Medical Devices & Electronics
From Insights to outcomes, we aren’t here to revolutionize the Healthcare industry, we’ll let you do that. We are here to help enable opportunities of business intelligence and innovation through the effective use of advanced analytics and big data. This immense complexity confronting the healthcare industry will require smarter, more informed decisions to enable the improved outcomes and better value required by market dynamics, increasing governmental regulation, and today’s more connected patient.
Healthcare organizations around the world are challenged by pressures to reduce costs, improve coordination and outcomes, provide more with less and be more patient centric. Yet, at the same time, evidence is mounting that the industry is increasingly challenged by entrenched inefficiencies and suboptimal clinical outcomes. Building analytics competency to accelerate outcomes.
Here are a few examples where we have expertise and can effective deliver value to your organization.
Medical Device Manufacturers
From MRI machines to pace makers to intelligent pills to wireless glucose monitors, everything in the health care industry seems to be getting connected. All with the goals of building sustainable healthcare systems and improving patient care and outcomes.
If you put a sensor or three on a person you have the potential to easily collect 1 Gigabyte of data every single day. Multiply that by a few thousand people and we’d say you have a big data problem fueled by IoT. Like similar companies and industries who are really good at collecting IoT data, these companies are still developing out the necessary skill sets to harness all that data for their customers and their business. While you could claim that “A big-data revolution is under way in health care”, we at Cyient-Insights believe that a “Smart Analytics revolution is underway in health care”.
At Cyient Insights we have expertise in analyzing sensor data to estimate the health of the devices and predicting the failures of the machines and subsystems. The ability to get warnings before equipment failure helped our customers streamline service operations and increase asset reliability. We have helped our customers in capturing the intrinsic knowledge of seasoned technicians and engineers who repair these devices. Leveraging historical data, we have used association rules mining technique to identify the prominent causes and ways to fix the problems.
Run-to-fail is not a strategy embraced by the medical device industry. Today’s medical equipment and devices offer considerable amounts of data, which when analyzed properly can provide valuable insights into the health of production assets.
Predictive analytics enables better decision making to increase asset reliability to meet the ever increasing and dynamic market demands. Modeling tools produce static thresholds based on design or expected levels, and predictive analytics produce a data model that dynamically changes in response to evolving asset conditions. Due to these differences, they can be highly complementary tools for maintaining asset reliability.