Identifying Rural Health Clinics Within the Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files

Authors

Katherine Ahrens MPH, PhD, University of Southern Maine, Muskie School, Maine Rural Health Research CenterFollow
Zachariah Croll, University of Southern Maine, Muskie School, Maine Rural Health Research CenterFollow
Yvonne Jonk PhD, University of Southern Maine, Muskie School of Public Service, Maine Rural Health Research CenterFollow
John Gale MS, University of Southern Maine, Muskie School, Maine Rural Health Research CenterFollow
Heidi O'Connor MS, University of Southern Maine, Muskie School of Public Service, Maine Rural Health Research Center;Follow

Document Type

Policy Brief

Publication Date

3-2024

Keywords

MRHRC, Rural Health Clinics, data, Medicaid, statistics, health policy

Abstract

Researchers at the Maine Rural Health Research Center describe a methodology for identifying Rural Health Clinic encounters within the Medicaid claims data using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files.

Background: There is limited information on the extent to which Rural Health Clinics (RHC) provide pediatric and pregnancy-related services to individuals enrolled in state Medicaid/CHIP programs. In part this is because methods to identify RHC encounters within Medicaid claims data are outdated.

Methods: We used a 100% sample of the 2018 Medicaid Demographic and Eligibility and Other Services Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files for 20 states to estimate pediatric and pregnancy-related services to patients enrolled in state Medicaid/CHIP programs. We scanned fee-for-service and Medicaid encounter claims (and claim lines, representing unique procedures provided at each visit), looking for eight possible indicators of an RHC encounter, listed in Table 1. We considered an encounter to be an RHC encounter if any of the claim lines contained at least one of the eight indicators. We categorized the percentage of RHC encounters captured by each of the eight indicators listed for one of our populations of interest: the pediatric population.

Results: We found substantial variation in how RHC encounters were identified across states. For example, type of bill (provided on facility claims) code '071' identified the majority of RHC encounters in Maine, Montana, Nebraska, New Mexico, Oklahoma, and Wyoming, whereas place of service (provided on professional claims) code '72' identified the majority of RHC encounters in Iowa, Kansas, Kentucky, Mississippi, North Carolina, South Carolina, South Dakota, and Tennessee.

Conclusion: Our strategy to identify RHC encounters could be used by T-MSIS data users to identify RHC encounters. However, our methodology for identifying RHC encounters could have led to misclassification of RHC encounters (undercounting or overcounting encounters) and needs further validation.

For more information on this study, please contact Kate Ahrens, katherine.ahrens@maine.edu

Funding Organization

HRSA-Federal Office of Rural Health Policy

Grant Number

Grant #CAU1CRH03716

Recommended Citation

Ahrens, K., Croll, Z., Jonk, Y., Gale, J., & O'Connor, H. (2024). Identifying Rural Health Clinics within the Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (PB-83). University of Southern Maine, Muskie School, Maine Rural Health Research Center.