We propose a hierarchical discrete time survival model to analyse registry data on haemodialysis patients in Rio de Janeiro, Brazil, collected at different dialysis centres. Our aim is to estimate differences in hazard ratios attributable to variation in dialysis centre performance, after adjusting for further observed covariates both at the individual and centre level. The proposed model allowed for the estimation of a residual calendar time trend varying across dialysis centres through the adoption of a random slope model. These calendar time trends turned out to have significant variation, after adjustment for important observed covariates. The technique can be easily adapted to other diseases as long as survival time is the measurement of interest.
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