Clinimetrics corner: a closer look at the minimal clinically important difference (MCID)

Abstract

Minimal clinically important difference (MCID) scores are commonly used by clinicians when determining patient response to treatment and to guide clinical decision-making during the course of treatment. For research purposes, the MCID score is often used in sample size calculations for adequate powering of a study to minimize the false-positives (type 1 errors) and the false-negatives (type 2 errors). For clinicians and researchers alike, it is critical that the MCID score is a valid and stable measure. A low MCID value may result in overestimating the positive effects of treatment, whereas a high MCID value may incorrectly classify patients as failing to respond to treatment when in fact the treatment was beneficial. The wide range of methodologies for calculating the MCID score results in varied outcomes, which leads to difficulties with interpretation and application. This clinimetrics corner outlines key factors influencing MCID estimates and discusses limitations with the use of the MCID in both clinical and research practice settings.