Unmeasured Confounding

What is unmeasured confounding? 

Unmeasured confounding occurs when an unaccounted-for variable affects both the treatment or exposure of interest and the outcome in a study, leading to a biased estimate of the relationship between the treatment and the outcome. This type of confounding can distort the apparent effects of an intervention, making it appear more or less effective than it truly is. Unmeasured confounding is especially problematic in observational studies and real-world evidence (RWE) research, where researchers do not have control over all potential confounding factors. 

Why is unmeasured confounding important? 

Unmeasured confounding is a critical issue in observational research because it can lead to biased conclusions that affect decision-making in healthcare, policy, and business. Researchers must be vigilant in considering the potential for unmeasured confounding and take steps to reduce its impact, whether through careful study design, advanced statistical techniques, or alternative research methods.