Providing hospitals with richer insights in their processes: an enhanced methodology for data-driven root-cause analysis using an improved event log (Research)
Hospitals are becoming increasingly aware of the need to improve their business processes to tackle challenges such as tightening budgets and an aging population. To focus process improvement initiatives, challenging questions such as "why is the flow time so high for a group of patients?" need to be answered. Root-cause analysis can be used to answer such questions as it aims to find explanations for problems, e.g. related to flow time. To find these explanations, data-driven root-cause analysis is promising as it enables studying a large number of patients using readily available data. This data originates from the hospital information system, which automatically records process execution information in event logs. Unfortunately, current state-of-the-art on data-driven root-cause analysis fails to reach its full potential because it suffers from two fundamental limitations: (1) the presence of data quality issues in real-life event logs and (2) hiatuses of existing approaches to perform data-driven root-cause analysis. The proposed research aims to tackle both limitations by (1) introducing a methodology to improve existing event logs using indoor location data and (2) introducing an enhanced methodology to support datadriven root-cause analysis. However, this requires overcoming several research challenges, which will lead to innovative results and fundamental contributions to literature.
Period of project
01 October 2019 - 30 September 2022