Title: Enhancing Hospital Process Management via Process Mining: An Analysis of COVID-19 Clinical Pathways

Abstract:

This research utilizes the COVID Data for Shared Learning dataset to examine care pathways associated with COVID-19. We developed a transparent and reproducible workflow designed to convert disparate clinical data tables into event logs suitable for process mining. This approach incorporates discovery techniques, declarative conformance checking, and outcome analysis. The resulting reconstructed pathways reveal the central role of monitoring in inpatient care, significant variability at the interface between the Emergency Department and admission, and outcome variations linked to patient age and exposure to intensive care units. These findings demonstrate the utility of process mining in supporting evidence-based hospital governance by informing strategies for triage standardization, capacity planning, and the coordination of patient transitions from intensive care to lower-acuity wards.

Source: arXiv Generated at: 2026-06-02 00:00:00 UTC