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As data is being collected, it is important to conduct Quality Assurance (QA) to define the expected standards, such as data formats, codes, metadata and conduct Quality Control (QC) so that specific checks and tests are in place to detect poor quality data and address them through correction or appropriate documentation.
NIH Guidelines: https://www.ninds.nih.gov/current-research/research-funded-ninds/clinical-research/quality-assurance-guidelines
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