MedTech Intelligence

Complaint handling was designed for a world where complaints arrived slowly and looked alike. That world is gone. A single high-volume product line can generate thousands of records a month, and they arrive from everywhere: call centers, field service reports, distributor emails, hospital portals, sales reps, and social media. Some are detailed. Many are two vague lines written by someone who never saw the device fail. Every one of those records has to be assessed. Is it a complaint?

Healthcare is undergoing a fundamental shift. For decades, care has been built around episodic interactions such as a doctor’s appointment, a hospital stay or a procedure. Clinicians assess a patient, make decisions based on the information available at that moment and schedule the next point of care. As healthcare expands beyond hospitals and clinics, providers need better visibility into patient conditions, device performance and care environments.

MTI Viewpoints Insights shared by industry relative to healthcare and the advancement of medical technology.

The U.S. Food and Drug Administration today issued a discussion paper on considerations for the regulation of generative artificial intelligence (GenAI)-enabled medical devices, seeking feedback from interested parties on risk assessment, premarket evaluation, postmarket monitoring, and other topics relevant to the regulation of GenAI-enabled medical devices.

Two regulatory changes have landed close together, and together they reset what adequate protection means for a medical device company. FDA’s Section 524B cybersecurity requirements now govern how connected devices reach and stay on the market. The Quality Management System Regulation, which took effect on February 2, 2026, rewrites the quality system rules that sit underneath every device a company makes.

According to a recent survey of MedTech sales representatives, those who use Artificial Intelligence (AI) at work are three times more likely to hit quota than those who do not. Similar patterns have emerged across other sales sectors as well. Salesforce’s 2026 State of Sales report found that sales teams that use AI tools are 3.7 times more likely to meet quota than those who do not. The data makes a compelling case for AI adoption. Yet it also reveals a more complicated reality.

The notion that “everything old is new again,” is attributed to various luminaries. Regardless of who coined the phrase, it is particularly salient to the application of lean principles in medical device manufacturing today. The philosophies that underpin lean manufacturing first emerged in Japan’s automotive sector in the 1930s and evolved to become a hallmark of successful brands.

Medical device manufacturers collect vast amounts of post-market surveillance (PMS) data, yet important product risks are still frequently recognized only after complaint trends become statistically significant or corrective actions become unavoidable.1-5 The challenge is rarely a lack of information. More often, organizations fail to connect subtle observations across multiple sources of evidence before meaningful risk emerges.

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MTI Viewpoints Insights shared by industry relative to healthcare and the advancement of medical technology. Aneesh Deshpande is a Hardware Engineer at Medtronic specializing in neuromodulation and neurostimulation platforms. He focuses on integrating complex medical device systems, hardware, firmware, and telemetry to ensure safe, reliable performance.