Joint modelling has gained attention in longitudinal studies incorporating biomarkers and survival data. In the context of chronic diseases, patient evolution is often tracked through multiple assessments, with patient-reported outcomes playing a crucial role. The Beta-Binomial distribution is suggested as a suitable model for these longitudinal variables. However, its integration into joint modelling remains unexplored. This study introduces an estimation procedure for analyzing longitudinal patient-reported outcomes and survival data together. We compare different estimation approaches through simulation experiments, including the proposed model. Furthermore, the methodologies are applied to real data from a follow-up study on chronic obstructive pulmonary disease patients.