How Monitoring Environmental Factors Can Optimize Medical Equipment Performance

Pawan Jheeta
Tuesday, August 28, 2018

Factors like humidity, room or tube temperature, and equipment water flow impact medical device performance more than you may realize.  

We’ve talked a lot about the importance of proactive machine maintenance, AI and machine learning based anomaly detection, and the value of predictive analytics. But what about the external factors, like room temperature or humidity, which could affect the performance of medical equipment?

The quality of medical care begins and ends with the caliber of an organization’s facilities, equipment, and personnel. However, your company could have the best medical imaging equipment in the world, but if conditions aren’t optimized for it to run properly, patient care will be interrupted and revenues will be lost. In order to provide seamless patient experiences and the most effective care, machines must do what they were made to do and run when they are supposed to run. And, even if the equipment is operational, there may be environmental factors that are slowly degrading machine performance. Monitoring machine data analytics and environmental variables can predict failures before they happen and ensure medical imaging equipment is operating within safe and optimized conditions.

This is the first blog in a two-part series. We will kick off the series by introducing Environmental Variable Monitoring (EVM) and use cases. Let’s dive in.

Related: Data Doesn’t Lie: 5 Ways Hospitals Can Use Machine Log Data

What is Environmental Variable Monitoring?

Not to be confused with environmental monitoring for pharmaceuticals, EVM continuously samples environmental machine log data (such as fan speed, air temperature, and more) to provide insights into the external conditions in which the medical imaging equipment is operating. These external conditions are directly correlated to the health of medical imaging equipment. Sensors measure key factors – such temperature, humidity and current flow – and EVM systems instantly notify maintenance teams of any issues and their priority level.

Take chillers, for example. Imaging equipment produces a lot of heat, which can lead to damage if not properly cooled. Chillers use cryogens – substances used to produce very low temperatures, such as helium or nitrogen – to cool components that are prone to overheating. Imaging equipment cannot operate without the temperature regulation of chillers. EVM monitors the operational status of chillers and alerts equipment managers to the issue before it results in downtime. 

Case Study: EVM in Action

On a Friday night before a long weekend, a chiller at a medical facility lost power. Glassbeam EVM reported power issues with a chiller within minutes. The dashboard was updated and alarms were generated, notifying both Glassbeam and the organization’s employees. Within an hour, maintenance teams were dispatched on site to resolve the chiller problems so that the machine would not overheat over the long weekend.

You are probably already beginning to understand the potential cost savings and reclaimed revenues. The next installment of this blog series will take an even deeper dive into the business impact and return on investment (ROI) of EVM. We’ll discuss how root cause analyses can give insight into why a machine breaks down, how EVM can connect imaging equipment and its support equipment (which may be housed in a separate room), how EVM can help turn unplanned downtime into planned downtime, and more. Stay tuned!

Can’t wait for part two? If you’re ready to learn more about how Environmental Variable Monitoring can protect your expensive medical imaging equipment suite right now, reach out to talk to one of our experts in connected devices.  

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