TY - JOUR
T1 - Data Management in Multicountry Consortium Studies
T2 - The Enterics For Global Health (EFGH) Shigella Surveillance Study Example
AU - Feutz, Erika
AU - Biswas, Prasanta K.
AU - Ndeketa, Latif
AU - Ogwel, Billy
AU - Onwuchekwa, Uma
AU - Sarwar, Golam
AU - Sultana, Shazia
AU - Yori, Pablo Peñataro
AU - Acebedo, Alyssa
AU - Ahmed, Naveed
AU - Ahmed, Imran
AU - Atlas, Hannah E.
AU - Awuor, Alex O.
AU - Bhuiyan, Md Amirul Islam
AU - Conteh, Bakary
AU - Diawara, Oualy
AU - Elwood, Sarah
AU - Fane, Moussa
AU - Hossen, Md Ismail
AU - Ireen, Mahzabeen
AU - Jallow, Abdoulie F.
AU - Karim, Mehrab
AU - Kosek, Margaret N.
AU - Kotloff, Karen L.
AU - Lefu, Clement
AU - Liu, Jie
AU - Maguire, Rebecca
AU - Qamar, Farah Naz
AU - Ndalama, Maureen
AU - Ochieng, John Benjamin
AU - Okonji, Caleb
AU - Paredes, Loyda Fiorella Zegarra
AU - Pavlinac, Patricia B.
AU - Perez, Karin
AU - Qureshi, Sonia
AU - Schiaffino, Francesca
AU - Traore, Moussa
AU - Tickell, Kirkby D.
AU - Wachepa, Richard
AU - Witte, Desiree
AU - Cornick, Jennifer
AU - Jahangir Hossain, M.
AU - Khanam, Farhana
AU - Olortegui, Maribel Paredes
AU - Omore, Richard
AU - Sow, Samba O.
AU - Yousafzai, Mohammad Tahir
AU - Galagan, Sean R.
N1 - Publisher Copyright:
© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.
PY - 2024/3/1
Y1 - 2024/3/1
N2 - 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.
AB - 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.
KW - clinical research
KW - consortium studies
KW - data management
KW - data quality
KW - population enumeration
UR - http://www.scopus.com/inward/record.url?scp=85188801777&partnerID=8YFLogxK
U2 - 10.1093/ofid/ofad573
DO - 10.1093/ofid/ofad573
M3 - Article
AN - SCOPUS:85188801777
SN - 2328-8957
VL - 11
SP - S48-S57
JO - Open Forum Infectious Diseases
JF - Open Forum Infectious Diseases
IS - Supplement_1
ER -