A Look at the Evolution of Remote Monitoring for Medical Devices
What we refer to today as IoT (Internet of Things) was coined in 1999, however, the vision actually began back in the 1800s. The telegraph developed in the 1830s and 1840s was described as “wireless telegraphy.” The first radio voice transmission occurred in 1900. The evolution continued with the development of GPS satellites and other defense programs. The vision of connecting and collecting data to drive insights and decisions has been in the front of mind for centuries and will remain for decades to come.
The ability to remotely monitor medical devices is a topic that has evolved greatly over the past 20+ years. The scope of monitoring devices and digesting machine data can vary from clinical information, patient data, machine performance data, utilization, and the ability to piece many of those data points together to create a holistic outcome for both the patient and customer.
Speaking from my own experiences, I remember being a field engineer in 1999 servicing cancer diagnostic equipment. Around that time, we ventured into a relationship with a company called Axeda later to be acquired by PTC, which many of you will recognize. This was a groundbreaking and exciting time where we began utilizing machine sensors and connectivity to detect failures or disruption with our machines. The device’s onboard operating system was Windows and through Axeda we were able to take remote control of the instruments and perform onboard troubleshooting. This was over 20 years ago, and for us, this vision was that this technology would get us over the reactive curve and well on our way to be a proactive service provider. Looking back at this today, we were only scratching the surface in overall capabilities, but having the ability to remotely pull logs and navigate the system remotely had great benefits for the time. Those initial abilities still reduced truck rolls and began us on our journey of becoming more efficient and productive.
Fast forward to the present where we now have the ability to leverage IoT technology and greatly impact the outcomes for our service businesses and customers. In this article, I will examine the progress we’ve made in predictive maintenance and share where we can go in the future.
Moving Away from Time-Based Maintenance
Let’s look at the automotive industry for a moment. Not to simplify an automobile, but regardless of pricepoint, most cars will tell their driver a few critical data points proactively by use of sensors to help prevent an inconvenient failure or put the driver and their passengers in a dangerous situation. Tire pressure is one good example of a predictive alert telling a driver to check their tires before heading out or to pull over safely before experiencing a complete flat. Another example of an important alert is when it’s time for maintenance. Some cars at 3,000 miles, others at 10,000, regardless of the limit, the car measures usage and gages the time maintenance is required by that usage. This is far more efficient than telling a driver that they need to get an oil change every six months. Not all drivers are alike, not all drivers drive the same distances, hence their automobiles will require maintenance at different intervals.
Let’s now take that maintenance example and apply it to medical devices. The majority of medical devices today and historically do not tell a customer when maintenance is required. The majority of the time it’s the OEM who manufacturers the device that establishes the preventative maintenance (PM) cycle. It may be once a year at the six-month mark, or twice a year, or quarterly. The PM cycle has never been established by the usage or throughput of the device, but instead a simplistic gauge. This doesn’t necessarily work, because just like cars, not all medical devices are used the same. They are not all used in the same environment, they all have different operators and different utilization.
Becoming Predictive is Possible with New Technology
With today’s technological advancements, medical device manufacturers can now change the landscape of how maintenance cadences are established. By leveraging device connectivity (IoT), asset management machine data, and AI the OEM can now alert the service organization when a PM is due based on device usage. This capability will have a dramatic impact on the continued increase in uptime, customer satisfaction, cost containment for the OEM, and positive revenue impact for both the end customer and OEM. The implementation of this capability in the medical device market will be a game-changer.
Where predictive truly comes into play is when a manufacturer can truly predict when a machine or device will fail before it happens. The entire objective around being predictive is to prevent a catastrophic failure before it has the chance to disrupt an operation or as in healthcare, delay or interrupt a diagnosis or procedure for a patient. There are medical device companies in the market today that are now well on their way to becoming truly predictive.
A ServiceMax customer now has the ability to utilize machine data through sensors and historical data points to predict the failure of a CT tube weeks to months in advance. This capability to prevent a CT from going down could prevent an ED from going into bypass, which means shutting down and diverting patients who need their care. Instead, through these predictive capabilities, this customer can now identify potential failures ahead of time and take the customer down at their convenience to conduct a repair that typically takes eight to twelve hours to complete. Capabilities like this save the customer time, prevents significant loss in revenue, and most importantly allows them to deliver a higher level of patient care. For the manufacturer, these capabilities help in driving down costs in expedited parts, overtime expense, and in the end, drives up customer satisfaction. That in turn will drive revenue up for the manufacturer as these remote predictive capabilities could be leveraged as a premium service offering, creating new revenue channels for the service business.
Remote Connectivity Is the Next Step for Big Savings
On the cost-saving side for the manufacturer, remote connectivity on software-based products has a dramatic impact if your system allows you to upgrade software or firmware remotely. In my experience, having this capability to upload a software upgrade remotely on an install base of 500 devices saved the business over $1M in potential cost. The ROI in these cases is massive and this is just one upgrade. In my experience, you can potentially launch two to three upgrades annually. This of course is for proactive upgrades, but also plays a role in remote repair. If it’s found that software is corrupt or firmware needs to be upgraded or refreshed, being able to do that remotely is highly efficient and reduces cost dramatically. Through connectivity, we should be able to manage all software-related troubleshooting and corrective action remotely. This means you can send field engineers only to critical events that truly require on-site service, thereby reducing truck rolls and improving productivity in the field. This allows a service business to reduce costs, repurpose teams to more critical work, open capacity, and drive an overall more efficient organization.
Stayed tuned for my next article where I will dive into the advancements we’ve made in supply chain and remote service.
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