Mumbai hospital launches AI-based hub-and-spoke stroke model across city

With stroke cases rising rapidly across India and delays in diagnosis often costing patients their lives or mobility a Mumbai hospital has taken a unique step to bridge this critical gapKeeping the importance of the ldquogolden windowrdquo of 45 hours in mind the hospital has launched an AIbased HubandSpoke stroke care model with diagnostic centres acting as spokes and Gleneagles Hospital in Parel functioning as the central hub This initiative ensures that the moment a suspected stroke is detected on CT or MRI the hospitalrsquos stroke team is alerted instantly allowing faster decisions quicker transport and timely treatmentAIenabled stroke response networkUnder this model Dr Nitin Dange heads the stroke response team supported by Dr Shirish Hastak and Dr Pankaj Agarwal Dr Kushal Bhatia and Dr Mayur Gharat receives realtime AI notifications on their mobiles the moment a suspected stroke is detected at any connected diagnostic centreUnderstanding stroke and the urgency of timeA stroke occurs when blood supply to the brain is either blocked ischemic stroke or when a blood vessel ruptures causing bleeding hemorrhagic stroke Common causes include high blood pressure diabetes smoking high cholesterol and heart disease If not treated quickly a stroke can lead to paralysis speech loss permanent disability or even death The biggest challenge in stroke care is time Many patients lose precious hours after diagnosis due to a lack of awareness delayed referrals or being taken to centres without advanced stroke facilities Recognising this gap the city hospital conceptualised an AIdriven HubandSpoke model to ensure that diagnosis immediately translates into actionDr Nitin Dange director Interventional Neurologist and Neurosurgeon Gleneagles Hospital Parel says ldquoGleneagles Hospital has taken the initiative of launching an AIbased HubandSpoke stroke model to address the growing burden of stroke cases and the delays we commonly see in treatment For the past six months we have installed this AI software at selected diagnostic centres offering CT scan and MRI services in Mumbai and Navi Mumbai areas such as Ghatkopar Mulund and Panvel and which other areas The moment a scan suggests a stroke the software automatically identifies whether it is a bleeding stroke or a blockage stroke estimates the time of onset and sends instant alerts to our stroke team on their mobile phones This allows us to act immediately In cases of blockage stroke if the patient is within the 45hour golden window we can even start thrombolysis on the way while shifting the patient to our hospital for advanced procedures like mechanical thrombectomy Till now we have treated 34 patients so far under this model all have shown good recovery With more awareness and more diagnostic centres joining this network many more stroke patients can receive lifesaving treatment on timerdquoldquoThis HubandSpoke model is not just about technology it is about saving time brain function and lives By connecting diagnostic centres directly with our stroke specialists we are ensuring that no patient loses crucial minutes due to confusion or delays Our vision is to expand this network and collaborate with more centres so that early diagnosis leads to immediate treatment With the rising incidence of stroke such integrated care models will play a vital role in improving outcomes and creating greater public awarenessrdquo concludes Dr Bipin Chevale CEO of the hospitalStrengthening stroke care through the HubandSpoke ModelThe AIbased HubandSpoke stroke model offers advantages for both diagnostic centres and hospitals Diagnostic centres benefit by becoming active participants in lifesaving care ensuring that stroke findings are immediately escalated to specialist teams rather than ending at diagnosis For the Hospital the model enables early clinical decisionmaking faster patient transfers better utilisation of the golden window and improved treatment outcomes By creating a seamless technologydriven link between diagnosis and intervention the model reduces delays optimises resources and sets a new standard for coordinated stroke care