Learning from coding data-surgical treatment of benign prostatic syndrome : Big data for BPS

Abstract

Benign prostatic syndrome (BPS) is one of the most common urological diseases. Currently, there are numerous surgical methods to treat BPS. The digitalisation of medicine enables new study approaches in healthcare research using digital data from individual treatment pathways. In the present work, BPS-specific longitudinal trend analyses were performed. Treatment-related figures, both with regard to the therapy methods and predefined patient cohorts, could be examined after validating the datasets. This meant that information on relevant characteristics of surgical BPS treatment could be read and calculations made that reflect the overall impact of these processes. In the future, it is expected that increasingly comprehensive, higher-quality digital datasets on different clinical pictures will be available for analytical purposes. Intensification of research projects in this field is desirable. The results thus obtained enable further optimisation steps of certain treatment actions and provide important key figures for the strategy development of amedical facility.