Evaluating the Statistical Significance of Health-Related Quality-Of-Life Change in Individual Patients

Abstract

Assessing individual change is feasible and potentially useful in clinical practice. This article provides an overview of the evaluation of statistically significant change in health-related quality of life (HRQOL) for individual patients. We review the standard error of measurement, standard error of prediction, and reliable change indices using a sample of 54 patients receiving care at the UCLA Center for East-West Medicine. The largest amount of change necessary for statistical significance was found for the reliable change index and the smallest change was needed for the standard error of measurement. The amount of change required for statistical significance was intermediate for the standard error of prediction. The median kappa for classifying change (declined, stayed the same, improved) by different indices was .82, indicating a high level of agreement. Future research is needed to determine if one index is most appropriate for evaluating the significance of individual change.