HARNESSING THE TAF ANALYSIS REPORTING CHECKLIST TO ELEVATE TRANSPARENCY IN MEDICAID RESEARCH

The following information was released by AcademyHealth:

The T-MSIS Analytic Files (TAF) Analysis Reporting Checklist is an essential tool designed to enhance the clarity and reproducibility of research using Medicaid claims data. Developed by the Medicaid Data Learning Network (MDLN), this checklist ensures studies are both transparent and methodologically sound to safeguard the research used to inform policy.

Posted Feb 02, 2026 By Brianna Bragg

Medicaid serves as the largest source of health insurance in the United States, covering over77 million individuals. However, for decades, researchers faced significant obstacles in accessing timely, high-quality data necessary for comprehensive analysis of the programhindering the development of evidence-based Medicaid policies. The introduction of the Transformed Medicaid Statistical (T-MSIS) Analytic Files (TAF) in 2019 marked a pivotal shift, providing researchers with a rich dataset to explore the program's complexities and a detailed view of demographics, eligibility, enrollment, and service utilization.

While the TAF represent a significant improvement in quality and usability over former files, many challenges remain for Medicaid researchers. The complexity of TAF data coupled with Medicaid's decentralized nature results in variations in data collection and reporting practices both across states and over time. These inconsistencies impact data quality and complicate researchers' ability to conduct crucial longitudinal and multi-state analyses.

Development of the TAF Analysis Reporting Checklist

Recognizing the need for transparency and reproducibility in TAF-based research, theMedicaid Data Learning Network (MDLN), a consortium managed by AcademyHealth of over 70 academic and nonprofit institutions, developed theTAF Analysis Reporting Checklist to assist researchers in conducting and reporting studies using TAF data. This tool offers guidance to researchers on addressing variations in data quality and recommends items that should be reported in TAF-based studies.

The TAF Analysis Reporting Checklist recommends reportable items in four main categories:

Data Details:Specify the TAF files used, including the file types, years, release versions, and the size of the data extract.

Analytic Sample:When applicable, describe the criteria for defining the analytic sample, such as eligibility groups, enrollment span, scope of benefits, encounter data, and dual eligibility.

State and Territory Exclusions:Identify which states or territories are included or excluded in the analysis based on data quality concerns along with the criteria used for exclusion.

Special Considerations:Provide additional methodological details, if applicable, on how spending outcomes were calculated and whether TAF data were used with predecessor Medicaid Analytic eXtract (MAX) data.

Initially drafted by a MDLN subcommittee of 11 researchers, this checklist was informed by iterative review and feedback from MDLN members; an advisory group consisting of leaders in academia, government and industry, editors of health policy journals, and the broader Medicaid research community. To learn more about the development process and see reporting examples, visitJAMA Health Forum.

The Checklist's Role in Research Quality

Transparency, reproducibility, and completeness are fundamental principles that collectively ensure the integrity and reliability of research, especially when informing critical Medicaid policy decisions. When researchers thoroughly document methodology and data used in analyses, others can validate findings and replicate results, further strengthening the evidence base. Enhancing the credibility of research facilitates trust among policymakers, practitioners, and the public, providing confidence that policy decisions are grounded in robust evidence. By standardizing TAF reporting, the checklist strengthens the ability of health services researchers to increase the real-world impact of the evidence they generate.

How to Use the TAF Analysis Reporting Checklist

This checklist represents a collective effort to promote transparency and reproducibility in TAF-based research and standardize reporting practices. Importantly, items included are offered as recommendations, not prescriptions. Not all checklist items will apply to all studies, and they can be adapted to different study designs.

For Authors:The checklist provides a structured framework to transparently document their methodologies, enhancing the reproducibility and credibility of their research. Authors should indicate whether they followed the checklist in their manuscripts. Including the checklist table in the supplementary materials is helpful for authors to demonstrate how they complied with each recommendation.

For Journal Reviewers: The checklist can be used as an aid to assess completeness of the research and identify potential biases or limitations arising from data quality issues. By providing structured feedback, reviewers can highlight areas for improved reporting, ultimately enhancing the quality of research.

The TAF Analysis Reporting Checklist is not meant to be a substitute for broader reporting checklists (e.g., theSTROBE reporting guideline for observational research or theRECORD reporting guideline for research using routinely collected health data). Rather, it is meant to complement those resources with guidance on TAF-specific methodological considerations.Authors and reviewers of Medicaid research are encouraged to integrate the TAF Analysis Reporting Checklist into study designs and reporting processes. Committing to transparent, rigorous reporting helps to safeguard data research quality, ultimately informing evidence-based policies to improve health outcomes.

VisitTAF Analysis Reporting Checklist to access the checklist and learn more. Beyond the MDLN and this checklist, AcademyHealth supports a portfolio of programs aimed to build researchers' capacity to produce policy-relevant evidence and ensure that findings reach policymakers, including two Medicaid-focused networks, theState-University Partnership Learning Network (SUPLN) and theMedicaid Outcomes Distributed Research Network (MODRN).