Analysis of Patient Treatment Procedures

Abstract

A real-life event log, taken from a Dutch Academic Hospital, provided for the BPI challenge is analyzed using process mining techniques. The log contains events related to treatment and diagnosis steps for patients diagnosed with cancer. Given the heterogeneous nature of these cases, we first demonstrate that it is possible to create more homogeneous subsets of cases (e.g., patients having a particular type of cancer that need to be treated urgently). Such preprocessing is crucial given the variation and variability found in the event log. The discovered homogeneous subsets are analyzed using state-of-the-art process mining approaches. More specifically, we report on the findings discovered using enhanced fuzzy mining and trace alignment. A dedicated preprocessing ProM plug-in was developed for this challenge. The analysis was done using recent, but pre-existing, ProM plug-ins. The high-level view of our approach is depicted in Fig. 1. Using this approach we are able to uncover many interesting findings that could be used to improve the underlying care processes.