Minerva H Zhou 1 , Akash P Kansagra 2,3,4 . Show Affiliations »
Abstract
OBJECTIVE: To compare performance of routing paradigms for patients with acute ischemic stroke using clinical outcomes. METHODS: We simulated different routing paradigms in a system comprising one primary stroke center (PSC) and onecomprehensive stroke center (CSC), separated by distances representative of urban, suburban, and rural environments. In the Nearest Center paradigm, patients are initially sent to the nearest center, while in CSC First, patients are sent to the CSC. In Rhode Island and Distributive paradigms, patients with Field Assessment Stroke Triage for Emergency Destination (FAST-ED) score ≥4 are sent to the CSC, while others are sent to the nearest center or PSC, respectively. Performance and efficiency were compared using rates of good clinical outcome determined by type and timing of treatment using clinical trial data and number needed to bypass (NNB). RESULTS: Good clinical outcome was achieved in 43.67% of patients in Nearest Center and 44.62% in CSC First, Rhode Island, and Distributive in an urban setting; 42.79% in Nearest Center and 43.97% in CSC First and Rhode Island in a suburban setting; and 39.76% in Nearest Center, 41.73% in CSC First, and 41.59% in Rhode Island in a rural setting. In all settings, the NNB was considerably higher for CSC First than for Rhode Island or Distributive. CONCLUSION: Routing paradigms that allow bypass of nearer hospitals for thrombectomy-capable centers improve population-level patient outcomes. Differences are more pronounced with increasing distance between hospitals; therefore, the choice of model may have greater effect in rural settings. Selective bypass, as implemented in Rhode Island and Distributive paradigms, improves system efficiency with minimal effect on outcomes. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2019. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
OBJECTIVE: To compare performance of routing paradigms for patients with acute ischemic stroke using clinical outcomes. METHODS: We simulated different routing paradigms in a system comprising one primary stroke center (PSC ) and onecomprehensive stroke center (CSC), separated by distances representative of urban, suburban, and rural environments. In the Nearest Center paradigm, patients are initially sent to the nearest center, while in CSC First, patients are sent to the CSC. In Rhode Island and Distributive paradigms, patients with Field Assessment Stroke Triage for Emergency Destination (FAST-ED) score ≥4 are sent to the CSC, while others are sent to the nearest center or PSC , respectively. Performance and efficiency were compared using rates of good clinical outcome determined by type and timing of treatment using clinical trial data and number needed to bypass (NNB). RESULTS: Good clinical outcome was achieved in 43.67% of patients in Nearest Center and 44.62% in CSC First, Rhode Island, and Distributive in an urban setting; 42.79% in Nearest Center and 43.97% in CSC First and Rhode Island in a suburban setting; and 39.76% in Nearest Center, 41.73% in CSC First, and 41.59% in Rhode Island in a rural setting. In all settings, the NNB was considerably higher for CSC First than for Rhode Island or Distributive. CONCLUSION: Routing paradigms that allow bypass of nearer hospitals for thrombectomy-capable centers improve population-level patient outcomes. Differences are more pronounced with increasing distance between hospitals; therefore, the choice of model may have greater effect in rural settings. Selective bypass, as implemented in Rhode Island and Distributive paradigms, improves system efficiency with minimal effect on outcomes. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2019. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Entities: Disease
Gene
Species
Keywords:
stroke; thrombectomy
Mesh: See more »
Year: 2018
PMID: 29970618 DOI: 10.1136/neurintsurg-2018-013994
Source DB: PubMed Journal: J Neurointerv Surg ISSN: 1759-8478 Impact factor: 5.836