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Improving Data Integrity in Public Health: A Case Study of an Outbreak Management System in Nigeria
The completeness and accuracy of data in the Nigerian health care system is a challenge. Studies have shown that the data quality, and by extension data integrity, has been suboptimal and thus poses a barrier to strengthening service delivery. This article showcases how the design process sparked th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Global Health: Science and Practice
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628498/ https://www.ncbi.nlm.nih.gov/pubmed/34845046 http://dx.doi.org/10.9745/GHSP-D-21-00240 |
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author | Tijani, Bosun Jaiyeola, Tomi Oladejo, Busayo Kassam, Zahra |
author_facet | Tijani, Bosun Jaiyeola, Tomi Oladejo, Busayo Kassam, Zahra |
author_sort | Tijani, Bosun |
collection | PubMed |
description | The completeness and accuracy of data in the Nigerian health care system is a challenge. Studies have shown that the data quality, and by extension data integrity, has been suboptimal and thus poses a barrier to strengthening service delivery. This article showcases how the design process sparked the concept for an intervention to improve the integrity of public health data being collected in Nigeria. In collaboration with the Nigerian Institute of Medical Research (NIMR) and Lifebank, the Co-creation Hub team conducted formative research with the coronavirus disease (COVID-19) test center managers at NIMR. The insights informed the development of the features for an outbreak management system. These features were refined through an iterative process of development and continuous feedback from the end users. NIMR reported an improvement in its data collection process and data integrity. They reported that (1) almost all data collection by the test center was now automated, thereby minimizing the proportion of inaccurate and repeat entry in comparison to data collected in other parts of the same center; (2) the auto-validation feature of the system ensured that all required fields of a patient’s information were completed and verified, thereby ensuring 100% data completeness; and (3) the validation and verification feature ensured that patients’ contact information was validated. The integration of this intervention into the current health information system ensures an improvement in the accuracy and validity of health care data being collected and stored. |
format | Online Article Text |
id | pubmed-8628498 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Global Health: Science and Practice |
record_format | MEDLINE/PubMed |
spelling | pubmed-86284982021-12-03 Improving Data Integrity in Public Health: A Case Study of an Outbreak Management System in Nigeria Tijani, Bosun Jaiyeola, Tomi Oladejo, Busayo Kassam, Zahra Glob Health Sci Pract Field Action Report The completeness and accuracy of data in the Nigerian health care system is a challenge. Studies have shown that the data quality, and by extension data integrity, has been suboptimal and thus poses a barrier to strengthening service delivery. This article showcases how the design process sparked the concept for an intervention to improve the integrity of public health data being collected in Nigeria. In collaboration with the Nigerian Institute of Medical Research (NIMR) and Lifebank, the Co-creation Hub team conducted formative research with the coronavirus disease (COVID-19) test center managers at NIMR. The insights informed the development of the features for an outbreak management system. These features were refined through an iterative process of development and continuous feedback from the end users. NIMR reported an improvement in its data collection process and data integrity. They reported that (1) almost all data collection by the test center was now automated, thereby minimizing the proportion of inaccurate and repeat entry in comparison to data collected in other parts of the same center; (2) the auto-validation feature of the system ensured that all required fields of a patient’s information were completed and verified, thereby ensuring 100% data completeness; and (3) the validation and verification feature ensured that patients’ contact information was validated. The integration of this intervention into the current health information system ensures an improvement in the accuracy and validity of health care data being collected and stored. Global Health: Science and Practice 2021-11-29 /pmc/articles/PMC8628498/ /pubmed/34845046 http://dx.doi.org/10.9745/GHSP-D-21-00240 Text en © Tijani et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited. To view a copy of the license, visit https://creativecommons.org/licenses/by/4.0/. When linking to this article, please use the following permanent link: https://doi.org/10.9745/GHSP-D-21-00240 |
spellingShingle | Field Action Report Tijani, Bosun Jaiyeola, Tomi Oladejo, Busayo Kassam, Zahra Improving Data Integrity in Public Health: A Case Study of an Outbreak Management System in Nigeria |
title | Improving Data Integrity in Public Health: A Case Study of an Outbreak Management System in Nigeria |
title_full | Improving Data Integrity in Public Health: A Case Study of an Outbreak Management System in Nigeria |
title_fullStr | Improving Data Integrity in Public Health: A Case Study of an Outbreak Management System in Nigeria |
title_full_unstemmed | Improving Data Integrity in Public Health: A Case Study of an Outbreak Management System in Nigeria |
title_short | Improving Data Integrity in Public Health: A Case Study of an Outbreak Management System in Nigeria |
title_sort | improving data integrity in public health: a case study of an outbreak management system in nigeria |
topic | Field Action Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628498/ https://www.ncbi.nlm.nih.gov/pubmed/34845046 http://dx.doi.org/10.9745/GHSP-D-21-00240 |
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