Who should use the Generate real-world evidence workflow?
Teams or solo builders working on science & healthcare tasks who want a repeatable process instead of one-off tool experiments.
Execution Map
3-step pipeline — follow each step in order
1Setup · Step 1 of 3
Open task pageLiterature review for RWE study design
Summarize existing research papers to identify knowledge gaps and inform the design of the real-world evidence study, ensuring a solid scientific foundation.
Why this matters
A thorough literature review prevents duplication and guides the selection of appropriate data sources and methods for RWE generation.
What you get
A concise summary of key findings and gaps is produced, ready to inform the next steps.
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2Input · Step 2 of 3
Open task pageAnalyze real-world clinical data
Extract and analyze real-world data from electronic health records or other clinical databases to prepare structured datasets for evidence generation.
Why this matters
High-quality data analysis is critical for generating reliable real-world evidence; this step transforms raw data into analyzable formats.
What you get
Cleaned and structured datasets are ready for the core evidence generation step.
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3Deliver · Step 3 of 3
Open task pageProduce real-world evidence
Apply statistical and analytical methods to the prepared dataset to generate real-world evidence, such as treatment effectiveness or safety outcomes.
Why this matters
This is the core step where actionable evidence is created, directly addressing the research question.
What you get
A comprehensive real-world evidence report is generated, ready for review and dissemination.
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