In survival analysis the random censorship model refers to censoring and survival times being independent of each other. It is one of the fundamental assumptions in the theory of survival analysis. We explain the reason for it being so ubiquitous, and we investigate its presence in medical studies. We differentiate two types of censoring in medical studies (dropout and administrative), and we explain their importance in examining the existence of the random censorship model. We show that in order to presume the random censorship model it is not enough to have a design study which conforms to it, but that one needs to provide evidence for its presence in the results. Blindly presuming the random censorship model might lead to the Kaplan-Meier estimator producing biased results, which might have serious consequences when estimating survival in medical studies.