Process Mining for Capacity Planning and Reconfiguration of a Logistics System to Enhance the Intra-Hospital Patient Transport: Case Study

Intra-hospital patient transport (IHPT) service is one of the important contributors to efficiency in hospitals due to its high prevalence. The efficiency of this service is, in turn, dependent on proper planning of capacities and resources. Although there is extensive research focusing on improving capacity planning, there is little research available on posterior analysis of real-life executions of transport activities and evaluation methods. Therefore, this paper first provides a set of Key Performance Indicators to measure the efficiency of IHPT services using process mining approaches. Second, it conducts an extensive multidimensional analysis to support capacity planning by examining data containing various event- and case-specific information from IHPT process for a period of 42 months beginning from January 2019 in a German hospital. Different perspectives are considered to enable multidimensional analysis and provide insights regarding the behavior of different elements involved in the transport process. Daily and hourly assignments are evaluated to investigate transport capacities, activity intervals, automatically and manually dispatched assignments, as well as the most significant routes concerning transport delays. The analysis showed that 34.2% of the transports experienced delays of ten or more minutes. After identifying the causes of these delays and process bottlenecks, several technical and operational solutions are proposed, which are evaluated by domain experts in the case hospital. This paper shows the capability of process mining methods to provide holistic and clear insights into processes, which can help hospitals better understand the organization of their processes and address the challenges outlined in IHPT services.