This paper presents a method to choose the threshold for dichotomization of survival outcomes in a structured fashion based on data analysis. The method is illustrated with an application to the prediction problem of the outcome length of stay at Intensive Care Unit (ICU LOS). Threshold selection is based on comparing the calibration of predictive models for dichotomized outcomes with increasing threshold values. To quantify model calibration a measure insensitive to class unbalance is used. The threshold value for which the associated predictive model has superior calibration is selected, and the corresponding model is used in practice. Using this method to select the threshold for ICU LOS, the best model calibration is found at a threshold of five days.