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Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal
The increasing availability and capabilities of mobile phones make them a feasible means of data collection. Electronic Data Capture (EDC) systems have been used widely for public health monitoring and surveillance activities, but documentation of their use in complicated research studies requiring...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496067/ https://www.ncbi.nlm.nih.gov/pubmed/28613121 http://dx.doi.org/10.1080/16549716.2017.1330858 |
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author | Style, Sarah Beard, B. James Harris-Fry, Helen Sengupta, Aman Jha, Sonali Shrestha, Bhim P. Rai, Anjana Paudel, Vikas Thondoo, Meelan Pulkki-Brannstrom, Anni-Maria Skordis-Worrall, Jolene Manandhar, Dharma S. Costello, Anthony Saville, Naomi M. |
author_facet | Style, Sarah Beard, B. James Harris-Fry, Helen Sengupta, Aman Jha, Sonali Shrestha, Bhim P. Rai, Anjana Paudel, Vikas Thondoo, Meelan Pulkki-Brannstrom, Anni-Maria Skordis-Worrall, Jolene Manandhar, Dharma S. Costello, Anthony Saville, Naomi M. |
author_sort | Style, Sarah |
collection | PubMed |
description | The increasing availability and capabilities of mobile phones make them a feasible means of data collection. Electronic Data Capture (EDC) systems have been used widely for public health monitoring and surveillance activities, but documentation of their use in complicated research studies requiring multiple systems is limited. This paper shares our experiences of designing and implementing a complex multi-component EDC system for a community-based four-armed cluster-Randomised Controlled Trial in the rural plains of Nepal, to help other researchers planning to use EDC for complex studies in low-income settings. We designed and implemented three interrelated mobile phone data collection systems to enrol and follow-up pregnant women (trial participants), and to support the implementation of trial interventions (women’s groups, food and cash transfers). 720 field staff used basic phones to send simple coded text messages, 539 women’s group facilitators used Android smartphones with Open Data Kit Collect, and 112 Interviewers, Coordinators and Supervisors used smartphones with CommCare. Barcoded photo ID cards encoded with participant information were generated for each enrolled woman. Automated systems were developed to download, recode and merge data for nearly real-time access by researchers. The systems were successfully rolled out and used by 1371 staff. A total of 25,089 pregnant women were enrolled, and 17,839 follow-up forms completed. Women’s group facilitators recorded 5717 women’s groups and the distribution of 14,647 food and 13,482 cash transfers. Using EDC sped up data collection and processing, although time needed for programming and set-up delayed the study inception. EDC using three interlinked mobile data management systems (FrontlineSMS, ODK and CommCare) was a feasible and effective method of data capture in a complex large-scale trial in the plains of Nepal. Despite challenges including prolonged set-up times, the systems met multiple data collection needs for users with varying levels of literacy and experience. |
format | Online Article Text |
id | pubmed-5496067 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-54960672017-07-11 Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal Style, Sarah Beard, B. James Harris-Fry, Helen Sengupta, Aman Jha, Sonali Shrestha, Bhim P. Rai, Anjana Paudel, Vikas Thondoo, Meelan Pulkki-Brannstrom, Anni-Maria Skordis-Worrall, Jolene Manandhar, Dharma S. Costello, Anthony Saville, Naomi M. Glob Health Action Study Design Article The increasing availability and capabilities of mobile phones make them a feasible means of data collection. Electronic Data Capture (EDC) systems have been used widely for public health monitoring and surveillance activities, but documentation of their use in complicated research studies requiring multiple systems is limited. This paper shares our experiences of designing and implementing a complex multi-component EDC system for a community-based four-armed cluster-Randomised Controlled Trial in the rural plains of Nepal, to help other researchers planning to use EDC for complex studies in low-income settings. We designed and implemented three interrelated mobile phone data collection systems to enrol and follow-up pregnant women (trial participants), and to support the implementation of trial interventions (women’s groups, food and cash transfers). 720 field staff used basic phones to send simple coded text messages, 539 women’s group facilitators used Android smartphones with Open Data Kit Collect, and 112 Interviewers, Coordinators and Supervisors used smartphones with CommCare. Barcoded photo ID cards encoded with participant information were generated for each enrolled woman. Automated systems were developed to download, recode and merge data for nearly real-time access by researchers. The systems were successfully rolled out and used by 1371 staff. A total of 25,089 pregnant women were enrolled, and 17,839 follow-up forms completed. Women’s group facilitators recorded 5717 women’s groups and the distribution of 14,647 food and 13,482 cash transfers. Using EDC sped up data collection and processing, although time needed for programming and set-up delayed the study inception. EDC using three interlinked mobile data management systems (FrontlineSMS, ODK and CommCare) was a feasible and effective method of data capture in a complex large-scale trial in the plains of Nepal. Despite challenges including prolonged set-up times, the systems met multiple data collection needs for users with varying levels of literacy and experience. Taylor & Francis 2017-06-14 /pmc/articles/PMC5496067/ /pubmed/28613121 http://dx.doi.org/10.1080/16549716.2017.1330858 Text en © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Study Design Article Style, Sarah Beard, B. James Harris-Fry, Helen Sengupta, Aman Jha, Sonali Shrestha, Bhim P. Rai, Anjana Paudel, Vikas Thondoo, Meelan Pulkki-Brannstrom, Anni-Maria Skordis-Worrall, Jolene Manandhar, Dharma S. Costello, Anthony Saville, Naomi M. Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal |
title | Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal |
title_full | Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal |
title_fullStr | Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal |
title_full_unstemmed | Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal |
title_short | Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal |
title_sort | experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern nepal |
topic | Study Design Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496067/ https://www.ncbi.nlm.nih.gov/pubmed/28613121 http://dx.doi.org/10.1080/16549716.2017.1330858 |
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