This extract is part two of a five-part series that breaks down the layers of the Data Strategy Framework for Connected Medical Devices, which we introduced in our recent whitepaper. Featuring insights from industry leaders at Cochlear, Dexcom, Medtronic, Omron, Vocxi Health, and S3 Connected Health, the paper offers a practical framework for leveraging data to stay competitive and succeed in a data-driven healthcare landscape.
The business applications layer is essential for organizations to transform data-driven insights into evidence-based decisions that facilitate regulatory approval, enhance market access, boost medical device adoption, and improve other critical aspects of the medtech industry. This layer integrates tools and applications with internal business functions and external systems, converging data analytics to support informed, strategic decisions that lead to tangible business outcomes and patient-centered innovations.
A successful data strategy begins with clearly defined business goals. Establishing these goals is critical; otherwise, organizations risk becoming overwhelmed by data collection without a clear direction. Achieving core elements such as regulatory approval, market access, and device adoption relies on a well-structured data strategy aligned with these business goals. Without clear objectives, data applications can become unfocused, leading to inefficient decision-making and a lack of alignment across teams.
Ensure that business leaders, product managers, regulatory experts, and other functions work closely with data science teams toward shared objectives. Hiring data experts is insufficient; their efforts must align with the broader business strategy. This is achieved through an integrated approach, where every department utilizes the same data, fostering a consistent understanding across the organization. As companies grow, they may struggle to manage data effectively, often neglecting the importance of strategic planning in their data initiatives.
A critical element of this layer is maintaining a single source of truth. This ensures that all teams are working from consistent and accessible data, eliminating discrepancies and ensuring that everyone refers to the same insights and performance metrics. This unity is essential for making informed decisions and driving the organization toward its goals.
“One noticeable gap is that data science teams often receive attention too late, especially as companies scale. Small companies can manage data better because the process is more straightforward, but as they expand, they tend to throw more people at the data problem without a strategic plan, which doesn’t always work.”
Harsimran Singh, Director of Behavioral & Translational Data Science, Dexcom
This function leverages historical and real-time data to accelerate R&D and innovation. Medical device vendors can use product data to identify trends and performance insights that inform future product iterations.
Example: Device usage data from implanted devices can be analyzed to detect patterns, such as battery life issues or signal reliability, which can inform the design of next-generation devices. In the case of continuous glucose monitors (CGMs) combined with insulin pumps, data can help optimize closed-loop
Enable operational functions to optimize their processes using real-time decision support systems. These systems provide predictive analytics to guide decisions, such as when to recalibrate or replace devices.
Example: Real-time monitoring of implanted devices, such as pacemakers, allows the system to detect anomalies and issue alerts for preventive maintenance, helping to avoid device malfunctions and potential market recalls.
Personalized therapy is a growing trend, and business applications help tailor treatments to individual patients based on device data. These applications can ensure that medical devices are optimally configured for each patient and monitor adherence to prescribed usage.
Example: A wearable heart monitor can provide personalized health insights to patients, increasing adherence to prescribed treatments. Additionally, therapy management solutions can monitor patient outcomes and alert healthcare providers if adjustments to the treatment plan are needed.
Beyond product development and operations, business applications provide valuable insights into commercial strategies. These tools help identify unmet clinical needs, customer behavior patterns, and new market opportunities.
Example: Aggregated data from thousands of wearable devices can provide population health insights, allowing medical device companies to identify national trends in disease management and tailor their sales and marketing strategies accordingly.
While the business applications layer offers immense value, it also presents several challenges organizations must navigate to ensure successful implementation and scalability.
The business applications layer is critical in turning data into actionable insights within medical device companies. While challenges such as usability, integration, and scalability must be addressed, the true value of this layer lies in its ability to drive meaningful business outcomes through data-driven insights, enhance product performance, optimize operational processes, and improve patient outcomes.
Check out our recent whitepaper for more information on building an effective data strategy framework for connected medical devices. Featuring insights from industry leaders at Cochlear, Dexcom, Medtronic, Omron, Vocxi Health, and S3 Connected Health, the paper offers a practical framework for leveraging data to stay competitive and succeed in a data-driven healthcare landscape. You can read other extracts in this series to understand each layer better: