Improving Healthcare Access with Data Storytelling: Why Context…

When I first started working on healthcare research, I had no idea just how much context would shape the insights uncovered. A research team had spent countless hours debating how to construct the perfect survey to capture health-seeking behaviors in rural Uganda. They wanted to know where people sought medical care and why, but we quickly realized that even basic questions like “How far did you travel to get care?” didn’t have simple answers.

Some respondents gave the distance in miles, some in kilometers, and others simply said, “About two hours.” Sounds simple enough, right? Well, that “two-hour” estimate could mean anything from a brisk walk across a dusty path to a motorbike ride over a washed-out road, all depending on what they were dealing with that day — and maybe even if they had a chicken to carry with them, or family members to see along the way.

But the real complexity came from understanding how context — the unquantifiable elements of people’s lives — was essential to interpreting the data. One person’s “two-hour” journey might not be equivalent to another’s, depending on how much of the trip was spent socializing with neighbors, or navigating a treacherous road. In rural Uganda, stopping to chat isn’t just about passing time — it’s part of the fabric of everyday life.

Now, imagine if we had taken the easy route: standardizing the distances, throwing out the inconsistencies, and reducing all those subjective answers into a neat, numerical dataset. We would’ve lost the most important insights: the human side of the data.

Here’s where the power of data storytelling comes in. By contextualizing the numbers, we gained a much deeper understanding of the barriers to healthcare — it wasn’t just about how far someone traveled, it was about the physical, social, and even cultural factors that impacted their journey.

Fast forward a few years, and I found myself applying these same lessons to a new project back home in underserved rural communities across the U.S. The situation was similar — rural hospitals were closing, providers were scarce, and patients had to travel for hours (sometimes days) to access specialized care.

In both cases, we were looking at how far people had to travel for medical care — but this time, I knew better than to just rely on the raw numbers. I knew we had to go beyond the data. We needed to understand why people chose a particular healthcare option, and what obstacles they faced in seeking that care.

One of the most interesting projects I worked on explored the factors that drove people to choose one of three types of treatment for reproductive healthcare: completely in-clinic care, completely at-home care, or a mix of both. It wasn’t just about accessibility — it was about preferences, social norms, and trust in healthcare providers.

Just like in Uganda, we had to consider things like cultural context, education levels, and socioeconomic status to really understand what was going on. Without this deeper dive into the context, we’d have missed the bigger picture. The numbers alone didn’t tell the story of why people chose one path over the other.

These experiences reinforced something I’d learned early on: Data, on its own, is just noise. It’s only when you weave it into a narrative that the story begins to take shape. You can have all the clean, polished numbers you want — but without qualitative insights, you miss the essence of what those numbers are telling you about people’s real-world experiences.

So why does this matter? In healthcare, especially when it comes to public health, patient care, and digital security, the stakes are high. If we make decisions based solely on raw data, we might make mistakes — mistakes that could impact people’s lives. The human story behind the data is what drives meaningful change. We need to use data not just to measure outcomes, but to understand the people behind those numbers, to shape strategies that truly meet their needs.

Now, I take that experience with me whenever I work on new projects — whether it’s improving digital privacy literacy in healthcare or researching global health disparities. I don’t just focus on the data; I focus on the stories within it. The messy, multilingual, and multi-layered datasets might look chaotic at first, but they often hold the insights that can spark real change.

If you’re working on a project where data meets human impact, let’s connect. Whether it’s turning complicated research into clear, compelling content or finding the deeper insights buried in your data, I’m here to help.

And hey — if you have your own data storytelling experience, drop it below! Let’s keep this conversation going and share what we’ve learned.