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Data management for large community trials in Nepal
E K Pradhan1, J Katz, S C LeClerq
1Dana Center for Preventive Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Controlled Clinical Trials
|June 1, 1994
Summary
A robust data management system was developed for a large community trial in Nepal, ensuring high-quality data collection and analysis for vitamin A supplementation research.
Area of Science:
- Public Health
- Clinical Trials
- Data Management
Background:
- Resource-poor settings present unique challenges for community-based trial data management.
- Advancements in hardware and software enable sophisticated data systems even in remote locations.
Purpose of the Study:
- To design, implement, and operate an effective data management system for the Nepal Nutrition Intervention Project Sarlahi (NNIPS).
- To assess the impact of vitamin A supplementation on preschool mortality in 38,000 children.
Main Methods:
- Established a central data center in Kathmandu, Nepal.
- Implemented a multi-stage data error correction process involving field workers, supervisors, and editors.
- Utilized extensive computerized data checking during entry, achieving low error rates (3.1/10,000 keystrokes).
Main Results:
- Processed over 200,000 forms with a data entry error rate of only 1% for out-of-range, missing, or inconsistent data.
- Successfully identified and corrected the majority of data discrepancies at the field level.
- Provided timely data analysis for project oversight and publication.
Conclusions:
- High-quality data management systems are feasible and effective in resource-poor environments for community-based trials.
- The developed system facilitated the successful completion of a large-scale vitamin A supplementation trial.
- The system ensured data integrity, supporting reliable analysis and reporting of trial outcomes.