Mountain Climbing and Mapmaking: Insights From Our Design Research Process

This week, we wanted to share three principles that’ve helped our team lean into the messy, complicated world of healthcare digitalization.

As a recap, in our last post, we shared some of our early takeaways from the research process. Our client, one of the largest vendors of electronic medical record (EMR) software in the US, challenged us to help their customers master their system.

Suffice to say, it’s a complicated space and many healthcare organizations and workers are still struggling to realize the value of having these systems.

So, how do you tackle a messy, sprawling problem like this?

I like to imagine us as mountaineers, dropped into a foreign land.

We want to climb the tallest mountain, but we don’t know where it is or what it’ll take to summit the thing.

We do know that our food and water is limited, and camping out indefinitely isn’t an option.

Pick a continent, quickly.

You can’t plan an expedition without knowing which continent you’re on.

You also can’t plan research without knowing what problem you’re trying to solve.

This invariably means making some assumptions in order to get started. It can be a treacherous balancing act. Do you take the client’s stated problem at face value? What if they have no idea what to solve? How do you make sure you’re making valid assumptions?

The truth is you can’t research everything in a given time period, so you have to make a best guess about where to start and move quickly. The important part is naming these assumptions and treating them as hypotheses to be tested through the research process. And, by discussing it as a team, all of you will be on the look-out for things that might validate or disprove them.

In our case, our client had handed us a relatively well-scoped brief with an underlying business problem that they were trying to tackle. We pointedly asked whether they were open to design opportunities outside of EMR training and, to our delight, they said yes. But, we also looked the key resource available to us — a team of client experts in education and professional services — and decided to at least start with a focus on EMR training, rather than widening our scope further.

It turned out to be a good decision, as we later learned that solving problems in this space, whatever you choose, requires going into the specifics of the healthcare organization and team alongside their clinical workflows.

Don’t lose the forest through the trees.

With any huge project, it’s easy to get lost in the details.

At some point or another, you might start confusing finishing a task with achieving a goal. That’s why we agreed on the Big Questions, making them visible and spelling them out in plain English.

For example,

What are the top five breakdowns in EMR training?

Who do they affect? Why do they happen?

How do we know?

By making them visible, we also remind ourselves to constantly revisit them, adjusting our research plan as we go. If we’re doing a bunch of stuff, but we’re not moving the needle on these questions, it’s a sign that we might’ve wandered off into the forest.

Lastly, one habit we’ve been trying to develop in our team communications is asking, “So what?” We do have more formal processes for doing this, such as affinity mapping, but we also do informal share-outs every time we meet. We don’t just restate findings, but spend time formulating and revising our hypotheses.

Find a map (or two, or three).

Sometimes, we must wander into the true unknown.

Most of the time though, we’re exploring a landscape that others have traversed before. What we need is a map to get a lay of the land.

The fastest way to do this is to borrow one from an expert. Experts often have a particular way of structuring and organizing a problem space, which can be extremely valuable to helping you orient yourself.

For example, our teammate Ishaan hustled his way into a phone interview with a very experienced health IT business leader. We’d already done a client kick-off and our hypothesis was that the greatest unmet needs were in the ambulatory space. He started the call by summarizing our findings, but before he could get to his main questions, the interviewee cut him off.

“The question you’re asking me doesn’t make any sense. Is this an outpatient radiologist? A nurse practitioner in a large public hospital? You have to get way more specific to really solve anything in this space.”

Although it threatened to blow up a chunk of our research plan, it was an invaluable insight. It helped that, by adopting a hypothesis-driven mindset, we were looking out for data which challenged our ideas. It pushed us to focus on validating whether there actually are meaningful differences in training needs across all healthcare settings. Those 60 minutes were worth many, many hours of Googling online or talking to random end-users, even though it took effort and preparation for Ishaan to land the interview.

That said, maps have their limitations. Like a real map, expert interviews and literature review can’t necessarily show which problems haven’t been discovered yet. They often can’t tell you exactly how to solve a problem, particularly when we’re talking about the contextually messy world of human problems. Lastly, they reflect the worldview of the mapmakers, so you have to watch out for their biases and unstated assumptions, too.

Lest I forget, we also interviewed current users of EMR systems. Our teammate Daphne tapped into her networks and trawled through LinkedIn to hustle up a diverse line-up of healthcare workers. This was also extremely helpful, as these individuals could speak with a level of detail and personal experience that helped us understand what experts meant by “alert fatigue” or “customized order sets.”

In other words, the trick is finding the right mix of these “top-down” (e.g. expert interviews, literature review) and “bottom-up” (e.g. users interviews, observations) approaches to mapping a problem space. Both are essential to a research process and using the right technique at the right moment in your process is both an art and science.

One thing we haven’t done so far is actually get into clinical settings to observe EMR usage and training in the field. We’re working on it, but there are special considerations for conducting contextual research in healthcare settings, such as patient privacy. As we look ahead, what’s top of mind for us is how we might engage clinicians in the most meaningful way, once we do connect.

Thanks for reading. We’ll follow up with part two next week: you’ve surveyed the terrain, but how do you actually decide which mountain to climb?

In the meantime, we’d love to hear your suggestions, feedback, and thoughts. What research principles and practices have helped you journey into the unknown?

Holler at the HIT Squad.