Literature DB >> 29306593

The Benefit of a Triage System to Expedite Acute Stroke Head Computed Tomography Interpretations.

Thomas F Osborne1, Andrew J Grabiel2, Reese H Clark3.   

Abstract

BACKGROUND AND
PURPOSE: We developed and tested a triage system to accelerate the interpretation of stroke head computed tomographies (CTs), with the goal of optimizing the time available for acute stroke therapy.
MATERIALS AND METHODS: In our practice, acute stroke protocol head CTs have been given the highest reading priority. We implemented a technologically enabled prioritization infrastructure to consistently present these critical cases to our radiologists so they are evaluated before other examinations. In our 1-year retrospective multicenter study of 350,495 head CT examinations, we compared the reading time of stroke protocol head CTs to our next highest priority head CT.
RESULTS: Our average acute stroke head CT reading turnaround time was 6.5 minutes. This represented a 17.3-minute improvement over the next highest priority head CT in our practice (confidence interval: 17.2-17.4 minutes, P < .001).
CONCLUSIONS: A technologically enabled acute stroke protocol CT triage system consistently improves the reading times of critically time-dependent head CT examinations. As a result, this system has the potential to improve treatment times, treatment eligibility, and clinical outcomes.
Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  TPA; neurology; process improvement; stroke; technology; telemedicine; triage

Mesh:

Year:  2018        PMID: 29306593     DOI: 10.1016/j.jstrokecerebrovasdis.2017.11.038

Source DB:  PubMed          Journal:  J Stroke Cerebrovasc Dis        ISSN: 1052-3057            Impact factor:   2.136


  3 in total

1.  Active Reprioritization of the Reading Worklist Using Artificial Intelligence Has a Beneficial Effect on the Turnaround Time for Interpretation of Head CT with Intracranial Hemorrhage.

Authors:  Thomas J O'Neill; Yin Xi; Edward Stehel; Travis Browning; Yee Seng Ng; Chris Baker; Ronald M Peshock
Journal:  Radiol Artif Intell       Date:  2020-11-18

2.  Should Artificial Intelligence Tell Radiologists Which Study to Read Next?

Authors:  Stacy D O'Connor; Manav Bhalla
Journal:  Radiol Artif Intell       Date:  2021-02-10

3.  Detecting brain lesions in suspected acute ischemic stroke with CT-based synthetic MRI using generative adversarial networks.

Authors:  Na Hu; Tianwei Zhang; Yifan Wu; Biqiu Tang; Minlong Li; Bin Song; Qiyong Gong; Min Wu; Shi Gu; Su Lui
Journal:  Ann Transl Med       Date:  2022-01
  3 in total

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