✔ Why “index date” is more complicated than it sounds

✔ Common mistakes around exposure definitions

✔ The importance of understanding how RWE data is generated

✔ What programmers should know about timing, variables, and algorithms

✔ Why project management in RWE must be iterative and stakeholder-driven

✔ Key terminology pitfalls that can trip up even experienced professionals

✔ How data issues like duplicates, implausible values, and partial dates impact analyses

✔ Best practices for communication, timelines, and managing expectations in RWE projects

If you're working in real-world evidence or thinking of transitioning from clinical trials, this episode is packed with practical advice to help you avoid common mistakes and set your projects up for success. Rachel shares from her own hands-on experience—starting from data management and programming to leading statistical analyses in RWE. Alexander and Rachel also highlight real-world data quirks that no textbook prepares you for, making this episode an essential resource for statisticians, data scientists, and healthcare researchers alike.

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If you’re working on evidence generation plans or preparing for joint clinical advice, this episode is packed with insights you don’t want to miss.

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