This extract is part four 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.
In the context of smart connected patient devices, this layer is crucial for safeguarding sensitive health information, ensuring regulatory compliance, and maintaining the integrity of data for clinical and operational decision-making. Strong governance policies are essential for building trust with healthcare providers, patients, and regulators, while creating a reliable framework upon which data analytics and business applications rely.
Data governance provides the structure — through policies, processes, and practices — that ensures the availability, security, integrity, and compliance of data across the organization. For medical device vendors, this is especially critical due to the strict regulatory environment and the sensitivity of the data being handled.
Ensuring regulatory compliance and risk mitigation
One of the most critical aspects of data governance for medical device vendors is ensuring compliance with stringent regulatory frameworks globally, such as the FDA’s medical device regulations, HIPAA in the U.S., and GDPR in Europe. These regulations set strict guidelines on how healthcare data must be collected, stored, and shared. Non-compliance can result in significant penalties or even product recalls.
As John O’Gorman, Principal Technology Officer at S3 Connected Health, explains: “Regulatory and notified bodies need to know that companies are building safe systems that mitigate harm to their citizens. Both Europe and America have laid out quality-based guidelines for AI and machine learning that can be used to ensure the risk of harm is appropriately managed when building medical devices.” The rapid evolution of AI and machine learning is outpacing regulatory frameworks, which adds further complexity to managing data governance.
Recent regulations, such as the EU Data Act and existing rules like GDPR and HIPAA, intensify scrutiny of data handling practices. This regulatory landscape presents ongoing challenges for companies.
“The biggest hurdle remains the regulatory landscape, especially with recent developments like the EU AI Act coming into effect. Regulations like GDPR and HIPAA outline strict rules on data handling and privacy. Navigating what data can be collected, how it’s stored, and ensuring it’s safeguarded from cyber threats are constant challenges that drive up costs. It requires a tailored approach to determine each project’s specifics — what data we’re gathering and how we handle it technically.”
Aghogho Ekpruke, Research & Development, Medtronic
This evolving landscape requires medical device companies to stay agile in their governance practices. A strong regulatory compliance framework helps organizations manage risk, adhere to legal requirements, and ensure that devices remain effective and safe throughout their lifecycle.
Building trust with patients and healthcare providers
Effective data governance is essential not only for regulatory compliance but also for building trust with patients, healthcare providers, and regulators. Data security and privacy protections must be robust, especially since medical devices often generate continuous streams of sensitive health data. By ensuring that data is handled responsibly, companies can foster confidence that patient information is protected and used ethically. By adhering to the principle of using the minimum necessary data, companies can comply with regulations and demonstrate to patients that their data is handled with care and respect.
“It’s essential to have a clear regulatory plan that ensures all necessary elements are covered. This includes verifying that your data collection is justified and has the right permissions. You need to think about how data can be shared in a compliant way, often using the minimum amount of data necessary to reduce risk.”
Paul Stevens, Director of Digital Health at Omron Healthcare Global
A transparent and well-structured data governance strategy enables medical device vendors to gain patient trust, which is crucial for collecting the necessary data to drive insights and create value. Building applications on top of trustworthy data further enhances the value provided to patients and helps improve patient outcomes.
Key functions of the data governance layer
Data stewardship and ownership
Establishing clear roles and responsibilities around data management is essential. Data governance assigns ownership for data quality, security, and access across departments, ensuring accountability at every stage.
Example: For a portable glucose monitoring device, the clinical team may be responsible for managing patient data, while the IT team ensures secure storage and transmission.
Patient consent and data sharing
Medical device vendors must implement robust consent management processes that comply with regulations such as GDPR. Patients need control over how their data is collected and shared, and companies must demonstrate that data use is justified, ethical, and compliant.
Example: A wearable ECG monitor company must obtain patient consent and ensure data is shared only with authorized clinicians, maintaining HIPAA compliance throughout the device's lifecycle.
Data integrity and quality management
Data governance ensures that data remains accurate, complete, and reliable. In the medical device industry, poor data quality can lead to incorrect insights and unsafe clinical decisions, jeopardizing both patient safety and a company’s reputation.
Example: For an implanted cardiac monitor, governance ensures that data is validated, preventing any faulty readings that could mislead healthcare providers and harm patients.
Data security and privacy
Ensuring the security of patient data is paramount. This includes using encryption, access controls, and secure transmission protocols to protect data from unauthorized access and cyber threats.
Example: An insulin pump transmitting real-time data must ensure that all communications are encrypted, protecting the patient’s health data from potential breaches.
Data lifecycle management
Governance defines how data is managed throughout its lifecycle, from collection and storage to archiving and disposal. This is crucial for adhering to regulatory retention policies and ensuring data is securely deleted when no longer needed.
Example: A portable dialysis machine that generates large amounts of data during treatment must follow governance policies to ensure this data is either archived or securely deleted after the retention period ends.
Auditability and traceability
Governance ensures that all data-related activities are logged and traceable. In the medical device industry, this is vital for regulatory audits and ensuring accountability in case of data breaches or device malfunctions.
Example: A company producing implanted neurostimulators must maintain an auditable trail of all device data, from performance metrics to patient interactions, to comply with FDA guidelines.
Challenges and considerations
While essential, implementing robust data governance comes with several challenges that medical device companies must address.
Balancing security with usability
Strict governance protocols may limit data accessibility and flexibility, making it harder for stakeholders such as clinicians and internal teams to use data effectively. Striking a balance between security and usability is a constant challenge.
Evolving regulatory landscape
Companies must keep up with changes in global regulations such as GDPR and the EU AI Act, which may differ by region. This requires an adaptive approach to data governance practices.
Data fragmentation
Data generated by medical devices often resides in multiple systems, from cloud storage to hospital databases. Ensuring a unified governance strategy across all data systems is critical to maintain data integrity and avoid inconsistencies. Leaders and operational teams can use the insights to make informed decisions.
Managing real-time data
The real-time nature of data generated by connected devices demands governance policies that ensure compliance and security in real time. Automating governance processes becomes increasingly important as the volume and velocity of data grow.
The data governance layer is the backbone of responsible and compliant data management in the medical device industry. It ensures that sensitive health data is securely managed and complies with strict regulatory frameworks and builds the trust necessary for patients, clinicians, and regulators to rely on these devices.
A well-implemented governance strategy enhances data quality and reliability, allowing organizations to leverage data for clinical insights, operational efficiency, and product innovation. Maintaining agile and robust governance practices will be crucial for success as the regulatory landscape evolves and data generation increases.
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:
