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

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

Source: cs.CY updates on arXiv.org — https://arxiv.org/abs/2606.00041 Date read: 2025-01-17 Connected to: none Escalation: store-only Escalation rationale:

What this is

A methodological case study applying process mining techniques (discovery, conformance checking, outcome analysis) to reconstruct clinical pathways from heterogeneous hospital data. The work is domain-specific (COVID-19 triage and ICU routing) and focuses on transparency and auditability of an existing system rather than discovering a new mechanism or law governing protocolized systems.

What I took from it

This is a protocol auditing application rather than a theoretical contribution. The paper demonstrates that heterogeneous event logs from complex organizational systems can be systematically transformed and analyzed to reveal variability and outcome correlations—a useful methodological validation. The finding that triage variability concentrates at the ED-admission interface is a system-specific bottleneck, not a generalizable law.

The work confirms that protocolized systems (clinical pathways) exhibit measurable deviation from formal specifications, and that this deviation correlates with outcomes (age, ICU exposure). However, it does not articulate why this variability emerges, what mechanisms sustain it, or whether the pattern generalizes across institutional or clinical domains. It is descriptive instrumentation, not generative theory.

Research connections

• None currently; no active hypotheses on clinical pathway governance exist in the established inventory.

Candidate laws or signals

CL-2606.00041-1: Heterogeneous protocolized systems show measurable compliance gaps concentrated at decision nodes (interfaces) rather than distributed uniformly. [Weak signal—requires cross-domain validation.]