Health Policy Experts: Medicaid Data Processes Must Be Improved to Achieve Equity

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A team of healthcare policy experts has examined issues around data collection in the Medicaid program, and is calling for an overhaul of the ways in which data is collected and analyzed, in order to address health equity issues.

Writing in the Forefront section of Health Affairs, Brittany L. Brown-Podgorski, Ph.D., M.P.H., Eric T. Roberts, Ph.D., and William L. Schpero, Ph.D., discuss the issues, in their article entitled “Improving Medicaid Data To Advance Racial And Ethnic Health Equity In the United States,” published online in that section on May 24. “The COVID-19 pandemic has highlighted and exacerbated health care inequities in the United States,” they write in the article. “Calls to address health care disparities have intensified, and the Biden Administration has made equity a central component of its policy agenda. The confluence of these social and political forces has reinvigorated discussion about how to address health care inequities in public insurance programs, and refocused attention on Medicaid — which now covers more than 86 million Americans — as a lever for advancing health equity.”

Further, “In 2021, the Center for Medicare and Medicaid Innovation (CMMI) explicitly added health care equity as one of its five core objectives, aspiring to “a health system that achieves equitable outcomes through high quality, affordable, patient-centered care.” CMMI has also specifically prioritized initiatives to improve care and outcomes for vulnerable and underserved populations in Medicaid. These efforts depend, however, on the ability to measure disparities in access to care, quality of care, and health outcomes by race and ethnicity. Due to lack of high-quality data, it remains impossible to fully evaluate the state of health equity in the Medicaid program.”

The problem? “A legacy of underinvestment in Medicaid data quality and inconsistent data collection across states have historically impeded examination of racial and ethnic inequities in the program.” On the one hand, the authors write, “The Centers for Medicare and Medicaid Services (CMS) has made efforts to improve Medicaid administrative data through the new Transformed Medicaid Statistical Information System (T-MSIS)  Analytic Files (TAF). Yet, CMS recently reported that in a majority of states, race and ethnicity data in the TAF were missing for more than 10 percent of enrollees and that these data were ‘unusable’ in five states and of ‘high concern’ in 17 more. CMS only identified 15 states whose TAF race and ethnicity data were of ‘low concern.’ Variation in race and ethnicity data quality across states can be attributed to the lack of federal guidance and standards for mandatory collection,” the write, noting that race- and ethnicity-related questions are currently optional fields on Medicaid enrollment forms, with some enrollees possibly opting out over distrust over how the data will be used.

The article’s authors note that “Researchers at the University of Minnesota’s State Health Access Data Assistance Center have identified three strategies to improve administrative race and ethnicity data in Medicaid. First, since questions about race and ethnicity are optional on Medicaid enrollment forms, states, through their Medicaid application forms and intake processes, should take additional steps to explain the importance of the data and how they will be used. Second, states should partner with community organizations to proactively engage with enrollees, both to seek guidance on how to improve data collection and to communicate how the data will help ensure health equity in the Medicaid program. Third, states should explore augmenting race and ethnicity data obtained via self-report with data from other sources, including vital records, electronic health records, and data from other state-administered programs (such as the Supplemental Nutrition Assistance Program). Just as Medicaid programs are generally required to conduct so-called ex parte renewals — redetermining Medicaid eligibility by pulling eligibility information from all available sources, including other state agencies — they should similarly be encouraged to draw on secondary data sources to reduce the missingness of race and ethnicity data in Medicaid.”

Brown-Podgorski and Roberts are both assistant professors in the Department of Health Policy and Management at the University of Pittsburgh School of Public Health; and Schpero is an assistant professor in the Division of Health Policy and Economics of the Department of Population Health Sciences at the Joan & Sanford I. Weill Medical College of Cornell University.

 



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