Moments a Laboratory Can Never Show
Why Understanding User Errors in Medical Devices (Not Just Detecting Them) is Critical
A patient trying to set up a new infusion pump skipped a critical dose-setting step because the interface was complex and confusing. This small, seemingly harmless “click” error became the first link in a chain that could lead to very serious health consequences. This was not just a user error; it was a sign of a much deeper problem in our device development processes: a blind, purely technical approach that ignores human factors.
The real issue is not treating these errors as mere “data,” but understanding the human story behind them.
This article aims to move you away from a cold, mechanical view of user errors and toward empathy, story-based thinking, and deeper understanding. In doing so, we will explore four core strategies that can transform your processes.
Strategy 1: Warm Up Cold Procedures with Stories
The human brain remembers stories, not lists. Technical information does not stay in memory unless it is placed within a narrative. Procedures tell us what to do; stories help us feel why it matters. That is why we will use the infusion pump case introduced at the beginning as a narrative backbone throughout this article. This story makes complex procedures, risk analyses, and post-market activities tangible in real life. Most importantly, it reminds us that behind every technical process, there is always a human being.
Strategy 2: Ask “So What Does This Mean?” at Every Step
Listing technical errors is easy. But unless you connect them to their real-world impact, they remain nothing more than statistics. The question “So what does this mean?” helps us build a bridge between technical data and human consequences.
For example, imagine the following item in an EpiPen checklist:
“User does not hold the device against the thigh long enough or removes it too early.”
This is a technical and emotionless statement. Now let us ask the key question: So what does this mean?
It means the life-saving adrenaline may not be fully injected. In an anaphylactic shock situation, this can be fatal. With a single question, a simple checklist item becomes a matter of life and death.
Strategy 3: Reframe Your Processes Around the Human Story
Real transformation begins when these strategies are not treated as add-ons, but as lenses through which we rethink our processes. Let us now revisit the classic error-detection framework through this lens.
3.1 Preparation: From Task Analysis to Blind Spot Analysis
Every usability test starts with task analysis and risk assessment. We try to predict which steps users must take and where they might make mistakes. Returning to the infusion pump example, the clarity of the dose-setting screen may have been overlooked in this analysis. The case clearly shows how critical that blind spot was.
3.2 Video Analysis: From “What Happened” to “Why It Happened”
Video recordings are extremely valuable for capturing subtle details, such as hand movements. Their real power, however, lies in helping us understand not just what the user did, but why. Maybe the screen design was unclear. Maybe an audio alert caused confusion. Or maybe the patient was under extreme stress. Video does not just show the error—it tells the story behind it.
3.3 Clinical Studies: Reality Beyond the Laboratory
No matter how detailed laboratory tests are, they cannot fully capture the complexity of real life. Clinical studies do. A small mistake made by a tired patient at midnight can invalidate a treatment worth millions. That is why real-world data must go beyond the laboratory environment.
3.4 Post-Market Surveillance: From Regulatory Duty to Brand Protection
Monitoring user errors after a device is placed on the market is not just a regulatory requirement; it is one of the strongest ways to protect your brand. In our infusion pump case, field feedback showed that this error occurred repeatedly. Thanks to this insight, a critical software update was implemented, preventing similar errors. This was not only about regulatory compliance—it was also about protecting reputation.
Strategy 4: Move from Monologue to Dialogue
A philosophy only has value when it turns into action. Do not leave this as a mental exercise. In your next project meeting, add this agenda item:
“What was the most surprising error in the last test, and which blind spot did it reveal?”
Conclusion: Has the Next Revolution Begun?
The strategies shared in this article are not isolated steps. They are interconnected pillars of a new approach:
- Adding a story backbone turns data into insight.
- Asking “So what does this mean?” turns insight into urgency.
- Reframing processes around human stories turns urgency into action.
- Starting dialogue turns action into a continuous learning cycle.
So what is the next step?
Can we predict user errors before they happen by integrating generative AI into design processes?
Will this be the next major revolution in the industry?
Or is it still just science fiction?
The discussion has only just begun.
