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High quality standards for a large-scale prospective population-based observational cohort: Constances
Fabrice Ruiz1, Marcel Goldberg2, Sylvie Lemonnier2
1CLINSEARCH, 110 Avenue Pierre Brossolette, 92240, Malakoff, France. fabrice.ruiz@clinsearch.net.
BMC Public Health
|August 26, 2016
Summary
Implementing robust quality control in the Constances cohort, a large population-based study, ensured accurate data collection. This comprehensive quality management process improved measurement accuracy and prevented data drift across multiple sites.
Area of Science:
- Epidemiology
- Public Health Research
- Biostatistics
Background:
- Long-term multicenter studies face challenges to data integrity.
- Quality control and data standardization are vital for minimizing bias in population-based cohorts.
- Publication of bias management tools in cohort studies is infrequent.
Purpose of the Study:
- To detail bias control processes in the Constances cohort.
- To use lung function measurements as a case study for quality management.
Main Methods:
- The Constances cohort involves 200,000 participants with 5-year follow-ups.
- Standard Operating Procedures (SOPs) govern medical device specifications and measurement methods.
- On-site inspections and database controls assess protocol deviations.
Main Results:
- Participating centers adapted practices to study specifications.
- Medical device distributors adhered to international and cohort requirements.
- Spirometry acceptability rates doubled, and global repeatability reached 96.7% for 29,772 maneuvers.
Conclusions:
- Significant resource investment in quality management proved effective.
- Continuous quality management prevents data drift and enhances accuracy.
- This approach ensures data integrity despite heterogeneous materials and multiple study sites.