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The development and design of a highly discerning platform for data capture in a neonatal encephalopathy study
Dissertation (MSc (Medical Immunology))--University of Pretoria, 2024.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2025
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| _version_ | 1867613528447254528 |
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| access_status_str | Open Access |
| author2 | Pepper, Michael Sean |
| author_browse | Pepper, Michael Sean |
| author_facet | Pepper, Michael Sean |
| collection | Thesis |
| dc_rights_str_mv | © 2023 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MSc (Medical Immunology))--University of Pretoria, 2024. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/100047 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:34.848Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/100047 The development and design of a highly discerning platform for data capture in a neonatal encephalopathy study Pepper, Michael Sean tkkalua@gmail.com Joubert, Fourie Van Rensburg, Jeanne Kalua, Thumbiko Clover UCTD Sustainable Development Goals (SDGs) Database design NESHIE Data quality REDCap Hypoxic-ischaemic encephalopathy Error detection Dissertation (MSc (Medical Immunology))--University of Pretoria, 2024. Background: NESHIE is a clinical condition defined by a restricted supply of oxygen and blood flow around the time of labour and delivery. Some neonates diagnosed with moderate and severe cases die in the infantile stage while surviving neonates may develop neurodevelopmental disorders, with cerebral palsy being one of the most adverse outcomes. REDCap, an electronic data capture software, is utilised in the NESHIE study. However, database users are prone to data capturing errors. Therefore, we undertook a redesign of an existing REDCap database to reduce data capturing errors. The aims were to design and develop a national-level database capable of capturing and storing multiple data points from several sites. In addition, it will evaluate the data capture process to refine data quality assessments and enhance overall data accuracy, ensuring the database meets the needs of diverse users across all study sites. Method: Clinical data captured in REDCap was compared with corresponding case report forms to identify data discrepancies across all study sites. Key areas responsible for data discrepancies were identified; built-in and advanced REDCap features were leveraged to refine the database. To assess the impact of the adjustments, comparative analyses were conducted using Chi-squared analysis in R to compare variance across the original and adjusted databases. Post-hoc analysis with Bonferroni correction was also performed. Results and Discussion: Prior to implementing the refined database, error rates ranged between 6-20% (n=77). However, in the refined database across all sites (n=83), error rates were observed at 1-11%. These errors were mainly attributed to missing or unavailable data, as well as misinterpretation of case report forms. There was a noted significant difference in comparisons between the early amendments (A3 and A4) and the refined database (A7; p<0.05). showing a significant reduction in errors from the first database compared to the refined database. Conclusion: By leveraging multiple in-built features of REDCap, the aesthetics of the database were improved, and user error rates reduced. The enhancements ensure continued efficient usability, while simultaneously promoting the maintenance of high-quality data. Immunology Msc (Medical Immunology) Unrestricted Faculty of Health Sciences SDG-03: Good health and well-being 2025-01-15T06:37:48Z 2025-01-15T06:37:48Z 2025-05 2024-08 Dissertation * A2025 http://hdl.handle.net/2263/100047 10.25403/UPresearchdata.27967398 en © 2023 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Sustainable Development Goals (SDGs) Database design NESHIE Data quality REDCap Hypoxic-ischaemic encephalopathy Error detection The development and design of a highly discerning platform for data capture in a neonatal encephalopathy study |
| title | The development and design of a highly discerning platform for data capture in a neonatal encephalopathy study |
| title_full | The development and design of a highly discerning platform for data capture in a neonatal encephalopathy study |
| title_fullStr | The development and design of a highly discerning platform for data capture in a neonatal encephalopathy study |
| title_full_unstemmed | The development and design of a highly discerning platform for data capture in a neonatal encephalopathy study |
| title_short | The development and design of a highly discerning platform for data capture in a neonatal encephalopathy study |
| title_sort | development and design of a highly discerning platform for data capture in a neonatal encephalopathy study |
| topic | UCTD Sustainable Development Goals (SDGs) Database design NESHIE Data quality REDCap Hypoxic-ischaemic encephalopathy Error detection |
| url | http://hdl.handle.net/2263/100047 |