5 critical considerations for connected health manufacturers

The hospital of today bears little resemblance to its predecessor of just a few short decades ago, with internet-enabled medical equipment and devices now a central part of diagnosing, treating, and monitoring patients. 

While these technologies have significantly improved the standard of care, they also introduce a range of challenges for healthcare practitioners, administrators, and patients. 

The good news is these issues can be mitigated, or, in some cases, eliminated, in the engineering and design phase.

With that in mind, the following are five important considerations for manufacturers to support connected healthcare’s continued acceleration:

Address security vulnerabilities

According to one study by Cynerio, 53% of connected medical devices contain critical vulnerabilities that threaten both patient privacy and patient safety. 

Healthcare institutions are aware of their presence in hackers’ crosshairs, but often overlook upstream supply chain weaknesses when it comes to bolstering device security. 

These flaws are typically hidden deep inside the protocol stacks on embedded systems from third-party manufacturers. Consequently, they are often undetected in security scans and subsequently make their way into devices in production—enabling hackers to bypass onboard security controls and crash, deadlock, or freeze a device.

To combat these threats, device manufacturers must implement a comprehensive testing mechanism called protocol fuzzing. 

The process injects various errors into a communication exchange to confuse the entity at the other end of a connection and enable teams to identify protocol-level vulnerabilities. 

It is also a best practice to integrate protocol stress testing into the overall cybersecurity validation strategy to prevent device hacks on an ongoing basis and ensure that patient privacy and safety are protected as connected health innovations are introduced.

Ensure a positive user experience

Addressing user experience concerns is another critical step in supporting connected health’s ongoing innovation. This can be challenging from a testing perspective, as there are typically many different users for a given device or application.

Hiring numerous testers to manually test and validate performance is a costly, time-intensive endeavour that fails to account for the different user demographics that will be interacting with the technology daily. 

Often these users aren’t trained medical personnel but the patients themselves, meaning that the user profiles span a range of ages, backgrounds, and degrees of technical savvy. 

Also, users often expect healthcare applications to run correctly on a variety of physical platforms and operating systems. Just think of the many varieties in desktop and laptop computers, tablets, phones, and even smartwatches as well as the different operating systems that support them.

For these reasons, a better approach is to use AI-driven test automation to evaluate the user experience. Software-based solutions can find more paths through complex applications and test all possible user journeys.

In addition, they can deliver results significantly faster than traditional testing and automatically focus more attention on testing areas where defects are prevalent, ensuring manufacturers deliver an effective, safe, and efficacious device to all user segments on time.

Select the right battery

While their specifications may say otherwise, not all batteries are the same and picking the wrong one can curtail a device’s lifespan and overall capabilities. 

To make sure the right battery is selected, use emulation software to create a profile of actual batteries. These profiles can then be imported and used in tests without any involvement from the physical counterparts. Teams can measure and record battery conditions as the charge is depleted, better understand battery behaviour, and use these insights to determine which battery is best for the device at hand.

Ensure signal integrity even with increased data processing

Increased data processing in connected devices can present signal integrity challenges, and these are exacerbated as new health innovations are rolled out. 

Crosstalk from adjacent traces, boards running at lower voltage levels, and more onboard processing are just a few factors that interfere with the quality of electrical signals.

Because the efficacy of smart health devices is heavily reliant on signal integrity, it is important that manufacturers overcome any issues.

A good first step is using software emulation tools to identify and eliminate any issues before fabricating the board, saving time and money. Another best practice is documenting learnings in the quality management system to reduce risk and get to market faster with future designs.

Reduce measurement errors to make better decisions

Finally, it is critical that manufacturers address drift to ensure they are continuously able to make consistent, accurate and repeatable measurements.

Regular and proper verification is essential for making sure instruments are accurate, that they are operating within specifications, and that they have traceability backed by certification. 

In addition, regular calibration also enables teams to reduce work, avoid delays, and ensure that connected health innovations deliver maximum value to patients.

Connecting to the needs of tomorrow

We can only expect connected medical devices to grow more complex in the years ahead and, along with them, their path to the marketplace. That is why it is imperative manufacturers recognise security, usability, battery life and other connected healthcare considerations must be addressed during the design phase. 

Organisations that re-engineer their workflows, as needed, will be best positioned to develop safe, efficacious, and intuitive technologies that have market staying power.