Viz.ai Implementation of Stroke Augmented Intelligence and Communications Platform to Improve Indicators and Outcomes for a Comprehensive Stroke Center and Network

Figurelle, Morgan; Meyer, Dawn M; Perrinez, Emily; Paulson, D.; Pannell, J. Scott; Santiago-Dieppa, David R; Khalessi, Alexander A.; Bolar, Divya S.; Bykowski, Julie; Meyer, Brett C.

doi:10.3174/ajnr.a7716

Cited by 9 publications

(8 citation statements)

References 29 publications

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“…Prior studies have examined the effect of automated LVO detection on in-hospital quality metrics, as well as clinical outcomes. Several studies have found statistically significant reductions in DTG time and one study identified a reduction in hospital length of stay . These prior studies have been limited by several factors, which include small sample sizes, single-hospital data, and heterogenous populations that include both transfer patients as well as direct emergency department presentations.…”

Section: Discussionmentioning

confidence: 99%

Automated Large Vessel Occlusion Detection Software and Thrombectomy Treatment Times

Martinez-Gutierrez,

Kim,

Salazar-Marioni

et al. 2023

JAMA Neurol

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ImportanceThe benefit of endovascular stroke therapy (EVT) in large vessel occlusion (LVO) ischemic stroke is highly time dependent. Process improvements to accelerate in-hospital workflows are critical.ObjectiveTo determine whether automated computed tomography (CT) angiogram interpretation coupled with secure group messaging can improve in-hospital EVT workflows.Design, Setting, and ParticipantsThis cluster randomized stepped-wedge clinical trial took place from January 1, 2021, through February 27, 2022, at 4 comprehensive stroke centers (CSCs) in the greater Houston, Texas, area. All 443 participants with LVO stroke who presented through the emergency department were treated with EVT at the 4 CSCs. Exclusion criteria included patients presenting as transfers from an outside hospital (n = 158), in-hospital stroke (n = 39), and patients treated with EVT through randomization in a large core clinical trial (n = 3).InterventionArtificial intelligence (AI)–enabled automated LVO detection from CT angiogram coupled with secure messaging was activated at the 4 CSCs in a random-stepped fashion. Once activated, clinicians and radiologists received real-time alerts to their mobile phones notifying them of possible LVO within minutes of CT imaging completion.Main Outcomes and MeasuresPrimary outcome was the effect of AI-enabled LVO detection on door-to-groin (DTG) time and was measured using a mixed-effects linear regression model, which included a random effect for cluster (CSC) and a fixed effect for exposure status (pre-AI vs post-AI). Secondary outcomes included time from hospital arrival to intravenous tissue plasminogen activator (IV tPA) bolus in eligible patients, time from initiation of CT scan to start of EVT, and hospital length of stay. In exploratory analysis, the study team evaluated the impact of AI implementation on 90-day modified Rankin Scale disability outcomes.ResultsAmong 243 patients who met inclusion criteria, 140 were treated during the unexposed period and 103 during the exposed period. Median age for the complete cohort was 70 (IQR, 58-79) years and 122 were female (50%). Median National Institutes of Health Stroke Scale score at presentation was 17 (IQR, 11-22) and the median DTG preexposure was 100 (IQR, 81-116) minutes. In mixed-effects linear regression, implementation of the AI algorithm was associated with a reduction in DTG time by 11.2 minutes (95% CI, −18.22 to −4.2). Time from CT scan initiation to EVT start fell by 9.8 minutes (95% CI, −16.9 to −2.6). There were no differences in IV tPA treatment times nor hospital length of stay. In multivariable logistic regression adjusted for age, National Institutes of Health Stroke scale score, and the Alberta Stroke Program Early CT Score, there was no difference in likelihood of functional independence (modified Rankin Scale score, 0-2; odds ratio, 1.3; 95% CI, 0.42-4.0).Conclusions and RelevanceAutomated LVO detection coupled with secure mobile phone application-based communication improved in-hospital acute ischemic stroke workflows. Software implementation was associated with clinically meaningful reductions in EVT treatment times.Trial RegistrationClinicalTrials.gov Identifier: NCT05838456

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Section: Discussionmentioning

confidence: 99%

Automated Large Vessel Occlusion Detection Software and Thrombectomy Treatment Times

Martinez-Gutierrez,

Kim,

Salazar-Marioni

et al. 2023

JAMA Neurol

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“…When the application is accessed, real-time, dynamic, high-fidelity three-dimensional (3D) images can be viewed on the phone along with image rotation, allowing better visualization of vessel morphology (Figurelle et al., 2023). The cloud-based technology automates and provides the maximum-intensity projection of 3D images (Figure 2; Elijovich et al., 2022).…”

Section: Methodsmentioning

confidence: 99%

“…The platform provides HIPAA-compliant group communication messaging. Members can dialogue and exchange information on the same page (Figure 3; Figurelle et al., 2023; Morey et al., 2021). To be part of the messaging group, the application has to be toggled to “on-call,” resulting in case images received when on shift (Figurelle et al., 2023).…”

Section: Methodsmentioning

confidence: 99%

“…At the same time, the interventional radiologists worked closely with health care information technology groups to advance communication for stroke care. Interventional radiologists requested the development of a smartphone application that could perform three simultaneous functions: (1) a secure, coordinated, HIPAA-compliant text messaging thread for all team members; (2) access to secure, advanced computed tomography (CT) imaging, which the interventional radiologist could view immediately on their smartphone; and (3) the ability of the staff to be notified of the need for emergent mobilization by a toggle of the application (Figurelle et al., 2023; Kufel et al., 2022; Sardenelli, 2017). These three smartphone functions allowed time compression of care.…”

Section: The Impact Of Technology On Clinical Communicationmentioning

confidence: 99%

“…Subsequently, the typically cumbersome, at times contentious, on-call system was superseded (Figure 1). The large-scale, coordinated, multipleperson effort consisting of accessing schedules, placing/returning calls burdened with complex information, and contacting separate departments was prevented (Alkamel et al., 2020; Elijovich et al., 2022; Figurelle et al., 2023; Morey et al., 2021).

Figure 1. Usual care on-call staff mobilization process.…”

Section: The Impact Of Technology On Clinical Communicationmentioning

confidence: 99%

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Improving Time to Angioembolization for Trauma Care: Novel Smartphone Application

Miles,

Quinlan

2024

Journal of Trauma Nursing

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BACKGROUND: Timely angiographic embolization of abdominopelvic injuries is a hallmark of a high-functioning trauma center. Yet, the process depends on the timely mobilization of interventional radiology staff. Smartphone technology to notify and mobilize staff may be a viable option. OBJECTIVE: To describe the incorporation of a smartphone application into our trauma workflow process previously developed for stroke care. METHODS: In 2022, our Level I trauma center implemented a smartphone application with three simultaneously occurring functions: (a) high-definition image viewing on the phone; (b) text messaging thread for all parties; and (c) a single-call activation system for staff mobilization. The application was initially developed to notify interventional radiologists of large-vessel occlusions in victims of stroke and, at our request, was modified to fit our trauma workflow process. The smartphone application company developed a new program, installed the application on trauma service smartphones, and provided educational in-services over a 1-month period. The application was then integrated into our trauma workflow process. RESULTS: The trauma surgeon and the interventional radiologist can now simultaneously view high-definition images on their smartphones. Text messages are accessible to all team members. The staff is notified and mobilized with the singlecall smartphone application, preventing the placing and returning of phone calls. CONCLUSION: Smartphone technology enhances timely interventional radiology staff response for hemorrhagic patients requiring emergent angioembolization.

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Artificial intelligence in emergency neuroradiology: Current applications and perspectives

Gong,

Khalvati,

Ertl-Wagner

et al. 2024

Diagnostic and Interventional Imaging

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Viz.ai Implementation of Stroke Augmented Intelligence and Communications Platform to Improve Indicators and Outcomes for a Comprehensive Stroke Center and Network

Cited by 9 publications

References 29 publications

Automated Large Vessel Occlusion Detection Software and Thrombectomy Treatment Times

Automated Large Vessel Occlusion Detection Software and Thrombectomy Treatment Times

Improving Time to Angioembolization for Trauma Care: Novel Smartphone Application

Artificial intelligence in emergency neuroradiology: Current applications and perspectives

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