Real-world data (RWD), gathered from everyday clinical practice creates real-world evidence (RWE) that supports decision-making for regulatory bodies, health technology assessment (HTA) bodies, and payers. To enhance the value of RWD for decision making, diverse data and methods across various jurisdictions are employed for a more accurate outcome assessment. This diversity introduces variability or heterogeneity in study outcomes, posing interpretation. This session delves into the sources of heterogeneity and strategies to address it. Speakers will discuss how differences in RWD and data from different healthcare settings influence variation between estimates and explore designs and statistical methods to assess and minimize this variability.