In reliability theory, the lifetime remaining in a network of components after an initial run-in period is an important property of the system. Similarly, for medical interventions residual survival characterizes the subsequent experience of patients who survive beyond the beginning of follow-up. Here we show how quantiles of the residual survival distribution can be used to provide such a characterization. We first discuss properties of the residual quantile function and its close relationship to the hazard function.We then consider parametric estimation of the residual quantile function, focusing on the generalized gamma distribution. Finally, we describe an application of quantiles of residual survival to help describe the effects at the population level of the introduction and sustained use of highly active antiretroviral therapy for the treatment of HIV/AIDS.