I read this article in IoT World about connected health trends to keep an eye on for 2019. It talks about use cases for AI such as wearables, patient dashboards, surgical robots. It talks about some VS guy who a few years ago said that AI can do 80% of what doctors can do and that radiologists would be obsolete by 2022!
The overall progress of AI adoption in healthcare has been really slow. It seems to me that so many companies are trying to develop AI solutions for applications and use cases that are just too complicated or rely on an ecosystem of other technologies to make them happen.
We need to stick to the basics. No tech project or initiative will be successful unless there’s a business case to drive it. And in healthcare, the obvious business case for AI starts where IoT did: service and support.
Companies trying to deploy an IoT technology so they can remotely support their devices in the field are certainly still facing challenges today. More and more of their end users, particularly overseas, are resisting their attempts to connect to their devices on their network because of security concerns. But the business case for remote service and support still is strong. Reducing downtime, reducing 2nd service calls, improving MTTR and FTF rates still translate right to the bottom line for OEM’s and their customers.
AI for healthcare should start here. There are AI technologies available today that can help service and support organizations improve their support capabilities even further. Some of the benefits that you can get from AI today:
-Upskilling the service organization by making your service rookie as smart as your veteran;
-Automated dispatching so that experienced techs don’t have to spend time on the phone;
-Enabling connectivity to devices without relying on the customer’s network
-Dramatically reduce 2nd service calls
There are many others. And if you’re a radiologist, don’t worry – your job is safe!