As part of a partnership between the Institute for Healthcare Improvement and the Ethiopian Federal Ministry of Health, woreda-based quality improvement collaboratives took place between November 2016 and December 2017 aiming to accelerate reduction of maternal and neonatal mortality in L...
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doaj-40ce883e87b047df9005b10a5711574f2021-03-03T22:00:42ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01158e023770310.1371/journal.pone.0237703Effect of data quality improvement intervention on health management information system data accuracy: An interrupted time series analysis.Zewdie MulissaNaod WendradBefikadu BitewulignAbera BiadgoMehiret AbateHaregeweyni AlemuBiruk AbateAbiyou KiflieHema MaggeGareth ParryBACKGROUND:As part of a partnership between the Institute for Healthcare Improvement and the Ethiopian Federal Ministry of Health, woreda-based quality improvement collaboratives took place between November 2016 and December 2017 aiming to accelerate reduction of maternal and neonatal mortality in Lemu Bilbilu, Tanqua Abergele and Duguna Fango woredas. Before starting the collaboratives, assessments found inaccuracies in core measures obtained from Health Management Information System reports. METHODS AND RESULTS:Building on the quality improvement collaborative design, data quality improvement activities were added and we used the World Health Organization review methodology to drive a verification factor for the core measures of number of pregnant women that received their first antenatal care visit, number of pregnant women that received antenatal care on at least four visits, number of pregnant women tested for syphilis and number of births attended by skilled health personnel. Impact of the data quality improvement was assessed using interrupted time series analysis. We found accurate data across all time periods for Tanqua Abergele. In Lemu Bilbilu and Duguna Fango, data quality improved for all core metrics over time. In Duguna Fango, the verification factor for number of pregnant women that received their first antenatal care visit improved from 0.794 (95%CI 0.753, 0.836; p<0.001) pre-intervention by 0.173 (95%CI 0.128, 0.219; p<0.001) during the collaborative; and the verification factor for number of pregnant women tested for syphilis improved from 0.472 (95%CI 0.390, 0.554; p<0.001) pre-intervention by 0.460 (95%CI 0.369, 0.552; p<0.001) during the collaborative. In Lemu Bilbilu, the verification factor for number of pregnant women receiving a fourth antenatal visit rose from 0.589 (95%CI 0.513, 0.664; p<0.001) at baseline by 0.358 (95%CI 0.258, 0.458; p<0.001) post-intervention; and skilled birth attendance rose from 0.917 (95%CI 0.869, 0.965) at baseline by 0.083 (95%CI 0.030, 0.136; p<0.001) during the collaborative. CONCLUSIONS:A Data quality improvement initiative embedded within woreda clinical improvement collaborative improved accuracy of data used to monitor maternal and newborn health services in Ethiopia.https://doi.org/10.1371/journal.pone.0237703 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zewdie Mulissa Naod Wendrad Befikadu Bitewulign Abera Biadgo Mehiret Abate Haregeweyni Alemu Biruk Abate Abiyou Kiflie Hema Magge Gareth Parry |
spellingShingle |
Zewdie Mulissa Naod Wendrad Befikadu Bitewulign Abera Biadgo Mehiret Abate Haregeweyni Alemu Biruk Abate Abiyou Kiflie Hema Magge Gareth Parry Effect of data quality improvement intervention on health management information system data accuracy: An interrupted time series analysis. PLoS ONE |
author_facet |
Zewdie Mulissa Naod Wendrad Befikadu Bitewulign Abera Biadgo Mehiret Abate Haregeweyni Alemu Biruk Abate Abiyou Kiflie Hema Magge Gareth Parry |
author_sort |
Zewdie Mulissa |
title |
Effect of data quality improvement intervention on health management information system data accuracy: An interrupted time series analysis. |
title_short |
Effect of data quality improvement intervention on health management information system data accuracy: An interrupted time series analysis. |
title_full |
Effect of data quality improvement intervention on health management information system data accuracy: An interrupted time series analysis. |
title_fullStr |
Effect of data quality improvement intervention on health management information system data accuracy: An interrupted time series analysis. |
title_full_unstemmed |
Effect of data quality improvement intervention on health management information system data accuracy: An interrupted time series analysis. |
title_sort |
effect of data quality improvement intervention on health management information system data accuracy: an interrupted time series analysis. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2020-01-01 |
description |
BACKGROUND:As part of a partnership between the Institute for Healthcare Improvement and the Ethiopian Federal Ministry of Health, woreda-based quality improvement collaboratives took place between November 2016 and December 2017 aiming to accelerate reduction of maternal and neonatal mortality in Lemu Bilbilu, Tanqua Abergele and Duguna Fango woredas. Before starting the collaboratives, assessments found inaccuracies in core measures obtained from Health Management Information System reports. METHODS AND RESULTS:Building on the quality improvement collaborative design, data quality improvement activities were added and we used the World Health Organization review methodology to drive a verification factor for the core measures of number of pregnant women that received their first antenatal care visit, number of pregnant women that received antenatal care on at least four visits, number of pregnant women tested for syphilis and number of births attended by skilled health personnel. Impact of the data quality improvement was assessed using interrupted time series analysis. We found accurate data across all time periods for Tanqua Abergele. In Lemu Bilbilu and Duguna Fango, data quality improved for all core metrics over time. In Duguna Fango, the verification factor for number of pregnant women that received their first antenatal care visit improved from 0.794 (95%CI 0.753, 0.836; p<0.001) pre-intervention by 0.173 (95%CI 0.128, 0.219; p<0.001) during the collaborative; and the verification factor for number of pregnant women tested for syphilis improved from 0.472 (95%CI 0.390, 0.554; p<0.001) pre-intervention by 0.460 (95%CI 0.369, 0.552; p<0.001) during the collaborative. In Lemu Bilbilu, the verification factor for number of pregnant women receiving a fourth antenatal visit rose from 0.589 (95%CI 0.513, 0.664; p<0.001) at baseline by 0.358 (95%CI 0.258, 0.458; p<0.001) post-intervention; and skilled birth attendance rose from 0.917 (95%CI 0.869, 0.965) at baseline by 0.083 (95%CI 0.030, 0.136; p<0.001) during the collaborative. CONCLUSIONS:A Data quality improvement initiative embedded within woreda clinical improvement collaborative improved accuracy of data used to monitor maternal and newborn health services in Ethiopia. |
url |
https://doi.org/10.1371/journal.pone.0237703 |
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