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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal for healthcare quality : official publication of the National Association for Healthcare Quality
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
