Multi-perspective process mining for emergency process

Multi-perspective process mining is an analytical approach that uses data to gain objective insights and uncover hidden problems in business processes from multiple perspectives.

In this paper, we apply multi-perspective process mining techniques in the emergency process through a goal-driven performance evaluation method in order to understand and diagnose the timeliness of the emergency process.

Unstructured and multi-disciplinary emergency data is analyzed by following Goal-Question-Feature-Indicator (GQFI) method. In this paper, the GQFI method is extended with perspectives, and the insights in the enriched event data are examined by a decision tree model. All of them are applied in a systematic way in relation to the goal of assessing and improving the emergency process in a university hospital.

We detected the deviations (e.g., skipping the triage and consultation request steps) and two bottlenecks in the emergency process. Among the suggestions for improving the process, are performing defensive medicine in a harmless manner, classification of the emergency services, ensuring triage step is applied to all patients and effective usage of the call system application in consultation activities.

The results of this study showed that goal-oriented multi-perspective process mining is effective in identifying process improvements in emergency services.