Evaluation of patient transport service in hospitals using process mining methods: Patients' perspective

Designing healthcare facilities and their processes is a complex task which influences the quality and efficiency of healthcare services. The ongoing demand for healthcare services and cost burdens necessitate the application of analytical methods to enhance the overall service efficiency in hospitals. However, the variability in healthcare processes makes it highly complicated to accomplish this aim. This study addresses the complexity in the patient transport service process at a German hospital, and proposes a method based on process mining to obtain a holistic approach to recognise bottlenecks and main reasons for delays and resulting high costs associated with idle resources. To this aim, the event log data from the patient transport software system is collected and processed to discover the sequences and the timeline of the activities for the different cases of the transport process. The comparison between the actual and planned processes from the data set of the year 2020 shows that, for example, around 36% of the cases were 10 or more minutes delayed. To find delay issues in the process flow and their root causes the data traces of certain routes are intensively assessed. Additionally, the compliance with the predefined Key Performance Indicators concerning travel time and delay thresholds for individual cases was investigated. The efficiency of assignment of the transport requests to the transportation staff are also evaluated which gives useful understanding regarding staffing potential improvements. The research shows that process mining is an efficient method to provide comprehensive knowledge through process models that serve as Interactive Process Indicators and to extract significant transport pathways. It also suggests a more efficient patient transport concept and provides the decision makers with useful managerial insights to come up with efficient patient‐centred analysis of transportation services through data from supporting information systems.