Improving Hospital Process Management through Process Mining: A Case Study on COVID-19 Clinical Pathways 文章

ArXiv CS.AI2026-06-02NEWSen作者: Pasquale Ardimento, Mario Luca Bernardi, Marta Cimitile, Samuele Latorre

摘要

arXiv:2606.00041v1 Announce Type: cross Abstract: This study analyzes COVID-19 care pathways using the COVID Data for Shared Learning dataset. We build a transparent, reproducible pipeline that transforms heterogeneous clinical tables into a process-mining-ready event log and applies discovery, declarative conformance checking, and outcome analysis. The reconstructed pathways highlight the monitoring backbone of inpatient care, variability at the Emergency department-admission interface, and outcome differences driven by age and exposure to intensive care units. These insights support triage standardization, capacity planning, and step-down coordination from intensive care units to lower-acuity wards, showing how process mining can inform evidence-based hospital governance.

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