Methods for analyzing rates of events such as heart valve failure following surgery are important for comparing different techniques and devices; however, in patients undergoing major surgery, other risks such as mortality compete with the risk of heart valve failure to determine each patient's final outcome. When multiple, mutually exclusive endpoints are possible, a situation known to statisticians as a competing risks problem arises. No single statistical technique that is currently available provides an entirely satisfactory solution to this problem. We argue that in order for valve failure incidences to be useful clinically, the overall patient outcome milieu from which these failures arise must be considered. In this article, we review recent work in the area of competing-risks analysis as it pertains to heart valve surgery outcome.