• process mining
• Covid-19
• business process management
• healthcare
• comparative analysis

The main goal of this work was to develop a methodology that could support the conduct of a comparative analysis in the healthcare domain using process mining tools. The data analysed in the thesis refer to the treatment of COVID-19 patients at the Uniklinik hospital in Aachen. The work consists of three main analyses. Process discovery algorithms aim to obtain process models for each wave of the pandemic, which can then be compared with each other in order to highlight differences in the workflow. Through conformance checking techniques it is possible to compare the data of each wave with the normative model representing the clinical guidelines for COVID-19 treatment, in order to identify deviations between the expected behaviour and the actual behaviour of the process. A set of Key Performance Indicators is created to analyse the performances of the hospital. Major changes were found to be in the management of the Intensive Care Unit, the use of respiratory support techniques, and drug administration. The comparative methodology is able to give precise and data-driven information about various aspects of the clinical process and can be applied with flexibility to several Covid and non-Covid contexts.