Abstract P266: The Implementation of Artificial Intelligence Significantly Reduces Door-In Door-Out Times in Primary Care Center Prior to Transfer

Abstract

Introduction: Viz.ai artificial intelligence (AI) software utilizes AI powered large vessel occlusion (LVO) detection technology which automatically identifies suspected LVO through CT angiogram (CTA) imaging and alerts on-call stroke teams. We performed this analysis to determine if utilization of AI software can reduce the door-in door-out (DIDO) time interval within the primary care center (PSC) prior to transfer to the comprehensive care center (CSC). Methods: We compared the time interval between door-in and door-out for all LVO transfer patients from a single spoke PSC to our CSC prior to (Feb. 2017 to Nov. 2018) and after (Nov. 2018 to June 2020) incorporating Viz.ai. Using a prospectively collected stroke database at a CSC, demographics, DIDO time at PSC, modified Rankin Scale at discharge (mRS dc), mortality rate at discharge, length of stay (LOS) in hospital and neurological ICU, and intracranial hemorrhage rates were examined. Results: There were a total of 63 patients during the study period (average age 69.99 ± 13.72, 55.56% women). We analyzed 28 patients from the pre-AI (average age 71.64 ± 12.28, 46.4%), and 35 patients from the post-AI (average age 68.67 ± 14.88, 62.9% women); see Table 1 for comparison of baseline characteristics and outcomes. Following the implementation of the AI software, the mean DIDO time interval within the PSC significantly improved by 102.3 minutes (226.7 versus 124.4 minutes; p=0.0374); significant reductions were not noted in mRS at discharge, rates of hemorrhage, or mortality. Conclusion: The incorporation of the AI software was associated with a significant improvement in DIDO times within the PSC and may lead to significant improvements in functional outcome and mortality in transfer patients. More extensive studies are warranted to expand on the ability of AI technology to improve transfer times and outcomes for LVO patients.