Staying Ahead of a Heart Attack

How can you monitor patient health quickly and accurately? 

A mobile health company that processes EKG heart activity recently realized that they had a problem. Through a MATLAB model via a third-party product, they were responsible for up to 10,000 patients — a number that was growing. They needed to be able to understand how to better scale in the future as new patients register, while at the same time continue to process EKG data daily in a timely and cost-effective manner. This EKG data was crucial to understand as it indicated the future ability to predict a heart attack.

Pariveda was asked to implement a solution that would allow learning algorithms to automate the predictive analytics required to work and scale largely with the high demand the client was experiencing. This was a challenge that the team had experience working through with clients.

Predict your next heart attack

After extensive research, the team at Pariveda was able to identify the aforementioned third-party product as the client's primary constraint to scaling. We tested multiple solution options to determine the best way to scale horizontally, thus overcoming this challenge. Pariveda was also able to provide a total cost of ownership analysis for a new, preferred cloud-based option to highlight how the approach offered cost efficiency that the client had not been able to enjoy up until now. Azure was the natural choice for all of this due to its ability to scale, as well as for how it could reduce the costs for this service. 

An IoT algorithm that saves lives

The client soon implemented the recommended solution and began to enjoy the benefits associated with it almost immediately. Not only were they able to reduce the overall amount of time that it took to process EKG data, but they were also able to reduce hardware maintenance costs as well. All the while, they were able to support the type of efficient scaling necessary to meet the expected increase in both patients and heart activity data moving forward. This efficient monitoring makes it possible to understand and prevent someone from suffering from a heart attack. 

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