Key article takeaways
RUCA matters: Rural-Urban Commuting Area (RUCA) categories bring a more precise view to geographic classifications, clarifying how healthcare is being accessed in different communities.
MarketScan’s Medicaid database: Utilizing the MarketScan Multi-State Medicaid Database can help evaluate health equity and how social determinants of health (SDoH) impacts health outcomes prevalent among Medicaid populations.
Stronger Medicaid insights: Pairing MarketScan’s Medicaid claims data with RUCA-based geographic categories can create a more complete and context rich view of the healthcare landscape.
Understanding the needs of Medicaid populations requires far more nuance than broad geographic labels like “urban” or “rural” can provide. Communities differ widely in their access to services, commuting patterns, and local infrastructure. That’s why we’ve introduced Rural–Urban Commuting Area (RUCA) categories into the MarketScan Multi-State Medicaid Database—bringing a more precise, data-driven lens to geographic classification. By applying standardized RUCA groupings—metropolitan, micropolitan, small town, and rural—you now gain a clearer and more actionable understanding of where Medicaid members live and how their communities shape their healthcare experiences driven lens to geographic classification.
RUCA categories go beyond simple population counts. They capture the ways people move between their homes and key economic centers, offering a more complete view of how “connected” a location truly is. When these categories are layered onto MarketScan’s rich Medicaid claims data, you get an enhanced ability to understand how community type influences access to care, utilization patterns, and health outcomes across diverse populations.
These classification groups allow analysts, researchers, and policymakers to identify meaningful differences in the needs and behaviors of distinct population segments—without the complexity of managing granular code-level geography. For organizations aiming to tailor interventions, refine resource allocation, or understand local market dynamics, RUCA-based context adds clarity that traditional county level labels often miss in assessing geography.
With RUCA-enhanced data, you can:
Identify meaningful differences among metropolitan, micropolitan, small town, and rural populations seeking behavior
RUCA categories surface population nuances that standard geographic classifications can obscure. For example, two counties considered “rural” may actually have very different commuting patterns and access levels—distinctions that become clear with RUCA. This helps organizations achieve a more accurate understanding of local health needs, particularly in areas where transportation networks and community layout significantly influence care seeking behavior.
Explore how access and utilization vary across geography
By tying member behavior to RUCA categories, you can investigate how factors like distance to providers, availability of public transportation, or the presence of regional medical hubs shape utilization. RUCA adds depth to your analyses by capturing the role of commuting flows and urban connectivity—elements that often explain why service use differs even among populations with similar demographic profiles.
Strengthen network design, and policy planning—especially in states where geographic diversity contributes to cost variability and access challenges across regions
RUCA categories align with frameworks used by federal health agencies, enabling you to build analyses that reflect recognized standards. This helps support more accurate rate setting, network design, and policy planning—especially in states where geographic diversity contributes to cost variability and access challenges across regions.
Support equity focused initiatives
Geography plays a significant role in health equity. RUCA groupings highlight where geographic barriers such as travel distance, limited provider availability, or infrastructure gaps may hinder access to essential care. This creates opportunities to identify service deserts, monitor disparities in preventive and specialty care, and develop targeted interventions to improve outcomes for underserved groups.
Benchmark MarketScan data against broader Medicaid populations
Standardized RUCA categories allow you to compare MarketScan Multi-State Medicaid data to national Medicaid landscapes or specific state programs with similar geographic distributions. This creates a reliable foundation for external benchmarking and helps ensure that geographic composition is accounted for in comparative analyses.
By pairing MarketScan’s comprehensive Medicaid claims data with RUCA-based geographic categories, you gain a more complete and context rich view of the healthcare landscape. These insights help illuminate where populations face barriers, how utilization differs across community types, and where strategic investment can make the greatest impact. The result is stronger analytics, more informed decision-making, and clearer direction for planning the initiatives ahead.
Connect with our team today to learn more about MarketScan’s Medicaid claims data.