Leveraging Usability Engineering Data in Product Development

Practicing human-centered design in medical device development ensures user concerns are resolved in the final product.

October 20, 2016

3 Min Read
Leveraging Usability Engineering Data in Product Development

Practicing human-centered design in medical device development ensures user concerns are resolved in the final product.

Carol Stillman

For those of us living on the technical side of product development, data has always played a significant role in assessing development. Specs, test results, and statistical assessments help us understand where there are gaps and what is needed to get to where we need to be.

Usability, meanwhile, seems more abstract and more intuitive. It should be easy enough to develop a product with the user in mind, yet we can sometimes forget that parallels exist for harnessing data to meet usability needs and that there is much to be gained by taking advantage of those opportunities.

In recent years increased focus on usability has been driven by market demands and regulatory requirements. This, in turn, has led to the implementation of more human-centered design (HCD) methodologies that allow us to optimize products around what the users can do, what they need, and how they want to perform a task, versus forcing them to adapt to whatever we might come up with without their input.

In order to do this well, we need data. Gathering the right data--reflected by a real situation with cognitive, social, emotional, and physical elements layered upon each other--often requires true ethnographic research. Through this process, we are able to identify new and unmet needs while also making ourselves aware of subconscious expectations shared by users in the scenarios we are evaluating. As we refine the data, we're looking for the bridges between the patient and the device.

Since much of what is observed can't immediately translate into a hard requirement, many are established as trade-off criteria. These are aspects that guide us to optimize a device but they must be balanced with other attributes and are useful, but not critical, to device viability. Throughout this process, we outline the corresponding assumptions and document the rationale for decisions. As we gain additional data through future studies, we can better understand how our goals for the device should evolve.

With the requirements and criteria in mind, we continue down the path of concept development. As soon as we begin developing device concepts, we want to go back in to the field to get feedback to guide design refinement. As we iterate, we continue to integrate data analysis into the design and development process to gauge our progress and improve our data set.

For each subsequent study, we want to build on the last, using the right data to guide us as we prototype, test, iterate, and repeat. In addition to helping form these initial device concepts, the data from our contextual research is allowing us to define realistic scenarios and identify appropriate user groups and stratifications.

One of the key attributes of this process is the feedback loop. Concept refinements, test data, improved design criteria, and information related to unanswered questions circulate as design iteration continues. The process continues until data confirms the gaps have been closed and we've arrived at the right final design.

When development is guided by data that is acquired purposefully, used carefully, and continually updated and refined, attributes of our validated design can be mapped back to the user needs identified in contextual and ethnographic research. Ideally, at the end of the process, we can look back at the things our users were worried about and trace these to solutions reflected in the final design.

Carol Stillman is a project manager in medical devices at Battelle.


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