Post Market Surveillance, Vigilance and Incident Reporting

Post Market Surveillance, Vigilance and Incident Reporting form a critical part of the regulatory framework for software as a medical device (SaMD). These processes ensure that devices continue to perform safely and effectively after they have been placed on the market. The MHRA and EU regulations place strong emphasis on these activities, particularly for AI-based medical devices. Companies must have systems in place to monitor device performance, identify potential issues, and respond quickly to any incidents or safety concerns.

Post Market Surveillance

Post Market Surveillance (PMS) involves the systematic collection, analysis, and evaluation of data related to the device’s performance and safety after it has been released to the market. For AI-based SaMD, this includes monitoring clinical outcomes, software updates, and any unexpected behaviour. The data gathered through PMS must be reviewed regularly to identify trends or potential risks. The MHRA expects manufacturers to maintain detailed records of surveillance activities, including clinical data, user feedback, and software performance metrics.

For example, a manufacturer of an AI diagnostic tool must monitor how often the software makes correct or incorrect classifications. If a pattern of misdiagnoses emerges, this must be reviewed through PMS. The data must then be evaluated against clinical expectations and compared against clinical trials data. The goal is to ensure that the device continues to meet its intended clinical purpose and safety requirements. The EU AI Act requires that AI systems undergo continuous monitoring, especially those classified as high-risk or generative AI systems.

Vigilance and Incident Reporting

Vigilance involves the ongoing identification, reporting, and evaluation of any incidents or adverse events related to the device. This includes clinical incidents, software failures, or any other event that could affect patient safety or device performance. The MHRA and EU regulations require manufacturers to have a formal vigilance system that allows for prompt reporting of such events. The system must be capable of identifying, documenting, and escalating incidents to the relevant authorities.

Incident reporting must be done in a timely manner. For example, if a clinical team identifies that an AI-based clinical decision support tool provided incorrect recommendations, this must be reported through the established clinical incident reporting system. The incident must then be reviewed by the clinical and technical teams to determine whether it was due to software error, data misalignment, or other factors. The manufacturer must then decide whether to issue a safety notice, perform a software update, or take other corrective actions. The EU AI Act introduces new obligations for reporting incidents involving high-risk AI systems, including transparency requirements that apply from 2 August 2026.

• Incidents must be reviewed and documented within 30 days of discovery
• Any clinical or safety concerns must be escalated to the clinical safety officer
• Reports must be submitted to the relevant regulatory authority within 15 days of clinical evaluation

Compliance and Record Keeping

Effective compliance with post-market surveillance, vigilance, and incident reporting requires strong record-keeping practices. All data must be stored securely and be accessible for audit or inspection purposes. The data must be reviewed by qualified personnel, including clinical experts, software engineers, and regulatory affairs specialists. The clinical evaluation report must be updated regularly to reflect any new data or clinical findings. The clinical safety officer must ensure that clinical data is reviewed against clinical requirements and that any identified risks are properly managed.

ISO/IEC 42001:2023 provides guidance on implementing an AI management system that includes these surveillance and reporting processes. The standard requires that manufacturers have defined roles and responsibilities for clinical surveillance, clinical evaluation, and incident reporting. The clinical safety officer must have access to clinical data, clinical evaluation reports, and clinical incident data to make informed decisions. The clinical evaluation must be reviewed at least annually or whenever clinical data or clinical use changes significantly. The clinical evaluation must also be reviewed in response to clinical incidents or clinical feedback.

For AI-based medical devices, clinical data must include clinical outcomes, clinical validation data, clinical effectiveness data, and clinical safety data. 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