Identifying and Benchmarking the Number of Medicaid Beneficiaries with Comprehensive Benefits in 2017 (Brief)
T-MSIS Analytic Files Data Quality Brief #4062
- This brief describes the most reliable method for identifying Medicaid beneficiaries with comprehensive benefits in the 2016 T-MSIS Analytic File and benchmarks the number of Medicaid beneficiaries with comprehensive benefits against an external source of data—the Eligibility and Enrollment Performance Indicator (PI) data.
- The most reliable method for identifying Medicaid beneficiaries with comprehensive benefits in the 2017 annual Demographic and Eligibility T-MSIS Analytic File is to use the CHIP code (or the eligibility group code if the CHIP code is missing) to identify Title XIX Medicaid beneficiaries and then to further subset the population by using the restricted benefits codes that indicate eligibility for comprehensive benefits.
- In 21 states, the T-MSIS Analytic File-based counts generated with this method were within 5 percent of the counts based on PI data. In 9 states, the T-MSIS Analytic File-based counts were within 5 to 10 percent of the PI counts.
- In 9 states, the T-MSIS Analytic File-based enrollment counts differed from the benchmark by 10 to 20 percent. In 8 states, the T-MSIS Analytic File-based enrollment counts differed from the benchmark by more than 20 percent. Among these 8 states, Colorado, North Dakota, Rhode Island, and Wisconsin each had a difference of more than 50 percent between their T-MSIS Analytic File-based and PI counts, and we considered their data to be unusable for identifying beneficiaries in Medicaid with the method used in this brief.
- T-MSIS Analytic File users are encouraged to use the eligibility group code only when the CHIP code is missing, as the CHIP code appears to be more reliable than the eligibility group code for distinguishing between Medicaid and CHIP enrollment.