Theoretically, most would agree that evidence exists about how AI can enhance stroke triage and directly impact treatment times by making clinical workflows more efficient with mobile image viewing and care coordination. We have seen an influx of new clinical AI vendors enter the market in just the past five years.
In stroke and neurovascular care, the AI landscape has become quite crowded. It may be easy to think that one stroke triage algorithm is just as good as another. So, what sets Aidoc apart from the rest? This is a real story, from a real institution, that clearly demonstrates how AI is propelling stroke treatment forward with a direct benefit for patients.
Ochsner LSU Shreveport is a valued partner of Aidoc and trusted us to provide their Stroke AI triage and care coordination. There were institutional goals they wanted to achieve with regards to stroke performance metrics. Aidoc partnered with them to help achieve these milestones. In addition to implementing and utilizing our AI solutions, together we initiated a Stroke Workflow Optimization Project led by our Solution Success Team. This team is made up of clinical experts in stroke workflows with more than 50 years of cumulative experience working in the hospital on stroke care teams.
As a part of the stroke workflow optimization project at Ochsner LSU Shreveport, Aidoc set out to help find potential inefficiencies or breakdowns in workflow and create solutions along the way using AI-augmented tools. Incorporating Aidoc’s care coordination mobile application helped streamline stroke patient awareness among the care teams and improve time metrics across the board. Data was also collected retrospectively studying the impact of an AI vendor transition to Aidoc as the primary stroke triage AI system.
Post-implementation of Aidoc’s stroke solution and upon conclusion of the workflow optimization project, Ochsner LSU experienced a 34% reduction in door-to-puncture (DTP) for their stroke patients, equivalent to 38 minutes. They also experienced a 24% reduction in door-to-CT time of 7 minutes. This outcome suggests that differences in workflow efficiency, coupled with AI capabilities, can contribute to significant improvements between vendor solutions.
The effectiveness of Aidoc’s solution underscores the importance of vendor selection in optimizing clinical outcomes. Looking ahead, further research is needed on incidental stroke findings, vessel occlusion location distribution and how AI can impact patient care among these different groups.
To put these numbers into perspective, saving an average of 38 minutes in treatment time accounts for 72.2 million neurons per patient. In a world where time is brain and 1.9 million neurons are lost with each minute that a stroke is untreated, minutes matter. Not only do minutes matter to Ochsner, as they are committed to provide best in class stroke care to their patients, they matter to the patients suffering strokes every day.
Abstract presented at SNIS 2024 Annual Meeting: Enhancing Stroke Care Efficiency Through Ai Vendor Transition: A Comparative Study Of Workflow Metrics Before And After Implementation. H. Chokhawala,, H. Cuellar, R. Shah, A. Savardekar; Louisiana State University Health Sciences Center, Shreveport.
Stroke solution is based on Aidoc’s AI Triage solutions in combination with Icometrix.
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