How Software Will Kill or Save Medical Devices

Posted in Mobile Health by Brian Buntz on February 13, 2014

Don't think your medical device company is facing a BlackBerry-like crisis? Think again.

In the same way that smartphones quickly made digital cameras, GPS systems, and even the "CrackBerry" obsolete, the digital health industry could ultimately replace half of traditional medical devices, says Shahid Shah, CEO of Netspective Communications.

Shahid Shah
Shahid Shah

During his keynote address at MD&M West on February 13, Shah pointed out that this is already happening, as a growing number of diagnostic-grade mHealth devices are hitting the market, and the trend will only accelerate.   

Shah notes that Apple recently met with FDA’s medical device division, and notes that he believes the rumors that the firm is mulling a soft entry to the medical device field. Mobile devices powered by iOS 8 may be a Class I medical device, he says. “What if it is iOS 9? What if they enter the medical device space in three years? We in the medical device space are still dead,” Shah said. 

All is not doom and gloom for device makers, however. The digital communications and Big Data revolutions could end up enabling all kinds of ways to actually ensure that medical devices are helping people versus hurting them; companies just need to get ahead of the curve. 

The future of medical devices may lie in their potential interoperability and their ability to send useful data to connected electronic health records (EHRs). They can also be used as “accountable tech,” Shah notes, serving as helpful tools in showing the value of a device therapy. In the future, medical devices will need to produce and share data to prove their value.  

In as few as three to five years, half of healthcare payments will be based on value, Shah predicts. At present, only 20% are.

Apple iWatch
Recent new hires at Apple—as well as interactions with the FDA—suggest the much-anticipated iWatch will include digital health features.

Also helping to drive the trend of accountable tech is Big Data and the functionality it enables like predictive analytics. Healthcare needs Big Data, which is all about solving big problems, Shah says. And Big Data—and data in general—will become increasingly vital for medical devices. Ultimately, hardware, sensors, and software are temporary businesses but data has long-term value. “He who owns, integrates, and uses data wins in the end,” Shah notes.  

The data from medical devices is too important and specialized to leave to software vendors, service providers, and the like. “Guess who has all of the data that could easily fill most of the EHRs?” Shah asks. “It’s not the physicians hand entering data.” Medical devices and health-tracking technology can accomplish this.


Tech Trends

Shah says the way forward for the device field is to get ahead of three trends: commoditization, consumerization, and workflow automation.

In terms of commoditization, device firms should actively ask how much of what is special in a medical device has been or will be commoditized by consumer technology, including PCs, tablets, phones, and software.

The trend of consumerization dovetails with commoditization. Medical device firms should look for existing consumer technologies that can drive device functionality. “Your mobile phone from three years ago already has more horsepower than you need for many medical device computing applications. ... If you are not watching commoditization, [many medical devices] will be disrupted very easily. All the computing power we need in medical devices exists on the mobile phones of yesterday,” Shah says. “In the future, sensors embedded into smartphones could be used for an array of medical device functions and may not need FDA clearance, given their broad use. 

In terms of workflow automation, Shah stresses the importance of designing medical devices that can fit into the agile workflow of the future doctor. Many clinicians will see growing numbers of patients and confront growing data sets linked to them, so any device technologies that can help automate manually performed tasks or even some amount of rudimentary diagnostics will likely win favor. “In an outcomes focused world, doctors won’t ask for the devices that worked in the past—they will want technology that fits into their new workflow,” Shah says.

Data Trends

The three central data trends that should influence device development efforts are interoperability, connected EHRs, and accountable technology.

In terms of interoperability, clinicians and hospitals are looking for device technologies that can streamline and complement their own data collection efforts.

As for connected EHRs, the federal government is spending billions on the technology, almost all of which is going to a handful of EHR vendors. Shah recommends that the device field tap into this market, as medical devices can serve a valuable role in sending data to them.

Finally, as alluded to before, the debut of what Shah terms accountable technology will ultimately mean that device makers will need to show that their products pay for themselves based on the outcomes they achieve.

Multipurpose Devices with Connectivity

In 2011, Qualcomm Life’s vice president Rick Valencia mused that unconnected medical devices may become obsolete in the future. Shah agrees: single-purpose and multi-purpose standalone devices won’t be purchased when equivalent connected devices exist.

Because of the regulatory timelines involved in producing medical devices that must cleared via the 510(k) and PMA pathways, Shah recommends that device firms create data bridges, such as specified by FDA’s medical data display system, which simplify and present data gathered by another device. The data bridge can then be used to link data from regulated medical devices to EHRs. A data bridge could also be used to help interpret medical device data, although such a system would require greater regulatory scrutiny.

In the longer run, however, analytics will play a vital role in the healthcare ecosystem. This includes predictive analysis of healthcare problems and automated diagnostics that might potentially be offered by systems like IBM’s Watson.

Brian Buntz is the editor-in-chief of MPMN. Follow him on Twitter at @brian_buntz and Google+.