Deconstructing Central Rating In Clinical Trials | Part I

By Juliet Brown, PhD; Joan Busner, PhD; Daniela Chereches; MD, MBA; & Margot Oakley, RN, MSN

Central Rating is used as a method to improve data quality and success rates in clinical trials by addressing the prevalent issue of trial failures. This entails utilizing a centralized team of external raters, managed independently, to remotely administer and score diagnostic or severity scales. This approach significantly reduces biases linked to site raters, including enrollment, expectation, confirmation, framing, attribution, anchoring, and trajectory biases.

By keeping raters detached from site incentives and blind to protocol specifics, Central Rating ensures greater objectivity, especially in trials with significant treatment effects. This strategy not only minimizes cognitive biases but also decreases data error variance through the use of a small group of highly trained raters, thus reducing inter-rater variability. It is particularly beneficial for studies that lack experienced site raters, such as those involving rare diseases. Learn more about these and other advantages of Central Rating that will collectively enhance your data quality.