Collection, Processing and Analysis of Heterogeneous Data Coming from Spanish Hospitals in the Context of COVID-19.

The COVID-19 pandemic has already caused more than 150,000,000 cases worldwide. In Spain this has lead to a massive and simultaneous saturation of all sanitary regions. Coherently, the quick and consistent understanding of the COVID-19 disease requires of the combined analysis of thousands of medical records generated by dozens of different institutions. In the context of the publicly funded CIBERES-UCI-COVID project, we have gathered, cleaned and preprocessed data from heterogeneous sources - more than 30 hospitals, with different data entry systems - in order to produce a unified database, of more than 6.000 patients, that is used in several clinical studies being carried by different multi-disciplinary groups. In this paper, we identify the complexities we encountered, the solutions we applied, and we summarise the statistical and machine learning techniques we have applied for the studies.