Framework for Exploration of Statistical Heterogeneity in Multi-Database Studies: A Case Study Using EXACOS-CV Studies

Multi-database studies are a powerful way to understand healthcare outcomes across different populations and systems. Yet, even when researchers follow a common protocol, results can differ more than expected by chance—a phenomenon known as statistical heterogeneity. This variation can reflect differences in study design, database coding, healthcare practices, or real clinical differences between populations.

Research challenge

Despite using harmonized study protocols, the multi-database EXACOS-CV (EXAcerbations of COPD and their outcomeS on CardioVascular diseases) program spanning Germany, Canada, Spain, and the Netherlands revealed striking differences in the strength of associations between chronic obstructive pulmonary disease (COPD) exacerbations and cardiovascular outcomes. For example, the adjusted hazard ratio (aHR) for decompensated heart failure in the 1–7 days post-exacerbation ranged from 2.6 in Germany to 72.3 in Canada; all-cause mortality ranged from 3.5 in the Netherlands to 22.1 in Spain.