ABSTRACT
Survival analysis is used in a wide variety of research settings to maximize the information extracted from a group of timed observations. Measures employed in continuous quality improvement (CQI) efforts often involve such observations. Yet to date, survival analysis has not been widely used to guide CQI efforts. This article presents the features of survival analysis that are most applicable to CQI efforts and illustrates the application of these techniques to a quality improvement project focused on diabetic kidney disease. Results are compared with those from a "standard" analysis. The interpretation of results is discussed in the context of constraints typical of CQI efforts. The article concludes with a recommendation for broader application of this valuable analytic methodology.
