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Why Interoperability Is Crucial to Medtech’s Survival

lens of a microscope placed over a slide containing a medical sample

The consequences could be dire. In Germany, like much of the world, health systems perform rigorous cost-benefit analyses before signing off on new medical device and technology purchases. The intense scrutiny, combined with emerging business practices and innovation models, is slated to force some medtech companies out of competition altogether. Those that remain understand that gaining an edge in the market requires more cost-efficient, more clinically effective medtech solutions. Time and again, we find, that means integrated data-driven solutions, straight from the manufacturer.

In short, medtech companies that fail to build impressive data elements into their solutions could also fail to stay viable.

But what does a successful data component look like in a medtech solution? The answer is the same set of characteristics that are improving clinical care in Germany and the world over: the power to turn enormous quantities of information into healthy data and the kind of interoperability that can breakdown stubborn data silos. Medtech companies that will survive and thrive in this new world will build their life-saving solutions on an interoperable data platform.

More Data, More Opportunity

In the next five years, the world’s data stores are expected to jump from 33 to 175 zettabytes, according to the IDC white paper “Data Age 2025.” Healthcare, whose data supply is projected to climb by 10 percent, will ride a flood of wearables, genomic, and diagnostic imaging data to be among the top growth industries.

The effects are already visible in healthcare specialties like radiology, where the sheer mass of medical data can’t be analyzed and managed without intelligent data technology. But if medtech companies get it right, the influx of data won’t be a problem. Unlike humans, after all, technology works exponentially more precisely and reliably when fed greater amounts of information. All this data could mean better care.

Success, however, hinges on adaptation. Medtech companies and their healthcare providers must establish interdisciplinary teams, recruit experienced big data professionals, and execute better data networking and analysis, according to a 2019 Capgemini study titled “Intelligent Technologies.”

At the heart of this evolution is the availability of normalized data, or what we call, “healthy data.” Information isn’t any good—in fact, it can be detrimental—if it’s messy and unusable. Medtech companies will position themselves for victory when they institute a strong coordinated data management program, built on a solution that reconciles the orchestration of big data with patient well-being and client financial goals.

Interoperability and Data Management

The next key to medtech success is simple but imperative: Removing data silos is vital to any agile digitization process. Whether it’s a new system or device or a legacy technology, medtech solutions must encompass the ability to transfer information among all integrated sources. When data is trapped in one place, patients and clients lose out on its clinical and financial benefits.

Interoperability, of course, depends on forward-thinking software. This includes systems that seamlessly support current standards and profiles, like those produced by IHE, HL7 and FHIR, and DICOM.

From there, medtech companies and healthcare providers can pursue higher aspirations. Pioneering artificial intelligence applications, for instance, can use their speed and precision to deliver targeted support to physicians. But the aptitude of AI and machine learning will always depend on the quality and seamless exchange of the underlying data.

Optimizing Medtech for a New Kind of Care

Medtech’s data evolution comes down to the sort of scalable, comprehensive, interoperable data platform that fuels an agile data management program and fosters in-depth analysis. InterSystems IRIS for Health, for example, gets the job done by facilitating and accelerating the development, provision, and maintenance of real-time, data-intensive applications. I’ve seen medtech companies use IRIS for Health to bring new innovative services to market, opening new revenue streams and improving interactions between physicians and patients. The ability to innovate through AI and big data stems from the solution’s proven knack for supporting interoperability and multi-model databases, two central building blocks for managing heterogenous data flows.

Medtech companies that ignore data will suffer in a consolidating market. Those that prioritize interoperability and healthy data will boost the value of their solutions and their organizations. More important, they will create a more effective healthcare system for physicians and patients alike.

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