ArticleHealth services research2025
Benchmarking the Transformed Medicaid Statistical Information System Analytic Files for analysis of opioid use disorder treatment.
Article in Health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Geographic Availability and Use of Medications for Opioid Use Disorder Among Medicaid Enrollees.JAMA health forum · 2026Article
- Dental Surgeries in Hospitals and Surgery Centers for Children With Developmental Disabilities.Hospital pediatrics · 2026Article
- Pediatric dental surgeries in children with intellectual disabilities and autism paid by means of Medicaid.Journal of the American Dental Association (1939) · 2026Article
- Cascade of Care for Opioid Use Disorder Among Medicaid Beneficiaries.JAMA network open · 2026Article
- Completeness and Quality of Data for Children in Medicaid Comprehensive Managed Care Compared to Fee-for-Service, 2001-2019.Health services research · 2025Observational
- Medicaid Payments and Outcomes for Pediatric Dental Surgical Procedures by Site of Care.JAMA network open · 2025Article
- Benchmarking the Transformed Medicaid Statistical Information System Analytic Files for analysis of opioid use disorder treatment.Health services research · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
objectiveTo evaluate the data consistency and quality of Medicaid claims data on opioid use disorder (OUD) treatment, benchmarking the Transformed Medicaid Statistical Information System Analytic Files (TAF) against metrics reported by the Medicaid Outcomes Distributed Research Network (MODRN), which analyzed data obtained directly from 11 state Medicaid agencies. DATA SOURCES AND STUDY
settingThe primary data source was TAF claims for the years 2017 and 2018, limited to non-dual, full-benefit Medicaid beneficiaries aged 12-64 in one of the 11 states in our study sample. STUDY
designUsing TAF data, we replicated performance on the following five OUD quality metrics reported by MODRN: number of enrollees receiving any OUD medication, receipt of behavioral health counseling, completion of urine drug screens, receipt of any opioid analgesic fill, and receipt of any benzodiazepine fill. DATA COLLECTION/EXTRACTION
methodsAccess to TAF data was facilitated through the Chronic Conditions Warehouse. PRINCIPAL
findingsThere were 11% fewer Medicaid enrollees with OUD in TAF compared to MODRN (912,478 vs. 1,034,412). Patient characteristics were largely similar across the two datasets, with the exception of more missing race information in TAF (20.9% vs. 7.1%). Across the 11 states, performance on the six quality measures was similar. For example, the rate of use of any OUD medication in 2018 was 57.1% in MODRN and 58.6% in TAF. However, there were important discrepancies in the TAF data in individual states for single years.
conclusionsTAF data may undercount patients with OUD, but otherwise exhibited consistency with MODRN benchmarks, suggesting suitability of TAF for research on OUD treatment. Our results highlight several data quality issues with TAF that researchers who use these data should be aware of, including reporting of race and ethnicity.
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