Pathways of Patients With Neurological Emergencies at Pediatric Emergency Department: A Process-Based Data Mining Study.

Authors

Henna Aro, Tuomo Antikainen, Mari Videman, Elina Wärnhjelm, Erika Ignatius, Pirjo Isohanni, Miika Koskinen

Published in

European journal of neurology. Volume 33. Issue 9. Pages e70743.

Abstract

Neurological patients represent a small yet resource-demanding group in pediatric emergency departments (PEDs). Their pathways and resource needs remain poorly understood. This population-based real-world data study aims to bridge this gap.
We analyzed neurological visits from 2021 to 2023 at the sole PED serving 300,000 children using process mining and statistical analysis. Neurological visits included patients triaged for neurologist evaluation and those with neurological complaints and/or diagnosis.
We identified 4854 neurological visits, constituting 5% of PED visits. Seizure and headache comprised 64% of the chief complaints; seizures dominated the highest acuity visits, while headache was linked to visits with lower acuity. Neurological patients had a nearly fivefold increased risk of requiring immediate lifesaving interventions compared to non-neurological patients. Half of the highest acuity patients were 1-5 years old. Patient disposition was most strongly associated with acuity: 81% of highest acuity patients were admitted and 15% of them to the pediatric intensive care or surgical unit, whereas only 18% of stable patients were hospitalized. Variability of patient pathways was moderate. 87% of patients adhered to one of four most common pathways where disposition decision was made without advanced testing. Over 30 pathways were identified for patients needing advanced tests. These patients presented with higher acuity, non-seizure complaints and increased admissions.
This population-based study pioneers process mining for analyzing patient care processes and resource utilization of neurological patients at the PED. It highlights the critical nature of pediatric neurological emergencies and uncovers the variability of patient needs and pathways.

PMID:
42714217
Bibliographic data and abstract were imported from PubMed on 09 Sep 2026.

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