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Quantifying the Validity of Routine Neonatal Healthcare Data in the Greater Accra Region, Ghana

OBJECTIVES: The District Health Information Management System–2 (DHIMS–2) is the database for storing health service data in Ghana, and similar to other low and middle income countries, paper-based data collection is being used by the Ghana Health Service. As the DHIMS-2 database has not been valida...

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Autores principales: Kayode, Gbenga A., Amoakoh-Coleman, Mary, Brown-Davies, Charles, Grobbee, Diederick E., Agyepong, Irene Akua, Ansah, Evelyn, Klipstein-Grobusch, Kerstin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4140714/
https://www.ncbi.nlm.nih.gov/pubmed/25144222
http://dx.doi.org/10.1371/journal.pone.0104053
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author Kayode, Gbenga A.
Amoakoh-Coleman, Mary
Brown-Davies, Charles
Grobbee, Diederick E.
Agyepong, Irene Akua
Ansah, Evelyn
Klipstein-Grobusch, Kerstin
author_facet Kayode, Gbenga A.
Amoakoh-Coleman, Mary
Brown-Davies, Charles
Grobbee, Diederick E.
Agyepong, Irene Akua
Ansah, Evelyn
Klipstein-Grobusch, Kerstin
author_sort Kayode, Gbenga A.
collection PubMed
description OBJECTIVES: The District Health Information Management System–2 (DHIMS–2) is the database for storing health service data in Ghana, and similar to other low and middle income countries, paper-based data collection is being used by the Ghana Health Service. As the DHIMS-2 database has not been validated before this study aimed to evaluate its validity. METHODS: Seven out of ten districts in the Greater Accra Region were randomly sampled; the district hospital and a polyclinic in each district were recruited for validation. Seven pre-specified neonatal health indicators were considered for validation: antenatal registrants, deliveries, total births, live birth, stillbirth, low birthweight, and neonatal death. Data were extracted on these health indicators from the primary data (hospital paper-registers) recorded from January to March 2012. We examined all the data captured during this period as these data have been uploaded to the DHIMS-2 database. The differences between the values of the health indicators obtained from the primary data and that of the facility and DHIMS–2 database were used to assess the accuracy of the database while its completeness was estimated by the percentage of missing data in the primary data. RESULTS: About 41,000 data were assessed and in almost all the districts, the error rates of the DHIMS-2 data were less than 2.1% while the percentages of missing data were below 2%. At the regional level, almost all the health indicators had an error rate below 1% while the overall error rate of the DHIMS-2 database was 0.68% (95% C I = 0.61–0.75) and the percentage of missing data was 3.1% (95% C I = 2.96–3.24). CONCLUSION: This study demonstrated that the percentage of missing data in the DHIMS-2 database was negligible while its accuracy was close to the acceptable range for high quality data.
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spelling pubmed-41407142014-08-25 Quantifying the Validity of Routine Neonatal Healthcare Data in the Greater Accra Region, Ghana Kayode, Gbenga A. Amoakoh-Coleman, Mary Brown-Davies, Charles Grobbee, Diederick E. Agyepong, Irene Akua Ansah, Evelyn Klipstein-Grobusch, Kerstin PLoS One Research Article OBJECTIVES: The District Health Information Management System–2 (DHIMS–2) is the database for storing health service data in Ghana, and similar to other low and middle income countries, paper-based data collection is being used by the Ghana Health Service. As the DHIMS-2 database has not been validated before this study aimed to evaluate its validity. METHODS: Seven out of ten districts in the Greater Accra Region were randomly sampled; the district hospital and a polyclinic in each district were recruited for validation. Seven pre-specified neonatal health indicators were considered for validation: antenatal registrants, deliveries, total births, live birth, stillbirth, low birthweight, and neonatal death. Data were extracted on these health indicators from the primary data (hospital paper-registers) recorded from January to March 2012. We examined all the data captured during this period as these data have been uploaded to the DHIMS-2 database. The differences between the values of the health indicators obtained from the primary data and that of the facility and DHIMS–2 database were used to assess the accuracy of the database while its completeness was estimated by the percentage of missing data in the primary data. RESULTS: About 41,000 data were assessed and in almost all the districts, the error rates of the DHIMS-2 data were less than 2.1% while the percentages of missing data were below 2%. At the regional level, almost all the health indicators had an error rate below 1% while the overall error rate of the DHIMS-2 database was 0.68% (95% C I = 0.61–0.75) and the percentage of missing data was 3.1% (95% C I = 2.96–3.24). CONCLUSION: This study demonstrated that the percentage of missing data in the DHIMS-2 database was negligible while its accuracy was close to the acceptable range for high quality data. Public Library of Science 2014-08-21 /pmc/articles/PMC4140714/ /pubmed/25144222 http://dx.doi.org/10.1371/journal.pone.0104053 Text en © 2014 Kayode et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Kayode, Gbenga A.
Amoakoh-Coleman, Mary
Brown-Davies, Charles
Grobbee, Diederick E.
Agyepong, Irene Akua
Ansah, Evelyn
Klipstein-Grobusch, Kerstin
Quantifying the Validity of Routine Neonatal Healthcare Data in the Greater Accra Region, Ghana
title Quantifying the Validity of Routine Neonatal Healthcare Data in the Greater Accra Region, Ghana
title_full Quantifying the Validity of Routine Neonatal Healthcare Data in the Greater Accra Region, Ghana
title_fullStr Quantifying the Validity of Routine Neonatal Healthcare Data in the Greater Accra Region, Ghana
title_full_unstemmed Quantifying the Validity of Routine Neonatal Healthcare Data in the Greater Accra Region, Ghana
title_short Quantifying the Validity of Routine Neonatal Healthcare Data in the Greater Accra Region, Ghana
title_sort quantifying the validity of routine neonatal healthcare data in the greater accra region, ghana
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4140714/
https://www.ncbi.nlm.nih.gov/pubmed/25144222
http://dx.doi.org/10.1371/journal.pone.0104053
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