With its AI-based care coordination platform, Viz.ai is transforming stroke care by making every second count. Senior director of clinical strategy, Dr Prem Batchu-Green, speaks to NR Times
Viz.ai uses artificial intelligence to help clinicians make the correct diagnosis and communicate this with the relevant people within seconds. Using data from hospital systems, such as CT scans, echocardiograms, MRIs and electronic health records, the company’s algorithms are able to detect specific conditions in medical images and then share this with care teams across different hospital systems.
This quick coordination is crucial when it comes to stroke, with research showing that for every minute that passes after a stroke, 1.9 million brain cells die. The quicker the patient is treated, the better the outcome is likely to be.
Research has found that Viz’s AI-based care coordination platform is associated with a significant reduction in the time taken for the patient to access the appropriate treatment. As a result real-world evidence collected by the company has shown a reduction in overall disability in patients following stroke.
A clinician by background with a doctorate in physical therapy, Dr Prem Batchu-Green, has been with Viz.ai as senior director of clinical strategy for the past two and a half years. Having seen a family member affected by stroke, she was well aligned with Viz’s goal to transform stroke care by helping clinical teams detect it before it’s too late.
Dr Batchu-Green Prem speaks to NR Times about the significant impact Viz is making in patient outcomes in stroke care.
Can you start by telling us what drew you to the company as a clinician?
Making that switch to the industry side was really about exploring how to drive a larger impact across this disease state, starting in stroke and across the patient populations that we treat today. I transitioned into this journey having a family member affected by stroke and having seen the stroke rehab process as a clinician. The vision and the focus of what Viz was trying to accomplish was near and dear to my heart. Viz is focused on providing access to timely care to patients and ensuring that there is a seamless path forward for physicians to coordinate care. It’s been really exciting to see the impact we’ve had on the stroke side, not only with improving time to treatment given that time is brain, every second matters to help reduce some of that functional disability that results from stroke, but also in being able to drive outcomes across patients in different disease states.
There is certainly some very interesting data around the platform, can you talk me through how it works in practice?
A patient comes into an emergency department or an outpatient imaging centre and has some imaging done based on their clinical presentation. That image gets sent to the cloud in which our algorithm lives. The algorithm then runs on that image and provides an alert back to the physician to notify them of a specific disease condition, for instance, for stroke it could be large vessel occlusion, intracerebral haemorrhage or subdural haemorrhage. It alerts the entire care team and because it is a triage tool it allows physicians to view the image and if they agree with the findings they can alert their teams to help coordinate and facilitate a certain type of intervention. It allows all of that communication within the app itself, allowing for a much more seamless pathway as opposed to having to pick up multiple phones, all of which eats into the time and efficiency of getting your patient to treatment.
Is this disjointed communication something that has been identified as an issue in terms of stroke care?
What we’ve seen historically is that it takes over three hours to get a patient to the appropriate level of care and to actually have an intervention completed. A lot of our research has demonstrated significant time savings to accelerate those in-hospital workflows. When you think about the critical time metrics from a stroke standpoint and Get With The Guidelines®, even notification to the neuro interventionist for sites that don’t utilise AI could be close to 90 minutes whereas with AI, it’s 50 minutes.
What research has been done to support the benefits of the Viz platform?
We’ve been able to demonstrate improvements across all key metrics of the Get With The Guidelines®. Our real-world evidence shows significant reductions in time savings to get that patient to appropriate treatment, along with an improvement in length of stay and in discharge MRS scores, which essentially shows a reduction in overall disability to that patient and the ability to be discharged to home versus a subacute or acute rehab facility, because we were able to resolve some of that with earlier treatment and management.
What are you excited about when it comes to AI in the future of stroke care?
I think we’re at the tip of the iceberg. I think AI is going to play a huge role in terms of helping optimise workflows and coordinate care teams in a much more robust manner than was done previously, which will allow for time to treatment to be significantly expedited. What was exciting to see over time is now even within the guidelines there are recommendations for utilisation of AI triage software for stroke care. With the incorporation of that we’ll start to see significant improvements and reductions in disparities in care whether it’s in urban or rural settings.
What is adoption of Viz like among clinicians, do you find there is still some scepticism about the role of AI in healthcare?
Over time we’ve had a lot of care teams really embrace the functionality and the use of the AI within the app. The ease of access has really supported physicians as well, just from a work-life balance perspective. We are installed in over 1,500 hospitals and it’s exciting to see that continue to grow and it’s not just for our stroke platform, but other algorithms and pathways that we have available as well.
Everyone is starting to engage, from the emergency department to the neuro interventionalists to the nurses, even to transfer centre staff to help with managing decision making for when a patient gets transferred and to coordinate bed placement. The more adopted and integrated AI gets within the workflows, the more cases they see to expand the user base of who should be involved in the communication.
What can we expect from Viz in the future?
We started in stroke and now we’ve moved on to include pulmonary care, aortic care and cardiovascular care. The exciting part about what you can expect in the future from Viz is being able to continue to expand the care pathways that we are building into our platforms. The pathways that we have built to date are supporting both ischemic and hemorrhagic stroke management and being able to triage those appropriately. We’re also detecting cerebral aneurysms to avoid rupture, which leads to SAH, as well as subdural haemorrhage, which is another area that’s going to be pretty significant in clinical trials to help optimise patient outcomes.
How does Viz maintain that patient focus while also providing value for your other stakeholders?
Our key insights in terms of where the need is, come from a physician-based perspective. What we do best is listen to clinicians that are taking care of patients to understand where those challenges are and also what’s happening in terms of the clinical guidelines and where we can help establish pathways to support the clinical guidance. I think both of those together really keep Viz patient focused in terms of how we can impact outcomes. At the end of the day what we want to do is help our clinicians make better decisions on where the appropriate care is for the patient.
