The phrase “time is brain” means that quick treatment is very important in stroke cases. Research shows that every minute of delay can cause about 1.9 million brain cells to die. This can lead to worse health results and more long-term disabilities. If treatment like mechanical thrombectomy, which removes a clot, is delayed, the chance of recovery goes down.
Lowering door-to-puncture times has become an important goal in stroke centers. This is true especially for comprehensive stroke centers (CSC) that can do advanced procedures. The American Heart Association (AHA) and American Stroke Association (ASA) have new guidelines that stress faster treatment. Therefore, hospitals are looking for ways to make their workflows better so they can treat patients more quickly.
Neurovascular AI systems are special computer programs. They quickly analyze images from CT scans and MRIs. They find problems like large vessel occlusions (LVO) or bleeding in the brain and alert the medical team fast. This helps fix delays caused by things like waiting for a radiologist or slow communication.
Some AI platforms used in U.S. hospitals include Viz.ai, Aidoc’s aiOS™, and Rapid.ai. These systems have FDA approval and work with existing hospital computer systems to be used widely.
Faster Detection and Notification: AI spots crucial images first and sends alerts immediately. This helps stroke teams act faster than usual.
Reduced Treatment Times: Studies show AI can cut down door-to-puncture times. For example, Viz.ai helped cut the time by 41 minutes in a UCSD study. At Johns Hopkins, Rapid.ai’s app cut times by 33 minutes.
Improved Patient Outcomes: Quicker treatment means patients often have better recovery, shown by lower stroke severity scores after treatment.
Enhanced Transfer Efficiency: AI tools also speed up patient transfers between hospitals. One center saw transfer times drop by 37 minutes when using Viz.ai.
Viz.ai is a well-known example of AI used for stroke care in the U.S. It has AI tools that find LVO, brain bleeding, and other issues in CT scans. It has helped reduce door-to-treatment times from over 200 minutes to under 60 minutes in some cases, which is important in stroke care.
In the VISIION study at UC San Diego, patients diagnosed with LVO using Viz.ai had a 32% faster treatment time. That meant 41 minutes less before treatment started. Hospitals using Viz.ai also saw faster transfers from smaller stroke centers to bigger ones for surgery.
Dr. Ameer Hassan, a neurologist involved with these studies, said that AI tools like Viz.ai help by making workflows smooth and improving communication between care teams.
At Johns Hopkins University, the Rapid Workflow for Stroke app helped cut hospital stroke treatment times. The app sends alerts to stroke teams on their phones and gives fast access to scans, helping teams get ready faster.
In a study with 64 patients, the app cut door-to-puncture time by 33 minutes on average. Other treatment time points also improved. Patients had better stroke severity scores after surgery and when discharged, meaning they recovered better.
Dr. Mais Al-Kawaz, who helped with this study, said the app helps with quick assessment and communication, which is very important for fast care and less brain damage.
Aidoc’s AI works with hospital systems to analyze and alert care teams in real time. It covers different specialties, including stroke care. Aidoc reports it cuts door-to-puncture time by 34%, saving about 38 minutes per patient. This saves many neurons, roughly 72 million per patient.
Aidoc’s apps also improve team communication and fix workflow delays. Laci Costa from Aidoc said that using AI with better workflows helped hospitals like Ochsner LSU Shreveport treat stroke patients faster.
The U.S. stroke care system depends on networks of hospitals. These include primary stroke centers (PSCs) that give initial care and comprehensive stroke centers (CSCs) that handle complex treatments.
New guidelines say quick EMS triage, fast transfers, and better workflows are key to hitting treatment goals. AI fits well in this system by:
Hospital managers have to think about the costs and benefits of AI. Aidoc says a large hospital with 1,000 beds could gain millions of dollars a year from using their AI, because patients get treated faster and complications go down.
Besides reading images fast, AI systems now automate many stroke care tasks. They send alerts to the right medical staff quickly through secure apps, so no time is lost waiting for calls or messages.
Alerts reach neurologists, radiologists, surgeons, nurses, and emergency teams all at once. These apps also let teams:
Hospital IT staff need AI systems that work smoothly with current tools like image storage systems (PACS), electronic health records (EHR), and mobile device management. Platforms like aiOS™ make this easier with good integration.
After treatment, automated reports help hospital leaders and stroke program directors check how well teams did. This data helps find parts of the process to fix, leading to faster treatment times in the future.
Using automation can also reduce mistakes and lead to:
Even though neurovascular AI has many benefits, there are some challenges to using it. Hospital leaders need to think about:
| AI Platform/Study | Time Reduction | Patient Outcomes | Clinical Setting |
|---|---|---|---|
| Viz.ai VISIION Study (UCSD) | 32% reduction in door-to-groin puncture time (41 min) | Improved neurological recovery and reduced transfer delays | Large vessel occlusion stroke patients |
| Rapid Workflow Mobile App (Johns Hopkins) | 33-minute reduction door-to-groin puncture; 35 min door-to-first pass; 37 min door-to-recanalization | Lower NIHSS scores at 24 hours and discharge | Comprehensive Stroke Center |
| Aidoc aiOS™ (Ochsner LSU Shreveport) | 34% door-to-puncture time reduction (38 minutes saved) | Preservation of about 72 million neurons per patient | Integrated stroke care network |
| Viz.ai Comprehensive Stroke Center Study | 15-minute door-to-puncture time reduction; 37-minute transfer time reduction | Faster mechanical thrombectomy start | Multi-hospital stroke system |
Medical leaders, IT managers, and hospital owners in the U.S. must make important choices about new technology and ways to improve stroke care. Neurovascular AI helps reduce treatment times and improve patient outcomes. These systems help hospitals meet required health care standards set by groups such as the AHA and ASA.
Using AI well means teamwork between doctors, hospital staff, and IT teams. AI does not replace doctors but helps them by giving quick information and improving communication. This creates a better stroke care environment.
Hospitals that use AI and automation can expect smoother operations, better care coordination, and possibly fewer long-term disabilities because patients get treated faster. With stroke being a major health issue in the U.S., AI technologies offer a way to make stroke care faster and more effective.
Aidoc’s core enterprise platform is known as aiOS™, which enables seamless end-to-end integration into existing hospital IT infrastructure, supporting scalable AI implementation across clinical workflows.
aiOS™ tackles a fragmented healthcare system by unifying AI workflows, enhancing data accuracy, connecting care teams across specialties, and streamlining patient management to improve overall care coordination and efficiency.
Aidoc provides AI solutions across Radiology, Cardiology, Neurovascular, and Vascular specialties, automating imaging analysis, prioritizing findings, activating care teams, and facilitating patient follow-up.
Aidoc automatically analyzes medical imaging to prioritize critical findings, speed up notification times by 31%, activate care teams, and streamline radiology workflows, alleviating radiologist shortages.
The neurovascular AI provides high-performing algorithms for stroke, hemorrhage, and brain aneurysm with real-time notifications, reducing door-to-puncture times by 34%, improving stroke care outcomes significantly.
Aidoc’s cardiac AI provides consistent measurements and captures incidental findings in imaging and text data, addressing gaps where 30% of moderate to severe coronary calcification patients are otherwise not appropriately managed.
The vascular AI streamlines workflows, centralizes patient management for diseases like pulmonary embolism and deep vein thrombosis, ensuring 99% of eligible patients receive timely long-term follow-up.
Aidoc addresses fragmented healthcare systems by unifying disparate AI algorithms, connecting care teams, and integrating clinical and operational workflows to improve patient care continuity and operational efficiency.
Aidoc offers AI Strategy & Implementation resources including the BRIDGE guidelines, AI PATH program, and operational workshops to help health systems develop scalable, governed AI strategies beyond just deploying algorithms.
For a 1,000-bed health system, Aidoc estimates a potential $100 million annual net contribution from its AI enterprise solution, assuming a 25% net contribution margin and typical payor mix, illustrating substantial return on investment potential.
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