Thought Leaders in Healthcare IT: Brian Phillips, CEO of MedShift (Part 2)

Sramana Mitra: It sounds like the primary value proposition for the manufacturers in the use case that you provided is maintenance. Is that correct?

Brian Phillips: That is one use case. I would say that is a good use case. Maintenance is understanding whether the machine is operating well and also having the ability to remotely upgrade that machine.

In the past, these machines were running an embedded operating system. To upgrade a system, you’d have to drive an engineer around the country to all of the locations with one of these machines. You would have to plug a USB stick into the back and enter a security code to upgrade the operating system on the medical device. That is difficult when you have thousands of these machines deployed across the country.

Once it’s connected with MedShift’s technology, we provide the ability to remotely upgrade. This is not only maintenance but also to upgrade these machines. This is in addition to the big data analysis and the ingestion of the information regarding the procedures that are being delivered. 

Sramana Mitra: Let’s double-click down into the big data element of this. What data is being generated and what value can the data provide on top of that?

Brian Phillips: Each treatment that is being delivered with one of these machines has a different setting – energy, density, and depth. Each machine has a different variable. When you can see something as simple as the number of procedures occurring, that is helpful too.

Let’s say you are the manufacturer and you have a team of sales reps across the country. The salesperson drives into the city that day to sell new systems or to meet with existing doctors that he sold systems to.

If they want to understand the volume that has occurred over the last month, they could just pull up the MedShift application or utilize the data that we send over to the manufacturer from our platform. They can have a real-time view of procedure volume.

They could understand the difference between one plastic surgeon and the number of procedures that their device is being used for at one office versus another office. They can use that information to guide their business. Maybe they would see the busiest doctor first because they know that the machine has been making them a lot of money.

When they go in, they will be very happy. Maybe they sold a system to a different doctor, and it’s not being utilized at all. So, the salesperson’s behavior and the methodology that they go in with is going to be different because they have the underlying data set. In the past, they would not know and they would just go about their day without the key information. 

Sramana Mitra: Sales and customer support use cases are the two that you talked about. I want to point out something. This is not big data. This is data analytics. Our definition of big data is something that involves machine learning and data at scale. This is not huge amounts of data. 

Brian Phillips: In that scenario, you are right. We have a different version of our IoT product – a different form factor that patents are being filed on right now. This would apply to the scenario and the definition of big data more specifically. I can have a follow on after the patents are in, but I can’t be too specific about it right now. 

This segment is part 2 in the series : Thought Leaders in Healthcare IT: Brian Phillips, CEO of MedShift
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