Impact of an artificial intelligence–driven triage system on workflow and transfer efficiency: stratified analysis of 4548 admissions to four thrombectomy hubs receiving transfers from sixty spokes
Implementation of an AI-enabled triage platform was associated with significant reductions in workflow times and increased EVT utilisation, with effects specific to AI-enabled spokes rather than secular trends alone. The proportion of transfers who did not proceed to EVT decreased in AI-enabled spokes, though counterfactual outcomes for non-transferred patients remain unknown. Clinical outcomes at discharge were unchanged.
Authors
- C. Romero (ORCID: https://orcid.org/0000-0001-5725-0359)
- R. Nogueira
- Mark D. Starr (ORCID: https://orcid.org/0009-0003-9664-6235)
- Cynthia L. Kenmuir (ORCID: https://orcid.org/0000-0002-2152-1409)
- Marcelo Cristiano Rocha (ORCID: https://orcid.org/0000-0001-6821-2286)
- Alhamza Al-Bayati
- Mohamed F Doheim
- Nirav R Bhatt
- Abdullah Sultany
- Stephanie Henry
Institutions
- University of Pittsburgh (US)
- University of Pittsburgh Medical Center (US)
Publication Details
- Journal
- Journal of Neurology Neurosurgery & Psychiatry
- Published
- 2026-03-27
- DOI
- https://doi.org/10.1136/jnnp-2025-337903
- Primary Topic
- Acute Ischemic Stroke Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00