Leveraging predictive analytics

With the increasing number of connected medical devices, remote device monitoring has become a strategic area of focus for MedTech organizations to optimize the operational costs of devices in the field. Medical devices require remote device monitoring, and updates to ensure devices are working as desired, device health is a field that should receive more attention from all healthcare entities, including device manufacturers as well as payers and providers. As the industry is in constant demand to adopt emerging technologies to improve overall clinical outcomes and customer satisfaction, having a strategy in place to help providers maintain or upgrade medical devices appropriately will support an ongoing relationship between all parties. 

Traditionally medical device maintenance is driven by on-premises maintenance of devices by field service engineers. However, with adoption of connected medical devices, healthcare providers have been seeking ways to rapidly change that approach, which opens the door to make device maintenance a strategic imperative within organizations. Medical device organizations not only want to remotely manage their devices but also want to ensure they can service the devices even before they fail – or provide recommendations regarding available upgrades. 

Addressing Medical Device Maintenance Challenges 

To become a true strategic partner, medical device organizations must first assess how they can evolve their maintenance processes to use technology and predictive tools most effectively. To begin, there must be an underlying understanding of when a device is trending toward a possible failure. By incorporating predictive analytics into servicing strategy, medical device organizations can reduce the number of times a field service engineer must visit provider sites to perform a thorough analysis of the device. This approach will only improve the quality and reliability of the device itself but extend its “life” and provide additional safety and improved performance. Further, through the adoption of innovative technology solutions, medical device organizations can reduce field service visits by up to 20% while achieving significant savings due to proactive maintenance of devices. 

Introducing predictive strategies into medical device maintenance processes can also have a positive effect on compliance with industry regulations related to patient safety. Predicting device failure can help organizations anticipate and address possible safety risks and anomaly detection before they make a larger or more critical impact. 

AWS also provides managed solutions for addressing the needs of predictive maintenance of devices. AWS Monitron can capture data from medical equipment, securely send the data to the cloud, and analyze the data for anomalies using machine learning. AWS Monitron includes hardware as well as software solutions: sensors, gateway, anomaly detection service, and mobile app for analytics and real-time alerts. 

Using data to effectively drive proactive maintenance depends on the mix of device and operational data currently being generated by medical device service teams and medical providers. Most data will fall in one of two categories: 

• ShapeStructured Data: The year of production, make, and model of the device, warranty period, machine utilization, inventory, CRM, etc.
• ShapeUnstructured Data: Maintenance history, device or logs, temperature, flow pressure, coolant levels or other sensors data. 

By combining the two types of data into highly customized predictive algorithms, medical device companies can identify devices showing deviation from normal behavior based on their age, service history, use and more. Predictive analytics solutions can provide device health alerts days, weeks, or even months before actual failure. 

The devices that require maintenance can be proactively scheduled for servicing before they go offline and cause the medical provider unanticipated downtime. In addition, medical device organizations can improve field service engineer’s efficiency by providing them AI-enabled service assistant tools. 

An added benefit to proactive maintenance is that medical device organizations can help optimize inventory levels of spare parts stocked at facilities. By integrating data from operational systems such as enterprise resource planning (ERP) or inventory management systems, a device organization can limit inventory tie-up while ensuring out-of-stock parts does not occur. 

The Way Ahead for Medical Device Maintenance

Medical device organizations need to create a unified device data platform to act as a single source of truth across devices that combine device, clinical and operational data. Once the unified data is available, organizations will be able to generate business insights and understand trends (utilization, downtime, labor cost, shipping cost, etc.) to drive proactive maintenance of devices. 

Dhaval Shah is senior vice president and head of the medical technology market at CitiusTech. He has over 18 years of experience in IT outsourcing, with a strong focus on the US healthcare market and holds a Masters degree in Bio-Medical Engineering from Wright State University. 

Dr. Simran Mittal is the consulting head of the medical technology market at CitiusTech. She has over 13 years of IT experience and has an MBA from Tata Institute of Social Sciences in Mumbai, India.