Viz.ai and why workflow > tech
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Let’s get visual, vi-su-al
A company called Viz.ai recently announced that it now can be reimbursed by Medicare. The company provides a stroke detection workflow using AI to more quickly identify and escalate the issue. I believe this is the first reimbursement that CMS has given for AI-augmented care.
This is an area I don’t know too much about, so I thought I’d use this as an excuse to learn a bit more about the company, AI-workflows, and Medicare reimbursement. If you want to read an actual expert opinion on this, I recommend the two part series Luke-Oakden Rayner put together.
But here are some of my thoughts diving into it.
Viz.ai, the product
Viz.ai is really quite a sleek product. It focuses on doing one thing very specifically, detecting Large Vessel Occlusions (LVO) which - for simplicity sake - is a type of clot that cuts blood flow to your brain, resulting in a serious stroke.
In this situation time is of the essence. In one scenario, these patients will be taken to a primary stroke center, which can handle most simple stroke cases and can also assess if a patient has a more serious stroke issue, such as an LVO, that will require more complex stuff like a thrombectomy, neurosurgery, etc. Those more serious patients will be sent to a comprehensive stroke center, which has all the bells and whistles to handle all strokes and post-stroke intensive care.
This creates a type of hub-and-spoke model, where lower acuity cases can be taken care of in these primary stroke centers and transferred to the mothership for necessary procedures, etc.
So the question is how do primary stroke centers assess whether or not a patient needs to be escalated? There’s a pretty complicated set of steps to assess this but I’ll use Viz.ai’s definitely unbiased marketing materials for simplicity sake.
In a normal workflow, there’s a lot of back and forth that happens between an emergency medicine doctor, a diagnostic radiologist, a neurologist, and a neurointerventional radiologist (smh they just keep making these specialty names longer). This escalation happens somewhat linearly, requires lots of phone calls and pings, and eventually a decision gets made to transfer a patient to a comprehensive stroke center.
Enter Viz.ai. I believe the company’s LVO product takes the advanced imaging step, analyzes it using AI black magic, assesses if it’s a serious and intervenable LVO stroke, and then sends an alert to EVERYONE on that care team simultaneously. Usually the diagnostic radiologist would have to read it first and escalate, but if Viz.ai thinks it’s serious it’ll basically start a group chat with everyone including the specialists (stroke neurologists/neurointerventional radiologist) that would make the call to bring a patient in for a procedure.
This shortens the time between patient coming in, notifying a specialist, and getting care, by a pretty crazy amount of time . Average time to notify a specialist in standard of care was 58.72 minutes vs. 7.32 minutes with Viz.ai!!! That’s literally a big enough time difference to rewatch the series finale of Game of Thrones, cut it off in the middle cause it’s terrible, complain on r/freefolk, and still have time leftover.
It’s worth noting that this time-saving mostly happens in the primary stroke centers. The comprehensive stroke centers are pretty fast since the specialists are right there to talk it out and there’s no distance required to transport the patient.
And the product is slick too. Here’s a view of the product sending an urgent alert to the care team when it suspects there’s a serious stroke. This is probably the most high-importance notification to ever be pushed to an iPhone (other than a Doordash notification that you now have 50% off your next order). Once you click in, you get multiple views of the CT scan that you can manipulate, zoom in on, etc.
Then there’s a messaging function where all the care team can communicate with each other, and you can see a trail of when the patient comes in, when the different doctors view the scan, leave annotations, etc. This product is so seemingly simple but executes exactly what’s necessary. It’s like Slack, but if every single message mattered instead of people sending details of their personal lives that no one asked for to the #random channel. Ok actually definitely not Slack.
Workflow > Tech
There are a few aspects of this workflow that I think are important.
- It makes the work both parallelized. There are a lot of algorithms and protocols that happen in healthcare which are relatively linear - a patient gets tests done, needs to get them interpreted, and then the next steps happen (escalation, sent to a specialist, more tests, etc.). If you can use tech to predict with higher certainty what the required follow-up for a patient is going to be, you can parallelize the process earlier and do more tasks simultaneously if you feel confident the patient has X issue. In this case, a linear process of scan -> radiologist -> interpretation -> escalation -> referral -> specialist, etc. was parallelized into everyone looking at once.
- The work and follow-up is collaborative AND trackable. Parallelization alone would result in a lot of redundant work if everyone was doing their own work stream in isolation. But the group messaging + ability to see activity means it’s easy to see who’s doing what piece of work.
- Finally, it’s a single use-case work stream. If you get a notification from this app, you know exactly why, the level of urgency required, and context within the push notification itself. Physicians generally have information overload - being able to cut through the noise is important. There are certain time-sensitive diseases where this is very important and early detection + escalation can completely change the outcome. AI-enabled workflows can be game changers in areas like sepsis, acute kidney injury, heart attack, many neonatology issues, etc. RapidAI is another company with similar workflows for cerebrovascular issues.
A point I’ve tried to hammer home is that tech in healthcare is only useful if enables a new workflow and as a result can change the economics of that process. For example, face-to-face telemedicine isn’t interesting because it’s the same workflow as an office visit, but asynchronous telemedicine lets you interact with many more patients and drop the cost of a visit.
AI diagnostic companies have struggled with this, but Viz.ai is a great case study of how a workflow can change thanks to tech. Honestly it’s basically just AI-charged push notifications + a group chat. It’s deceptively simple…but that works!
The workflow is so important that it’s what Viz.ai focused as its main mechanism of action instead of the AI alone. CMS had a lot of pushback about whether a workflow optimization would be considered having a therapeutic effect (the way a medical device would). But Viz.ai presented their case and managed to convince CMS that AI-assisted workflows can indeed be considered to have a therapeutic outcome.
From their application to CMS for reimbursement:
With respect to the first substantial similarity criterion, the applicant asserted that computer-assisted triage and notification is the mechanism of action for ContaCT and that the mechanism of action for ContaCT is not AI per se. According to the applicant, AI is a necessary component of ContaCT, but is not sufficient to achieve therapeutic effect.
Response: After considering the comments received regarding the new technology add-on payment application for ContaCT, [CMS] agree that ContaCT does not use the same or a similar mechanism of action to achieve a therapeutic outcome when compared to existing treatments because there are currently no FDA approved or cleared technologies that use computer-assisted triage and notification to rapidly detect an LVO and shorten time to notification. Therefore, we believe that ContaCT is not substantially similar to an existing technology and meets the newness criterion.
Every AI company should be thinking about this going forward - can you prove that your technology creates a unique workflow that can measurably improve outcomes vs. the standard of care? Then you can get reimbursed.
But if a workflow can be considered to cure a disease…does that mean workflows can also cause a disease? If so, then I nominate Jira.
Questions about the business
Most of my current questions around Viz.ai are about the business model. They’re charging a subscription, and while they reference $25K per year in the CMS document, I would guess they’ll be tiered pricing depending on whether it’s a primary or comprehensive stroke center.
In the above quote, CMS is approving Viz.ai to receive reimbursement through it’s New Technology Add-on Payment program (NTAP). It’s worth explaining how this works because it’s important for new tech companies. Even if your tech is considered dope or given the stamp of approval by the FDA, the hospital is not going to use you if they’re not getting paid to use you.
The gist of NTAP: When a Medicare patient gets admitted into the hospital as an inpatient, the hospital will be reimbursed for a bundle of services associated with whatever disease that patient is being treated for. These are known as Diagnosis Related Groups (DRGs), and an example is an ischemic stroke.
The problem with this DRG system is that a hospital will not want to try any new technology to treat these diseases, because using it would cost money and Medicare won’t reimburse them since it’s not within the DRG. So Medicare set up this NTAP program - which will pay a hospital an additional amount on top of the DRG bundle payment if it uses that technology and the cost of that tech causes the hospital to lose money.
The losing money part is key. The primary stroke centers will likely lose money using Viz.ai, so they’ll get the NTAP reimbursement. The comprehensive stroke center gets reimbursed well for the stroke surgery, so using Viz.ai won’t cause them to lose money and therefore they won’t get the NTAP.
Remember, the comprehensive stroke center actually likely doesn’t save time from using the product, so why would they care about Viz.ai at all? Their benefit actually comes from the primary stroke center using the software to both refer more patients that need surgeries and refer them faster so that the patients recover quickly and free-up beds faster. Apparently at large stroke hubs Viz.ai has increased surgery use 50-60%. Again, very much recommend reading Luke Oakden-Rayner’s post that dives deep into this.
So Viz.ai charges a subscription per year, and then the primary stroke center has to get reimbursed enough times from the NTAP to make it worth their while. Comprehensive stroke centers probably don’t really care about the cost, but want the primary stroke center to have access to the tool so they can get referred more procedures.
My first note is why even charge this as a subscription at all? This feels somewhat punitive to smaller, primary stroke centers who now need to guess if they’re going to see enough eligible stroke patients to recoup the cost of the (potentially $25K) subscription. Smart friends of mine have mentioned that this is not dissimilar to how large diagnostic equipment are paid for - leased per month, which turns a large capital expenditure into a monthly payment. But this is software - it isn’t a a large upfront cost and the cost to deliver a new scan is marginal. Is it because everyone wants that sweet sweet ARR and predictable revenue???
The second note is that this software seems like the exact kind of candidate that would benefit from the new stark/anti-kickback laws that are being proposed. Right now, a larger hospitals can’t just give/pay for smaller hospitals to access software because it’ll be seen as a financial relationship that coerces referrals. But that also makes care coordination more difficult since smaller hospitals can’t afford some of these systems, making hand offs between them very tricky. Viz.ai would be a good candidate example where everyone benefits if the hospital can basically share the software to these smaller providers, who then wouldn’t have debate whether it’s worth it to buy the subscription because they can’t guess if they’ll be reimbursed enough.
And a final note is whether or not this is actually going to save the system any money. It’s a rare trifecta of improving patient outcomes, reducing workload, while also getting hospitals more money. But at the end of the day someone is going to have to pay for the extra procedures…at least in this case the patient actually benefits and saves costs if they can avoid a lifetime of assisted care.
Random thoughts and Conclusion
Some random thoughts as I was researching that don’t really fit into any bucket.
- There’s a hilarious exchange between CMS and Viz.ai where CMS is trying to see if the company is really that “new”.
CMS: “This not new because AI works like a brain and brains are not new”
Viz.ai: “Brains are not FDA approved”
CMS: “Ok tru”
- While you might think this sets a precedent for new technologies to get an NTAP through this process, everything seems to be completely changing. CMS is now giving an NTAP reimbursement for devices that the FDA considers “breakthrough devices”, and Medicare may even potentially just fully cover these breakthrough devices. I think there will be a lot more NTAPs next year but for a different reason than Viz.ai’s reimbursement announcement. Once hospitals can get that bread (aka. reimbursement), I think we’ll see a ton more deployment of AI tools in clinics.
- There is a serious first-mover advantage here. With the current NTAP criteria, it seems like a competitor wouldn’t be pass the “new technology” criteria if Viz.ai already got it. Even for breakthrough devices, you have to prove you’re significantly better than what’s on the market. Getting the “new technology” designation first seems like a huge barrier to whoever would want to be a follow-on competitor.
- I sort of wonder how hard it would be for a tech giant to replicate this and just sell a service like this or workflow tool with the bundle of cloud services they’re trying to get hospitals to adopt anyway. Remember when Google’s Deepmind came out with that Acute Kidney Injury product? That product was also about skipping steps to escalate to a specialist in a time sensitive situation.
- From what I can see Viz.ai basically only submitted trials that compared its product vs. standard of care. But if there was a tool that could make the EMTs more confident based on other cues from a patient that it was a serious stroke, that would be even better they could drive a patient straight to the comprehensive stroke center and bypass the primary stroke center completely. That might be even better, though idk how feasible that is. Or could any center with a CT-Sc now do LVO stroke assessments, creating more spokes in the hub and spoke model?
- This is a great example of watching AI change the roles of physicians. For the roles/parts of a physicians job that are considered “escalation”, especially based on a singular data stream, those will likely be pushed to AI. Even in this scenario, increasing the number of procedures means more demand for people to be interventional radiologists vs. diagnostic.
- How would a company like Viz.ai expand, other than just selling into more hospitals and geographies? A product like this works because of its simplicity, trying to add more would probably be a bad idea. But I wonder if this could be a wedge into other collaborative care products between hospitals and other periphery clinics.
So my general sense from reading around is that Viz.ai is a product that works extremely well for its use case + has nailed the workflow and sits at a really lucrative part of the stroke care process (e.g. should a patient go get an expensive procedure or not).
But it has a strange business model to me that actually is somewhat worse for the small clinics that would benefit the most from it (since they’d have to guess if they’re going to have enough eligible patients to make it worthwhile). And if you could use this technology to turn NON-stroke centers into triaging areas, then they definitely would not be able to afford it with this business model.
I wonder if the business model changes, or the company gets acquired or bundled into some other products as part of a package. They seem to already have a close relationship with Medtronic…
I expect with the new changes to the FDA breakthrough device + NTAP rules, we’ll see a lot more AI startups build workflows and go down a similar route as well.
Let me know where I was off on this analysis, a lot of this was new for me.
Nikhil aka. “N-TAP”