Data management plan and REDCap mobile data capture for a multi-country Household Air Pollution Intervention Network (HAPIN) trial

Shirin Jabbarzadeh; Lindsay M Jaacks; Amy Lovvorn; Yunyun Chen; Jiantong Wang; Lisa Elon; Azhar Nizam; Vigneswari Aravindalochanan; Jean de Dieu Ntivuguruzwa; Kendra N Willams; Alexander Ramirez; Michael A Johnson; Ajay Pillarisetti; Thangavel Gurusamy; Ghislaine Rosa; Anaité Diaz-Artiga; Juan C Romero; Kalpana Balakrishnan; William Checkley; Jennifer L Peel; Thomas F Clasen; Lance A Waller

doi:10.1177/20552076241274217

Data management plan and REDCap mobile data capture for a multi-country Household Air Pollution Intervention Network (HAPIN) trial

Digit Health. 2024 Aug 21:10:20552076241274217. doi: 10.1177/20552076241274217. eCollection 2024 Jan-Dec.

Authors

Shirin Jabbarzadeh¹, Lindsay M Jaacks², Amy Lovvorn³, Yunyun Chen¹, Jiantong Wang¹, Lisa Elon¹, Azhar Nizam¹, Vigneswari Aravindalochanan⁴, Jean de Dieu Ntivuguruzwa⁵, Kendra N Willams⁶, Alexander Ramirez⁷, Michael A Johnson⁸, Ajay Pillarisetti⁹, Thangavel Gurusamy⁴, Ghislaine Rosa¹⁰, Anaité Diaz-Artiga⁷, Juan C Romero⁷, Kalpana Balakrishnan⁴, William Checkley¹¹, Jennifer L Peel¹², Thomas F Clasen³, Lance A Waller¹

Affiliations

¹ Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
² Global Academy of Agriculture and Food Systems, University of Edinburgh, Edinburgh, UK.
³ Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
⁴ Department of Environmental Health Engineering, Sri Ramachandra Institute for Higher Education and Research (Deemed University), Chennai, India.
⁵ Eagle Research Centre Limited, Kigali, Rwanda.
⁶ Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁷ Center for Health Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala.
⁸ Berkeley Air Monitoring Group, Berkeley, CA, USA.
⁹ Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA.
¹⁰ University of Liverpool, Liverpool, England.
¹¹ Center for Global Non-Communicable Disease Research and Training, School of Medicine, Johns Hopkins University, Baltimore, MA, USA.
¹² Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA.

Abstract

Background: Household air pollution (HAP) is a leading environmental risk factor accounting for about 1.6 million premature deaths mainly in low- and middle-income countries (LMICs). However, no multicounty randomized controlled trials have assessed the effect of liquefied petroleum gas (LPG) stove intervention on HAP and maternal and child health outcomes. The Household Air Pollution Intervention Network (HAPIN) was the first to assess this by implementing a common protocol in four LMICs.

Objective: This manuscript describes the implementation of the HAPIN data management protocol via Research Electronic Data Capture (REDCap) used to collect over 50 million data points in more than 4000 variables from 80 case report forms (CRFs).

Methods: We recruited 800 pregnant women in each study country (Guatemala, India, Peru, and Rwanda) who used biomass fuels in their households. Households were randomly assigned to receive LPG stoves and 18 months of free LPG supply (intervention) or to continue using biomass fuels (control). Households were followed for 18 months and assessed for primary health outcomes: low birth weight, severe pneumonia, and stunting. The HAPIN Data Management Core (DMC) implemented identical REDCap projects for each study site using shared variable names and timelines in local languages. Field staff collected data offline using tablets on the REDCap Mobile Application.

Results: Utilizing the REDCap application allowed the HAPIN DMC to collect and store data securely, access data (near real-time), create reports, perform quality control, update questionnaires, and provide timely feedback to local data management teams. Additional REDCap functionalities (e.g. scheduling, data validation, and barcode scanning) supported the study.

Conclusions: While the HAPIN trial experienced some challenges, REDCap effectively met HAPIN study goals, including quality data collection and timely reporting and analysis on this important global health trial, and supported more than 40 peer-reviewed scientific publications to date.

Keywords: Data collection; HAPIN; REDCap; REDCap mobile app; data management; digital data capture; household air pollution; multi-country.

Abstract

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