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Feutz, Erika, Biswas, Prasanta K, Ndeketa, Latif, Ogwel, Billy, Onwuchekwa, Uma, Sarwar, Golam, Sultana, Shazia, Peñataro Yori, Pablo, Acebedo, Alyssa, Ahmed, Naveed, Ahmed, Imran, Atlas, Hannah E, Awuor, Alex O, Bhuiyan, Md Amirul Islam, Conteh, Bakary, Diawara, Oualy, Elwood, Sarah, Fane, Moussa, Hossen, Md Ismail, Ireen, Mahzabeen, Jallow, Abdoulie F, Karim, Mehrab, Kosek, Margaret N, Kotloff, Karen L, Lefu, Clement, Liu, Jie, Maguire, Rebecca, Qamar, Farah Naz, Ndalama, Maureen, Ochieng, John Benjamin, Okonji, Caleb, Paredes, Loyda Fiorella Zegarra, Pavlinac, Patricia B, Perez, Karin, Qureshi, Sonia, Schiaffino, Francesca, Traore, Moussa, Tickell, Kirkby D, Wachepa, Richard, Witte, Desiree, Cornick, Jennifer, Jahangir Hossain, M, Khanam, Farhana, Olortegui, Maribel Paredes, Omore, Richard, Sow, Samba O, Yousafzai, Mohammad Tahir and Galagan, Sean R (2024) 'Data Management in Multicountry Consortium Studies: The Enterics For Global Health (EFGH) Shigella Surveillance Study Example'. Open Forum Infectious Diseases, Vol 11, Issue Supplement_1, S48-S57.
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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) Shigella 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 Shigella-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.
| Item Type: | Article |
|---|---|
| Subjects: | WA Public Health > Health Administration and Organization > WA 530 International health administration WA Public Health > Statistics. Surveys > WA 950 Theory or methods of medical statistics. Epidemiologic methods |
| Faculty: Department: | Clinical Sciences & International Health > Clinical Sciences Department |
| Digital Object Identifer (DOI): | https://doi.org/10.1093/ofid/ofad573 |
| SWORD Depositor: | JISC Pubrouter |
| Depositing User: | JISC Pubrouter |
| Date Deposited: | 28 Mar 2024 11:49 |
| Last Modified: | 28 Mar 2024 11:54 |
| URI: | https://archive.lstmed.ac.uk/id/eprint/24261 |
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