Control-flow analysis of procedural skills competencies in medical training through process mining

Abstract

Background. Procedural skills are key to good clinical results, and training in them involves a significant amount of resources. Control-flow analysis (ie, the order in which a process is performed) can provide new information for those who train and plan procedural training. This study outlines the steps required for control-flow analysis using process mining techniques in training in an ultrasound-guided internal jugular central venous catheter placement using a simulation.Methods. A reference process model was defined through a Delphi study, and execution data (event logs) were collected from video recordings from pretraining (PRE), post-training (POST) and expert (EXP) procedure executions. The analysis was performed to outline differences between the model and executions. We analysed rework (activity repetition), alignment-based fitness (conformance with the ideal model) and trace alignment analysis (visual ordering pattern similarities).Results. Expert executions do not present repetition of activities (rework). The POST rework is lower than the PRE, concentrated in the steps of the venous puncture and guidewire placement. The adjustment to the ideal model measure as alignment-based fitness, expressed as a median (25th–75th percentile) of PRE 0.74 (0.68–0.78) is less than POST 0.82 (0.76–0.86) and EXP 0.87 (0.82–0.87). There are no significant differences between POST and EXP. The graphic analysis of alignment and executions shows a progressive increase in order from PRE to EXP executions.Conclusion. Process mining analysis is able to pinpoint more difficult steps, assess the concordance between reference mode and executions, and identify control-flow patterns in procedural training courses.