Evaluating center-specific long-term outcomes through differences in mean survival time: Analysis of national kidney transplant data

Center-specific survival outcomes of kidney transplant recipients are an important quality measure, with several challenges. Existing methods based on restricted mean lifetime tend to focus on short- and medium-term clinical outcomes and may fail to capture long-term effects associated with quality of follow-up care. In this report, we propose methods that combine a lognormal frailty model and piecewise exponential baseline rates to compare the mean survival time across centers. The proposed methods allow for the consistent estimation of mean survival time as opposed to restricted mean lifetime and, within this context, permits more accurate profiling of long-term center-specific outcomes. Asymptotic properties of the proposed estimators are derived, and finite-sample properties are examined through simulation. The proposed methods are then applied to national kidney transplant data. The novelty of the proposed techniques arises from several angles. We utilize mean survival, in contrast to the most previous works that considered the restricted mean. Few previous studies have used the integrated survival function as a basis for center effects. Few provider profiling methods use a random effects model to estimate fixed center effects.