Handling missing data in large healthcare dataset: A case study of unknown trauma outcomes

Handling of missed data is one of the main tasks in data preprocessing especially in large public service datasets. We have analysed data from the Trauma Audit and Research Network (TARN) database, the largest trauma database in Europe. For the analysis we used 165,559 trauma cases. Among them, there are 19,289 cases (11.35%) with unknown outcome. We have demonstrated that these outcomes are not missed ‘completely at random’ and, hence, it is...