Thought Leaders in Artificial Intelligence: Shantanu Nigam, CEO of Jvion (Part 1)

Jvion applies AI to avoidable healthcare problems in patients inside and outside hospitals. Read on for more on a very interesting application.

Sramana Mitra: Let’s start by introducing our audience to yourself as well as Jvion.

Shantanu Nigam: I’m one of the founders of Jvion, and I’m also the CEO. We apply AI to reduce avoidable patient harm. We do it by anticipating where patient harm can happen and by finding out the modifiable aspect of harm. Also by identifying the right interventions that have the most likelihood of changing that harm event.

Sramana Mitra: Could you take us through a bit of a use case?

Shantanu Nigam: Avoidable harm occurs in two categories. One happens when a patient is inside the hospital and the other when a patient is outside the hospital. I can share an example of each one. Let’s say there’s a condition that shouldn’t happen if everything’s done right to the patient.

We pick up one of those disease conditions. It’s called called pressure injuries stage three and four. It’s also called bed sores. This is a very dangerous condition. It has about 20% to 30% mortality. Each incident costs about $36,000 to $38,000 of additional care.

When a patient walks into a hospital for a hip replacement, that patient will have to stay in the hospital for additional days because of bed sores. How we help is, we identify the likelihood and chances of the patient getting bed sores and identify the interventions that can help with that patient.

It could be clinical, applying medication, or as simple as turning that patient every hour instead of every four hours. The likelihood of having this disease condition is reduced through these interventions.

Sramana Mitra: Let’s stay on this particular use case for a moment. Help me understand what is the level of adoption of something like this. How much adoption has it in your customer base?

Shantanu Nigam: Our customers include marquee customers like Cleveland, Duke, Northwell. They have a different level of adoption. They could roll out these things with near 100% adoption. Then there are community hospitals. We have a lot of those as well where adoption is a little more staggered. The solution is rolled out at an enterprise level in almost every situation but the adoption happens either on the floor or a site.

Sramana Mitra: From a human behavior point of view, you need the nurses to be willing to adopt something like this. What do you think is the gating item? What do you think the nurses do or do not like?

I’ll give you an example. When CRM was first introduced to the industry, sales people didn’t like to insert notes into the system. That was one of the blocking items within until it became really useful and they started seeing the value. That drove the adoption.

What do you think is going on psychologically?

Shantanu Nigam: It took us a few years to learn that aspect. We’ve been at this for nine to 10 years now. For the first few years, we kept making a few mistakes. We learned over the last few implementations. Change management is an issue. You could follow all the best practices out of four or five bullet points of change management and reeducate them. In this space, there’s one more complexity; the way the nurses look at this kind of solution.

This segment is part 1 in the series : Thought Leaders in Artificial Intelligence: Shantanu Nigam, CEO of Jvion
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