When the Families First Coronavirus Response Act Medicaid “continuous coverage” requirement is discontinued states will restart eligibility redeterminations, and millions of Medicaid enrollees will be at risk of losing their coverage. A lack of publicly available data on Medicaid enrollment, renewal, and disenrollment makes it difficult to understand exactly who is losing Medicaid coverage and for what reasons. Publishing timely data in an easy-to-digest, visually appealing way would help improve the transparency, accountability, and equity of the Medicaid program. This expert perspective lays out a set of priority measures that states can incorporate over time into a data dashboard to track Medicaid enrollment following the end of the continuous coverage requirement. For a detailed discussion of the current status of Medicaid enrollment and retention data collection and best practices when developing a data dashboard to display this type of information, SHVS has published a companion issue brief.
Collection of Race, Ethnicity, Language (REL) Data in Medicaid Applications: A 50-state Review of the Current Landscape
Medicaid is a vital source of health insurance coverage for low-income children, adults, and individuals with disabilities; however, many individuals in Medicaid experience significant health disparities. Collecting and monitoring data on disparities by race, ethnicity, and language is an essential first step in any effort to reduce health disparities and address health equity. Today, all state Medicaid agencies collect self-reported data on race, ethnicity, and language (REL) from applicants during the eligibility and enrollment process. However, the type and granularity of information collected varies considerably, and many states continue to face longstanding and persistent challenges in collecting complete, accurate, and consistent data on REL.
This issue brief documents how states are collecting information about race, ethnicity, and language on their Medicaid applications. The information presented here draws from the State Health Access Data Assistance Center’s (SHADAC’s) review of 50 states’ paper Medicaid applications and 33 states’ online Medicaid applications. For this resource, the authors provide an overview of REL data collection standards and examine state Medicaid application’s question structure, answer options, and instructional language. They also provide an overview of the frequency of different iterations of questions and responses and provide state examples to illustrate common and unique data collection practices. Although other design factors, such as an application’s overall length, readability, or design layout undoubtedly impact user experience (and whether or not an applicant provides complete information), the authors did not assess applicants’ user experience in this report.