What methodological step is vital for RWD before drawing meaningful, unbiased RWE conclusions?
Answer
Significant cleaning and standardization
Because Real-World Data (RWD) was not initially collected specifically for a defined research question, extracting reliable Real-World Evidence (RWE) requires substantial methodological rigor before any analysis can commence. This rigor necessitates careful evaluation to ensure the RWD is fit for the intended purpose. A critical prerequisite step involves extensive data cleaning—correcting errors, handling missing entries—and standardization processes, which ensure consistency across different data formats or systems, allowing researchers to combine disparate datasets reliably and minimize the risk of drawing conclusions based on artifacts or inconsistencies within the raw observational data.
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