Extracting Alarm Events from the MIMIC-III Clinical Database

Lack of readily available data on ICU alarm events constitutes a major obstacle to alarm fatigue research. There are ICU databases available that aim to give a holistic picture of everything happening at the respective ICU. However, these databases do not contain data on alarm events. We utilise the vital parameters and alarm thresholds recorded in the MIMIC-III database in order to artificially extract alarm events from this database. Prior to that, we uncover, investigate, and mitigate inconsistencies we found in the data. The results of this work are an approach and an algorithm for cleaning the alarm data available in MIMIC-III and extract concrete alarm events from them. The data set generated by this algorithm is investigated in this work and can be used for further research into the problem of alarm fatigue.