AI-Assisted Triage: Accelerating Post-Market Surveillance While Eliminating Reporting Blind Spots

By Binitkumar M. Vaghani

Complaint volumes have outgrown manual triage, and medical device companies are turning to AI to keep up. The speed gains are real, but used carelessly the same tools can bury a reportable event at the bottom of a queue while the MDR clock runs. This piece maps where AI genuinely helps in post-market surveillance, where human judgment has to stay, and what validation, monitoring, and audit trails a defensible program needs. It is grounded in the current regulatory frame, including the QMSR and FDA’s new inspection program (CP 7382.850) that took effect February 2, 2026, 21 CFR Part 803 reporting timelines, and ISO 13485 software validation expectations. It includes a practical table drawing the line between tasks that are safe to automate and decisions that must stay human-owned. The intended audience is quality, regulatory, and post-market surveillance professionals in the medical device industry.

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Balancing Cyber Risk
Balancing Cyber Risk

What 524B and QMSR Change About Medical Device Risk

By Kaleb Averell

What 524B and QMSR actually require, in plain terms, including the post-market obligation that does not end at clearance? How both map to four kinds of exposure: cybersecurity, product liability, recall, and management liability. Where device makers are commonly unprepared against the new baseline, including the gap between cyber risk and product liability for software and devices.

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post market surveillance
post market surveillance

Why Organizations Miss Emerging Product Risk: Understanding the engineering mechanisms that remain hidden long before complaint trends become visible

By Aalap Patel, MS, CQE, CSSBB

Emerging medical-device risks are often missed because early warning signs are fragmented across complaints, manufacturing, suppliers, returned products, clinical observations, and other data sources; not immediately as statistically significant trends. An engineering-centered, cross-functional approach connecting these weak signals to underlying mechanisms sooner, can improve designs, verification, manufacturing controls, and risk management before isolated issues become widespread quality problems.

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AI in the EHR
AI in the EHR

Applying Agentic AI to Healthcare Delivery: The Key to True Transformation

By Jaimon Jose

MTI Viewpoints Insights shared by industry relative to healthcare and the advancement of medical technology. Jaimon Jose, senior director of engineering and compliance at CharmHealth, is a software architect and technical leader with more than 18 years of product development experience in the areas of identity and security technologies, distributed systems, cloud security, and data…

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