How collaboration builds value in medical device human factors research

March 16, 2023

Developing safe devices that work is the baseline for effective medtech design. FDA regulations help bring consistency to that process. But even guided by robust regulation, safety and functionality are only as effective as the likelihood that patients will adhere to a prescribed therapy.

What’s more: the value of medical devices – like insulin pumps and epinephrine auto-injectors – is driven by how, where, and when people use them.

Human factors research helps development teams proactively identify and design products for the intended uses by the intended users in the intended environments. And while there are differing approaches to addressing human factors, not all are created equal.

Some human factors research teams limit themselves with a top-down, one-size-fits-all approach to research that assumes knowledge without verifying how it applies to real world experiences.

But other researchers – we’d say the right researchers – collaborate with manufacturers to focus on designing medical devices that address, rather than exacerbate, the pain points that can drive down adherence and lead to adverse medical events.

In this post, we’ll dive into how and why collaboration is the best approach for human factors research teams with a focus on designing valuable products.


We help manufacturers design medical devices for real users in the real world

The benefits of user-centered design aren’t always represented in the vacuum of a lab. And delivering a useful product isn’t simply a matter of meeting regulatory standards, no matter how comprehensively they’re outlined.

Rather, valuable design depends on the human factors that drive adoption for real world use.

The efficacy of epinephrine auto-injectors, for example, depends on the successful administration of the medicine within a specific time frame before the onset of anaphylaxis.

External factors like a patient’s stress levels, age, or physical preparedness can impact how and when a patient uses a medical device like an epinephrine auto-injector. A five-year-old shouldn’t be relied on to self-administer medication, for example.

In the controlled environment of a lab, one or more of these factors might be overlooked if the fidelity of the simulated use environment and use scenarios are not paid sufficient attention. During a real-world medical emergency, someone in the midst of a severe allergic reaction might be unable to self-inject the medication they need to save their life:

  • If they’re too stressed, they may not be able to find their epinephrine.
  • If they’re in shock, they may be physically unable to self-administer their epinephrine.
  • If they are too young or physically unable to self-administer epinephrine in any case, they may be at the mercy of a caregiver’s – or bystander’s – preparedness.

These constraints, along with many others, represent the real-world human factors that we must examine to design the best possible medical devices. Good research depends on uncovering what’s unknown, and collaboration helps us recognize our blind spots.

Next, let’s look at how the conversations we have with medical device manufacturers help develop products that offer real-world value.


Effective research depends on conversations

Effective research depends on learning the constraints that govern how a product can be produced. And, once known, production constraints must be balanced with the realities of how a product will be used.

When researching the development of medical devices, we gather this information via two types of conversations:

  • Conversations with medical device manufacturers.
  • Conversations with end users (say, patients and physicians).

Another way to think of it: when we talk to manufacturers, we strive to understand the constraints within which the design team must operate so that any proposed solutions are feasible – not just theoretical improvements. And when we talk to users and hear their stories, we can identify pain points in order to deliver the products that help address them, within those previously identified constraints.

So how might this look in the real world? Say a medical device manufacturer is redesigning the packaging and labeling for their epinephrine auto-injector. Our conversation with them might lead us to research a design that prioritizes…

  1. their branding, while
  2. remaining easily distinguishable from other similar products on the market, because
  3. patients may need both products – but using one (like an insulin smart pen) when meaning to use the other (like an epinephrine auto-injector) can be life-threatening.

In this example, to address the manufacturer’s initial concerns, we might consider how to make the packaging easily distinguishable without departing from the manufacturer’s branding colors. But as we touched on above, we must also consider various situations that impact the product’s use.

The manufacturer’s branding requirements, for example, might direct that all packaging be blue. So distinguishing one product from another might depend on researching the shades of blue that both meet the branding expectations and can be distinguished from other products in packages of different shades.

However, epinephrine auto-injectors are commonly removed from secondary packaging and carried (e.g.) in a pocket or a purse. So in this use scenario, manufacturers need to consider users’ ability to distinguish between and use the device without the benefit of that secondary packaging. This has implications for both the visual appearance of the device, as well as the content of on-device labeling.


Research isn’t a one-size-fits-all activity

Our human factors teams recognize the research process isn’t a one-size-fits-all activity. The business objectives of one one manufacturer rarely map directly to those of the next. And the research needs of any one project change over the course of that project’s development. So right-sizing research throughout each project’s trajectory is paramount.

At the beginning of our research process – say, when we’re determining the right questions to ask – our approaches are fluid. This helps us maintain a lightweight, iterative perspective on our preliminary research. And it allows our teams to move rapidly, responding to what we learn so we can push forward and continue learning in the context of each stage of development.

Of course, as we gather and process more user data, our objectives shift as our perspective becomes more refined. So we focus less on generating the right questions. And we likewise move on from sampling a broad array of user groups to help us answer those questions.

But regardless of the phase of development, allowing adequate time for the corresponding scope of the research during each phase is critical. When teams take a top-down approach to research – dictating, for example, that each stage of the process take some arbitrary amount of time – it can produce suboptimal results.

Bold Insight’s collaborative approach begins with a conversation between partners. Some of the first questions we ask manufacturers focus on their timeline and scope. Then, we continue that conversation throughout the research and design process. And together, we ensure we’re working on the right timeline from stage to stage and project to project.


Collaboration Builds Trust

Every product development team is burdened by constraints. But by approaching research and design as a process deepend by conversations, human factors research teams can convert the process of overcoming constraints into trust.

In a world where not every solution designers want is possible, that’s key. The more we’re viewed as trusted partners who listen and collaborate with the medical device manufacturers we partner with, the better we’re able to deliver the best possible course forward for each project or product we work on.

Interested in hearing more about Bold Insight’s collaborative approach to human factors research? Reach out to us here to start a conversation.