» Articles » PMID: 38532952

Data Management in Multicountry Consortium Studies: The Enterics For Global Health (EFGH) Surveillance Study Example

Abstract

Background: Rigorous data management systems and planning are essential to successful research projects, especially for large, multicountry consortium studies involving partnerships across multiple institutions. Here we describe the development and implementation of data management systems and procedures for the Enterics For Global Health (EFGH) surveillance study-a 7-country diarrhea surveillance study that will conduct facility-based surveillance concurrent with population-based enumeration and a health care utilization survey to estimate the incidence of -associated diarrhea in children 6 to 35 months old.

Methods: The goals of EFGH data management are to utilize the knowledge and experience of consortium members to collect high-quality data and ensure equity in access and decision-making. During the planning phase before study initiation, a working group of representatives from each EFGH country site, the coordination team, and other partners met regularly to develop the data management systems for the study.

Results: This resulted in the Data Management Plan, which included selecting REDCap and SurveyCTO as the primary database systems. Consequently, we laid out procedures for data processing and storage, study monitoring and reporting, data quality control and assurance activities, and data access. The data management system and associated real-time visualizations allow for rapid data cleaning activities and progress monitoring and will enable quicker time to analysis.

Conclusions: Experiences from this study will contribute toward enriching the sparse landscape of data management methods publications and serve as a case study for future studies seeking to collect and manage data consistently and rigorously while maintaining equitable access to and control of data.

Citing Articles

Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms.

Ogwel B, Mzazi V, Awuor A, Okonji C, Anyango R, Oreso C BMC Med Inform Decis Mak. 2025; 25(1):28.

PMID: 39815316 PMC: 11737202. DOI: 10.1186/s12911-025-02855-6.


Predictive modelling of linear growth faltering among pediatric patients with Diarrhea in Rural Western Kenya: an explainable machine learning approach.

Ogwel B, Mzazi V, Awuor A, Okonji C, Anyango R, Oreso C BMC Med Inform Decis Mak. 2024; 24(1):368.

PMID: 39623435 PMC: 11613762. DOI: 10.1186/s12911-024-02779-7.


Optimizing Vaccine Trials for Enteric Diseases: The Enterics for Global Health (EFGH) Surveillance Study.

Vannice K, MacLennan C, Long J, Steele A Open Forum Infect Dis. 2024; 11(Suppl 1):S1-S5.

PMID: 38532964 PMC: 10962720. DOI: 10.1093/ofid/ofad586.


Detection and Molecular Serotyping With a Customized TaqMan Array Card in the Enterics for Global Health (EFGH): Surveillance Study.

Liu J, Garcia Bardales P, Islam K, Jarju S, Juma J, Mhango C Open Forum Infect Dis. 2024; 11(Suppl 1):S34-S40.

PMID: 38532960 PMC: 10962731. DOI: 10.1093/ofid/ofad574.

References
1.
Harris P, Taylor R, Thielke R, Payne J, Gonzalez N, Conde J . Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2008; 42(2):377-81. PMC: 2700030. DOI: 10.1016/j.jbi.2008.08.010. View

2.
Meiring J, Gibani M . The Typhoid Vaccine Acceleration Consortium (TyVAC): Vaccine effectiveness study designs: Accelerating the introduction of typhoid conjugate vaccines and reducing the global burden of enteric fever. Report from a meeting held on 26-27 October 2016,.... Vaccine. 2017; 35(38):5081-5088. DOI: 10.1016/j.vaccine.2017.08.001. View

3.
Harris P, Delacqua G, Taylor R, Pearson S, Fernandez M, Duda S . The REDCap Mobile Application: a data collection platform for research in regions or situations with internet scarcity. JAMIA Open. 2021; 4(3):ooab078. PMC: 8435658. DOI: 10.1093/jamiaopen/ooab078. View

4.
Conteh B, Badji H, Jallow A, Karim M, Manneh A, Keita B . The Enterics for Global Health (EFGH) Surveillance Study in The Gambia. Open Forum Infect Dis. 2024; 11(Suppl 1):S84-S90. PMC: 10962724. DOI: 10.1093/ofid/ofae049. View

5.
Wilkinson M, Dumontier M, Aalbersberg I, Appleton G, Axton M, Baak A . The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016; 3:160018. PMC: 4792175. DOI: 10.1038/sdata.2016.18. View