Get ready for a deluge of health data. The market for bedside monitors, remote health trackers, wearable medical apparatus and digital consumer devices is exploding. And that’s not even counting information collected from critical care instruments or paper questionnaires that most patients are still required to fill out prior to an appointment.

On the one hand, it’s great to have more information to use in diagnoses and treatment plans. On the other, that surge of different readings is now more a cacophony than a symphony. The instruments don’t use a common technical language, their signals sometimes conflict with one another, and their indications can be inconsistent. So, while the promise of detailed, real-time information to guide patient care may be the holy grail of medicine, it is today closer to a Tower of Babble. And it’s about to become more complicated.

That’s because, even with its shortcomings and confusion, the value these devices bring to the practice of medicine is both large and growing. In 2016, spending on medical devices and in vitro diagnostics totaled $173.1 billion, or 5.2% of total national health expenditures, which is actually a little below par. During the period from 1989 to 2016, it ranged from 5.4%–6 % of total national health expenditures. But the prices for digital medical devices, like most consumer electronics, have actually grown much more slowly than the Consumer Price Index, meaning that the medical electronics industry is likely to see significant new growth going forward, propelled by the combination of rising chronic disease incidence along with the greater use of medical imaging, monitoring, and implantable devices—together with an increasingly older population.¹

Equally significant is that the proliferation of technologies included in the medical electronics category is not restricted to hospital settings. Satellite centers, free-standing clinics, urgent care providers, doctors’ offices and patients’ homes are all getting fitted with monitors, analyzers, electronic devices, and an assortment of machines to check vital signs and provide specialized care. Their promise is significant. Not only do they collectively hold out the possibility of better, more timely care for patients, they even have the potential to replace a significant portion of the effort now provided by overworked medical professionals.

Back to Babble

Along with that growth, however, comes a series of complex issues reflecting the eclectic assortment of sources and types of devices in use combined with the heterogeneous network infrastructure that connects them to one another and to the healthcare personnel who need that information. Particularly in the case of large hospital systems with multiple owned and affiliated units, supporting the mix of physical and virtual networks, systems, data centers and applications while maintaining visibility into the full network, is a huge challenge. Even with today’s high-performance delivery, analysis and management software applications in place, only limited visibility is available, and performance is often degraded. Part of the problem, of course, is the exploding volume of network traffic. But another is that many of the applications were custom built and don’t lend themselves to current monitoring methods.

For example, one healthcare delivery system that had expanded through acquisitions and the addition of new affiliates, inherited a mishmash of complicated network infrastructure that didn’t have enough visibility to understand what was happening across it. It included different data centers, application tiers, and proprietary programs that system administrators just couldn’t monitor. Blind spots in the organization’s cloud infrastructure meant that IT personnel needed a lot more time and resources to isolate, prioritize and fix problems.

Cook Children’s Healthcare in Fort Worth, Texas experienced a similar situation. Over time, it had created a system with problems ranging from slow user responses and difficulty monitoring the network, to the inability to proactively identify potential performance issues. So Cook Children’s needed a way to realize their systems’ full potential. But in both cases, the solution to diagnosing and eventually solving their performance problems involved untangling their jumble of technology, policy and business issues.

A concern affecting many healthcare providers who are seeing biosensors, wearables and mobile applications coming into their professional landscape is that in many cases, the data had been operating in their own silos, such as nursing stations, backend servers, or within the devices themselves. But fragmented, Balkanized, and disjointed data sets are unhelpful. Interoperable data is critical both to improving the future of healthcare and to reducing its costs. But part of the shift from wired to wireless medical instruments has involved multiple devices, using different protocols, sharing the same radio frequency spectrum. That can lead to occasional communication failures, sometimes resulting in grave errors during life-critical incidents. And no protocol today covers the operating demands presented by multiple IoT devices.

Cybersecurity and privacy risks, as well as vulnerabilities that healthcare providers may or may not be aware of, can result. But for regulatory bodies like the FDA, they are a top concern. A smart medical device may need to interface with an assortment of technical protocols before it can perform reliably. As a result, leading companies are integrating their resources to make sure their products work robustly and securely in different situations, all while complying with strict medical regulations.

The Critical Test

Doing so is about to become both easier, although in some respects also more complex, as new technologies emerge and become integrated into the healthcare arsenal. One of the most significant involves 5G wireless networks, which are designed to be capable of handling vastly more data at very low latencies. At least in theory, as electronic monitoring devices continue to proliferate, that capability provides an ideal fit. In addition, new standards for massive machine-type communications, or mMTC, as well as others which apply to ultra-reliable low latency for all Internet of Machine Types, will help IT administrators sort out the welter of signals now crossing healthcare networks.

However, success isn’t guaranteed. The ability to succeed in the face of complexity shouldn’t be taken on faith; it requires a robust protocol of testing to confirm that its hardware, communication solutions, battery life, security, and other technical aspects work as intended. Each needs to be tested separately as well as together to verify that they can withstand the rigors of the environments in which they will need to operate. Whoever is assigned to their support once installed, must be able to monitor the devices and discover any failures before they actually occur. In addition, test equipment and software must evolve in close collaboration with the industries whose instruments it covers. Doing so benefits the healthcare and testing industries, driving greater insight and credibility into healthcare and into the market demands that drive their offerings.

Reference

1. Donahoe, G. (November 2018). “Estimates of Medical Device Spending in the United States.” Advanced Medical Technology Association. Retrieved from https://www.advamed.org/sites/default/files/resource/estimates_of_medical_device_spending_in_the_united_states_november_2018.pdf