Data Governance for Software as a Medical Device (SaMD)

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What is data governance?

Data governance refers to the overall management, accessibility, usability, security and protection of data within an organization. This includes the policies, procedures, and standards put in place to oversee proper data handling from creation to deletion.

Data governance is critical in Software as a Medical Device (SaMD) products because it supports the integrity, accuracy, and security of data used in life-critical applications, enabling compliance with regulatory standards while fostering trust in the software’s performance. A well-executed data governance plan is critical for products like digital diagnostics, digital therapeutics, imaging analysis software, and clinical decision support software (CDSS), some of which use Artificial Intelligence (AI)/Machine Learning (ML) and/or novel algorithms; these products rely on accurate, consistent, and secure data to deliver reliable and effective outcomes for patients and healthcare providers.

Why is data governance important?

Key reasons to have a robust data governance strategy include:

Patient Safety

Accurate and well-governed data ensures that recommendations, therapies, or interventions are based on correct and up-to-date information, minimizing risks to patient health.

Regulatory Compliance

Digital therapeutics and clinical decision support software are often subject to stringent regulations (e.g., FDA, MDR, GDPR). Data governance helps secure compliance by managing data integrity, privacy, and security, which are critical for audits and regulatory reviews.

Trust and Credibility

Healthcare providers and patients must trust that the software’s recommendations or outputs are valid and unbiased. A robust data governance framework helps build this trust by confirming data quality and traceability.

Interoperability and Scalability

These products often integrate with electronic health records (EHRs), wearables, or other health IT systems. Data governance establishes consistent data formats, standards, and definitions, enabling smooth integration and scalability.

Algorithm Advancement

A robust governance framework provides transparency regarding AI/ML algorithms, providing evidence that they are free from unintended bias, and their decision-making processes are traceable. This fosters user trust, supports continuous improvement of algorithms, and ensures compliance with regulatory requirements for accountability and safety.

Ethical and Privacy Concerns

With increasing reliance on patient data, governance outlines methods for ethical handling of sensitive information, protecting privacy while enabling innovations like AI-driven recommendations.

Improved Outcomes

High-quality data enables these products to make accurate predictions, offer effective treatments, and provide actionable insights, aimed at improving patient outcomes and reducing healthcare costs.

Key elements of data governance include:

Data Stewardship
Data management that oversees specific data assets including the acquisition, storage, deidentification, and procedures for the use and release of data.
Data Quality Management
The set of policies and technologies that confirm data is accurate, consistent, and complete.
Data Security
Policies that protect data from unauthorized access and ensure privacy compliance.
Access Controls
Processes that limit who has access to data and resources.
Compliance and Risk Management
Data management is aligned with regulatory measures and industry standards.

How does data governance apply to Software as a Medical Device (SaMD)?

Robust data governance and policies are key to developing a reliable SaMD. Both the Federal Drug and Food Administration (FDA) in the US and the European Union Medical Device Regulation (MDR) in Europe present guidelines and policies to advance medical technology through data governance compliance. Within the EU, different regulatory bodies may have additional requirements for data governance of SaMD to allow reimbursement, especially those considered digital therapeutics.

Companies should set forth a strategic framework to manage, protect, and use the data effectively. It is essential to define the roles, responsibilities, and access controls to maintain data integrity and regulatory compliance.

Plans should be developed to protect the reliability of the data in all stages of medical device development, including post-market surveillance. By employing robust data governance practices, SaMD manufacturers can improve data consistency and integrity, providing a consistent source of information for health and product improvements.

Why Choose Innovenn for Data Governance in SaMD Development?

At Innovenn, we understand that data governance is more than just a compliance checkbox, it’s the backbone of a successful SaMD product. SaMD development demands a unique combination of technical, regulatory, and ethical expertise to ensure data integrity, security, and usability. Our team brings decades of experience and a proven track record of guiding clients through this complex landscape.

To learn more about Innovenn’s Data Governance in SaMD consulting services, contact us to discuss your specific needs.

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