Seeing Rural Communities Clearly — Why Benchmarks Matter in Public Health Data
By Annie Elliott, Senior Data Analyst at Metopio, and Heather Blonsky, Vice President of Data at Metopio
Rethinking How We Measure Rural Health
Rural America tells a story that’s often lost in the averages. It accounts for nearly 80% of the land area in the United States but less than 20% of the population. When public health and hospital teams benchmark outcomes, they often rely on national or state averages that don’t reflect what life looks like in a small town or agricultural county.
That’s why Metopio developed U.S. rural benchmarks, a set of fair, comparable measures that allow health leaders to see performance in context and allows for more accurate interpretation of what “good” or “bad” looks like when serving rural communities.
In this post, we’ll share insights from a recent conversation with Annie Elliott, Senior Data Analyst, and Heather Blonsky, Vice President of Data.
Small Populations, Large Land Areas
Heather Blonsky explains that the mismatch between land and people is part of the issue:
“Rural areas make up a huge share of the country’s geography — something like 75 to 80 percent of the land — but represent a very small slice of the population. That means the data we use to describe them can look drastically different than what we see in urban areas.”
A rural community in southern Illinois will look nothing like one in Montana or on a Native American reservation. Geography, infrastructure, and access create their own local realities. Recognizing those differences is key to designing health interventions that fit.
Averages Can Be Misleading
If you looked at cancer mortality in Coles County, Illinois and compared it to the U.S. or Illinois averages, you might think, ‘We’re doing horribly.’ But when you compare Coles County to other rural counties like itself, you might find it’s actually performing a little better.
This shift in perspective changes the narrative from accepting failure to understanding context. It also helps local leaders defend their progress and prioritize resources realistically.
Access and Distance: The Hidden Drivers of Outcomes
Benchmarks also shed light on why outcomes differ. In rural areas, patients often have to travel long distances for specialty care, or don’t have access at all.
“Illinois, for example, averages about 116 specialists per 100,000 residents,” says Blonsky. “But in the Illinois rural benchmark, it’s closer to 27 per 100,000 — that’s a huge difference in people’s daily experience of care.”
Those numbers translate to real barriers: delayed screenings, skipped visits, and higher rates of avoidable hospitalizations. Contextualizing data this way helps hospitals and local health departments identify where access gaps are structural, not behavioral.
Variation Within the “Rural” Label
Even within rural areas, there’s no one-size-fits-all picture.
““Every map of rural America looks different depending on what you’re measuring. The rural South doesn’t look like the Northeast, and both differ from the Plains or reservation communities. Our data lets you zoom into those distinctions while still seeing the shared challenges.” ”
For analysts and planners, this means being able to compare fairly within peer groups while acknowledging nuance across geographies.
Defining “Rural” the Right Way
Many people assume that “rural” is synonymous with worse outcomes — but that’s not always the case. “When we looked at HIV incidence, rural areas were generally doing much better than both their own counties and the national average,” Elliott explains. “We don’t want to paint rural areas as struggling, they also show incredible strengths, like community resilience and strong social ties.”
Understanding where rural communities excel is as important as identifying where they lag. It shapes targeted interventions and helps avoid deficit-based narratives.
In the same way, not all “rural” definitions are created equal. Metopio aligns with the Health Resources and Services Administration (HRSA) classification because it’s built for healthcare access and resource allocation.
““The HRSA definition is specifically designed for healthcare. Other agencies, like the Census Bureau or the Office of Management and Budget, define rural differently. We chose HRSA’s model because it maps more directly to the questions our users ask about health access.” ”
This decision ensures consistency and relevance for public health and hospital users, especially when combining Metopio data with their own local datasets.
What This Means for Decision-Makers
Rural benchmarks help translate data into real-world strategy. Instead of comparing small counties to broad state averages — or worse, to national numbers dominated by urban data — leaders can now understand how their communities truly measure up.
For local health departments: this helps identify which metrics are genuinely concerning versus which simply reflect rural realities.
For hospitals: it offers a fairer peer comparison when tracking progress or reporting Community Health Assessment findings.
Most importantly, rural benchmarks make the invisible visible, giving rural communities the context they deserve and policymakers the evidence they need to act with confidence.
Rural benchmarks aren’t just numbers — they’re a correction to how we’ve misunderstood rural America for decades! They make data fairer, comparisons clearer, and stories more accurate.
““It’s about giving people a realistic picture,” Blonsky says. “Data isn’t just a scorecard, it’s how communities understand themselves.” ”