Medicaid insures approximately one out of four rural Americans, but we have limited visibility into rural-urban differences in Medicaid utilization. Medicaid participants represent an important subpopulation of rural America, given that Medicaid includes low-income populations, children, and pregnant people, the latter two of are rarely included in Medicare data, which is more commonly used for policy analysis.

This research had two purposes. First: To assess the quality of Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files in conducting analysis of rural-urban differences in utilization among Medicaid eligible. Medicaid programs are run by individual states, and although T-MSIS is designed to standardize the data across multiple systems, the data files are relatively new and unexplored by researchers. For example, a key variable for rural-urban analyses is BENE_ZIP_CD – the beneficiary residence ZIP code – as it identifies who is rural and who is urban. To the extent this variable might be of lower quality (e.g., unstable, inaccurate, or only contain three-digit ZIP codes in some states, for example), the ability to do rural-urban analyses could be considerably hampered. Likewise, it may be important to analyze utilization stratified by eligibility categories (e.g., the limited postpartum eligibility for those enrolled through the Medicaid for Pregnant Women category) and any threats to the quality of the variables that would limit the utility of analyses. Finally, race variables in administrative data are often of questionable quality; a better understanding of the accuracy in these data will be useful in assessing future work in equity using Medicaid data.

The second aim was designed to be an initial step into rural-urban Medicaid analyses to examine key utilization metrics for rural-urban differences in utilization among Medicaid beneficiaries. For this aim, researchers analyzed common metrics for utilization, including access, cost, and quality, among Medicaid eligibles and assessed whether there are rural-urban differences. These analyses helped address key unanswered questions facing rural population including:

• How do costs for Medicaid eligibles vary by rurality?
• Do pregnant Medicaid eligibles have different experiences by their degree of rurality?
• Do rural children insured by Medicaid receive well-child visits as often as urban children?
• How does the race of the eligible intersect with rurality to affect patterns of care?

Answers to questions like these helped inform federal policy, regulations, and programs and empowered state and local communities to tailor their approaches to the key differences affecting them.

Publications

• Rural-Urban Medicaid and CHIP Enrollee Comparisons Using the 2019 T-MSIS Analytic File
  Policy Brief
  North Carolina Rural Health Research and Policy Analysis Center
  Date: 12/2024
  In 2019, nearly 25 percent of rural residents under age 65 had Medicaid or CHIP health insurance coverage. Researchers used data from the 2019 T-MSIS Analytic Files to compare urban and rural residents enrolled in either fee for-service or managed care Medicaid. This brief provides descriptive data on enrollment and demographics.
• Utilization of Inpatient and Emergency Services by Rural and Urban Medicaid Enrollees
  Policy Brief
  North Carolina Rural Health Research and Policy Analysis Center
  Date: 12/2024
  In 2019, nearly 25 percent of rural residents under age 65 had Medicaid or CHIP health insurance coverage. Researchers used data from the 2019 T-MSIS Analytic Files to describe health care utilization among rural Medicaid beneficiaries at the national level and to compare these results to utilization among urban Medicaid beneficiaries.