This article is based on our recent webinar, "A Winning Data Strategy for Next Generation Implanted and Wearable Medical Device", in which digital health experts from S3 Connected Health, Boston Scientific, Medtronic, and Vocxi Health cover the benefits and challenges of an effective data strategy for medical devices.
Medical devices have evolved significantly from their early days of merely performing diagnoses or treatments. Today, connectivity and data are essential components in enhancing healthcare. Modern devices can automatically collect and transmit data, which helps optimize operations and improve patient outcomes through real-time insights. As a result, companies are moving beyond merely seeking operational efficiency; they are now integrating therapy improvement and connected care into their overall strategies.
When developing next-generation smart medical devices, companies must prioritize not only the physical product but also the creation of a robust data strategy. A well-planned data approach can streamline regulatory approval, enhance market access, boost user adoption, and improve healthcare outcomes. This webinar explored the critical elements of data strategy, highlighting the value of data and its unique challenges.
“The center of the universe for medical device companies for many years was the device itself—the device that generated the data, did the diagnosis, or performed the treatment. But as time has gone on, we've evolved to sending information. Building in connectivity has been one of the biggest changes in healthcare over the last decade. We've added consumer-oriented technology, allowing us to piece together the device and the data it generates, and connect that information so we can actually do something with it.”
Bill Betten, Director of Solutions – Medtech, S3 Connected Health
Today's medical devices offer benefits such as real-time data access and remote monitoring, enabling continuous patient oversight regardless of their location. This connectivity facilitates prompt responses to patient care needs, providing a level of freedom and flexibility previously unattainable. A poll of participants confirmed that therapy effectiveness is one of the core known benefits companies gain from a data strategy. We asked: What benefits can Medtech companies expect from developing a data strategy?
The poll results revealed that 89% of respondents identified this as the primary benefit. However, the panelists were quick to illustrate that, while this is currently the case, the potential of an effective data strategy extends far beyond merely improving therapies. The discussion emphasized that while enhancing healthcare is crucial, there should also be a significant focus on realizing the business potential of connected devices.
However, challenges persist in increasing device sales and generating new revenue from data monetization. Only 21% of participants viewed this as a benefit of a data strategy, while a further 34% and 21%, respectively, identified new revenues from digital services and increased device sales as benefits. This underscores the need for data strategies capable of addressing the challenges of driving new revenues.
“New revenues from data monetization are difficult, in my opinion. It doesn’t mean it won’t happen—I think it will over time. But with the way the healthcare system is structured today, it takes a lot of diligence and work from commercial teams, engineering teams, and marketing teams to address that space. Personally, I see it as a bigger uphill battle.”
Steven Yates, Program Director, Boston Scientific
The promise of smart devices remains substantial, yet many companies tend to overlook the importance of integrating a robust business strategy alongside their focus on therapy effectiveness. This has been a key factor in failures across both the pharma and medtech sectors. As companies are driven by profit and loss considerations, they must also embrace the value equation to sustain long-term success. Startups like Vocxi Health are making strides in this direction by focusing on data-driven approaches. For instance, their development of a breath analyzer to measure lung cancer through unique breath prints exemplifies how leveraging machine learning, AI, and big data can lead to groundbreaking insights. The long-term vision is to create a breath print databank, allowing physicians and patients to access new data and improve diagnostic capabilities.
“Data can help us think about how to treat known diseases in real time and prepare for unknown diseases or COVID-like threats that emerge globally, when we’re not ready but need to understand them quickly. Data is likely the current frontier for medtech, combining the benefits of historical devices with new insights from real-time data. I see this as a major opportunity for the industry, both now and in the long term."
Randy Schiestl, COO, Vocxi Health
There are numerous perceived challenges for companies seeking to develop an effective data strategy for regulated medical devices. Bill Betten highlighted several unique issues associated with implanted and wearable devices. Key considerations include understanding the anatomical location for sensor placement, which is crucial for effective monitoring. Additionally, the distinction between medically relevant data and consumer health data is significant; the focus should be on reliable, normalizable medical data for long-term use. Design considerations are also vital, as devices must evolve to be smaller and more aesthetically pleasing, such as insulin pumps that resemble cell phones. Persistent issues like power management and cybersecurity can further disrupt user reliance on connected medical devices.
In the second poll, participants were asked which areas of data strategy pose the most significant perceived challenges for medtech companies. A striking 74% identified data privacy and regulation as the core challenge, while only 14% saw data retrieval and storage as problematic, indicating that obtaining data is not the primary issue. Instead, 29% of respondents expressed concerns about understanding which data is medically relevant. Furthermore, 36% of participants struggled with leveraging this data and integrating it into a commercialization or business strategy, highlighting a significant gap between data collection and practical application in the medtech industry.
The panelists noted that while data privacy and regulation are critical concerns, medtech companies do understand the processes needed to handle data privacy; the challenge is that it requires ongoing effort to adapt to evolving regulations, akin to "painting the Golden Gate Bridge"—a task that is never truly finished. Data collection has improved significantly, yet the challenge remains in synthesizing that data holistically. The complexity of patient care, where multiple specialists may not communicate effectively, emphasizes the need for an integrated approach across the entire healthcare ecosystem.
“I would say data privacy is something we know how to do; it just takes a lot of work. Regulations keep changing, and there’s all the work you have to do around that. It’s like painting the Golden Gate Bridge—you're never done. There is always a constant new challenge."
Steven Yates, Program Director, Boston Scientific
Additionally, the integration of AI and machine learning into medical technology is still developing, promising significant advancements while also presenting challenges in application. Companies must focus on contextualizing data to improve outcomes for clinicians and patients rather than simply collecting data. The shift toward leveraging technology from other industries, particularly in cybersecurity, is essential to avoid reinventing the wheel. Notably, despite the potential for integration, current medical devices often operate in silos, failing to communicate even when manufactured by the same company. There is a substantial opportunity for the industry to harness data and AI to transform healthcare, moving beyond device-centric approaches to a more integrated model that benefits patient care and enhances clinical effectiveness.
Data alone doesn't add much value; it requires a clear focus on addressing unmet clinical needs, which should guide our efforts. A data-first approach is essential, meaning data should be integral to the development of new devices and solutions, not an afterthought. Adopting a holistic, ecosystem view is necessary to consider how devices fit into the larger healthcare architecture. By prioritizing these elements, we can leverage existing clinical data to enhance efficiency and innovation in bringing new technologies to market.
Developing effective data strategies involves understanding the "why" behind data collection and usage to align with clinicians' needs. The complexity of the healthcare space requires organizations to be adaptable and responsive to clinicians’ feedback. Successful strategies should aim for better patient outcomes and a healthier public, emphasizing collaboration among various disciplines, including clinical, regulatory, and technology sectors, to create a cohesive approach to data use.
"I see that data by itself doesn't add a lot of value; there has to be a desire and a laser focus on addressing customers' unmet clinical needs. That should be the North Star and the starting point. When we approach it from that perspective, we can bring data in as a very useful tool because, in the end, we have to meet those unmet needs—that's what drives willingness from the customer standpoint.”
Aghogho Ekpruke, R&D, Medtronic
For even more insights, you can listen to the full webinar to more about the unique challenges and benefits that data presents for medtech companies. Find out what panelists Bill Betten, Steven Yates, Aghogho Ekpruke, and Randy Schiestl had to say about everything from interoperability to improving patients' quality of life.