Analyzing PACS Usage Patterns by Means of Process Mining: Steps Toward a More Detailed Workflow Analysis in Radiology.

In this paper, statistical analysis and techniques from process mining are employed to analyze interaction patterns originating from radiologists reading medical images in a picture archiving and communication system (PACS). Event logs from 1 week of data, corresponding to 567 cases of single-view chest radiographs read by 14 radiologists, were analyzed. Statistical analysis showed that the numbers of commands and command types used by the radiologists per case only have a slightly positive correlation with the time to read a case (0.31 and 0.55, respectively). Further, one way ANOVA showed that the factors time of day, radiologist and specialty were significant for the number of commands per case, whereas radiologist was also significant for the number of command types, but with no significance of any of the factors on time to read. Applying process mining to the event logs of all users showed that a seemingly "simple" examination (single-view chest radiographs) can be associated with a highly complex interaction process. However, repeating the process discovery on each individual radiologist revealed that the initially discovered complex interaction process consists of one group of radiologists with individually well-structured interaction processes and a second smaller group of users with progressively more complex usage patterns. Future research will focus on metrics to describe derived interaction processes in order to investigate if one set of interaction patterns can be considered as more efficient than another set when reading radiological images in a PACS.